Respiratory Biofeedback Training as an Adjunct Intervention in Pulmonary Rehabilitation for Late-Stage COPD: A Pilot Trial

Respiratory Biofeedback Training as an Adjunct Intervention in Pulmonary Rehabilitation for Late-Stage COPD: A Pilot Trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Respiratory Biofeedback Training as an Adjunct Intervention in Pulmonary Rehabilitation for Late-Stage COPD: A Pilot Trial Gianvito Lagravinese, Giorgio Castellana, Maddalena Genco, Marialuisa Guglielmo, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6974767/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Jan, 2026 Read the published version in Applied Psychophysiology and Biofeedback → Version 1 posted 7 You are reading this latest preprint version Abstract Background: Chronic obstructive pulmonary disease (COPD) is associated with persistent dyspnea, reduced functional capacity, and significant cognitive and affective impairments. Pulmonary rehabilitation improves the physical and psychological condition , however residual symptoms often remain, especially in patients with advanced disease. Respiratory biofeedback training (RBT) may help modulate autonomic and emotional responses to dyspnea, offering a potential adjunctive intervention. Methods: This pilot study investigated the effects of RBT integrated into a standard program of pulmonary rehabilitation for hospitalized patients with very severe COPD (GOLD stage 4 and an mMRC dyspnea score of ≥3 despite maximal pharmacological therapy). Thirty patients were randomized to receive either standard pulmonary rehabilitation alone (control group) or in combination with daily RBT sessions for three weeks (biofeedback group). Pre- and post-treatment assessments included measures of dyspnea, functional performance, quality of life, cognitive function and mood. Data were analyzed using Bayesian repeated-measures ANOVA, and results were normalized using Minimal Clinically Important Differences (MCIDs). Results: Both groups showed significant improvements in respiratory and functional outcomes (e.g., mMRC, 6MWT), with no group differences. However, the biofeedback group demonstrated greater improvements in cognitive performance (MoCA) and depressive symptoms (HADS-D). Conclusions: While RBT did not enhance dyspnea or physical performance in patients receiving inpatient pulmonary rehabilitation, it was associated with significant gains in cognitive and emotional outcomes. These findings suggest that RBT may serve as a valuable neuropsychological adjunct in the management of late-stage COPD. COPD biofeedback dyspnea pulmonary rehabilitation cognition depression quality of life Figures Figure 1 Figure 2 Figure 3 1. Introduction Chronic obstructive pulmonary disease (COPD) is a progressive respiratory disorder characterized by airflow limitation, dyspnea, and significant extrapulmonary manifestations, including cognitive and emotional impairments (Dodd et al., 2010 ; Cleutjens et al., 2016 ). The Official American Thoracic Society Statement defines dyspnea as a subjective experience of respiratory discomfort characterized by sensations that vary in intensity, unpleasantness, and emotional-behavioral significance (Parshall et al., 2012 ). Its mechanisms are complex, involving physiological, psychological, and emotional factors (Parshall et al., 2012 ). Notably, there is often a disconnect between the severity of dyspnea and the clinical severity of the underlying disease; some patients report intense dyspnea despite mild disease, while others with severe pathology remain minimally symptomatic (Banzett et al., 2000 ; Jack et al., 2004 ; Teeter & Bleecker, 1998 ). For this reason. dyspnea in COPD is thought to arise from two interconnected mechanisms: a discriminative process that brings respiratory sensations into awareness and a cognitive-affective process shaped by attention, expectation, mood, and interpretation (De Peuter et al., 2004 ). As dyspnea worsens, it contributes to a cycle of physical inactivity, muscle deconditioning, and kinesiophobia, reducing adherence to rehabilitation and diminishing quality of life (Roche, 2009 ). Pulmonary rehabilitation improves exercise capacity, reduces symptoms, and enhances quality of life in chronic respiratory disease (Donner et al., 2020 ; Spruit et al., 2013 ), but some patients continue to experience debilitating dyspnea despite optimal treatment. Although breathing is primarily automatic, it can be consciously modulated. Biofeedback facilitates this by providing real-time physiological feedback, enabling voluntary control over breathing (Khazan, 2013 ; Schwartz & Andrasik, 2017 ). It has shown benefits in conditions including hypertension, anxiety, sleep disturbances, and chronic pain (Fournié et al., 2021 ), with emerging evidence supporting its role in respiratory diseases (Gevirtz, 2013 ; Lehrer & Moritz, 2023 ; Estève et al., 1996 ). In asthma, heart rate variability biofeedback has reduced medication use and improved symptom severity, though pulmonary function changes may include placebo effects (Lehrer et al., 2004 ; Lehrer & Moritz, 2023 ). Despite positive outcomes, broader adoption is hindered by incomplete understanding of the intervention’s key components (Lehrer & Moritz, 2023 ). In COPD, devices like Flutter have improved lung function and sputum clearance (Kaja et al., 2023), with biofeedback training also linked to improved function and quality of life (Giardino et al., 2004 ; Yucha & Montgomery, 2008 ). Similar results have been reported in cystic fibrosis (Delk et al., 1994 ). This study investigates the efficacy of respiratory biofeedback training in hospitalized COPD patients, focusing on dyspnea reduction, cognitive-affective outcomes, functional capacity, and quality of life. 2. Materials and Methods The study included 35 inpatients with COPD, diagnosed according to GOLD guidelines, admitted to the Pulmonary Rehabilitation Unit at ICS Maugeri in Bari, Italy. Inclusion criteria required FEV1 post brodilatation < 30% (GOLD stage 4) and an mMRC dyspnea score of ≥ 3 despite maximal pharmacological therapy (Bestall et al., 1999 ). Exclusion criteria included acute exacerbations, non-respiratory conditions, neurological or psychiatric disorders, cognitive deficits, or contraindications to rehabilitation. Participants were randomly assigned to a control or RBT group using Research Randomizer software (Urbaniak & Plous, n.d.) (see Fig. 1). All participants underwent a standard pulmonary rehabilitation program: two weekly 30-minute strength training sessions with elastic bands or weights (target Borg score 4–5), five weekly 36-minute endurance sessions on a cycle ergometer beginning at 60% of peak 6MWT performance and adjusted per Maltais et al. ( 1996 ), and one weekly 45-minute educational session addressing lifestyle, dyspnea management, and COPD therapies. The RBT group also received 15 respiratory training sessions (35 minutes/day, five days/week for three weeks), modeled on van Gestel et al. ( 2012 ). Training focused on correcting dysfunctional breathing patterns—rapid shallow breathing, irregular rhythm, and thoracic over-reliance—through diaphragmatic techniques guided by real-time visual and auditory feedback. Physiological signals were monitored via abdominal sensors and BVP on the index finger, transmitted to the ProComp5 Infiniti system and visualized through Biograph Infiniti software (Thought Technology, Montreal, Canada). At baseline assessments included the mMRC (Bestall et al., 1999 ), Barthel Dyspnea Index (Vitacca et al, 2016 ), CAT (Jones et al, 2014), six-minute walk test (6MWT) (Holland et al., 2014 ; ATS, 2002), ABG, spirometry, and quality of life questionnaires (EUROQOL-5D, SGRQ) (Jones et al., 1992 ; Balestroni et al., 2012). Psychological and cognitive assessments comprised the MoCA and HADS (Santangelo et al., 2015 ; Iani et al., 2014 ). Medication use, oxygen therapy, and ventilation were tracked during the intervention. At the end of the training period, a re-test was conducted employing psychological, cognitive, respiratory, and quality of life questionnaires. Data analysis used Bayesian repeated-measures ANOVA (JASP, Version 0.19.3) to evaluate main effects of Time, Group, and their interaction, with model selection guided by Bayes factors (BF₁₀, BFincl) (Lee et al., 2014). Pre-post changes were normalized using MCIDs to assess clinical relevance (Norman et al., 2003 ; Jaeschke et al., 1989 ), with values ≥ 1 reflecting meaningful improvement. 3. Results A total of 30 participants (Biofeedback group = 15; Control group = 15) completed the study. Table 1 presents demographic and clinical characteristics. Five participants did not complete the intervention: two withdrew, one was discharged early, one was transferred due to complications, and one deceased. On average, participants completed 13.53 ± 1.68 of the 15 planned sessions. Results are reported across three domains: (1) respiratory symptoms and functional performance, (2) quality of life and disease impact, and (3) cognitive and emotional functioning. Bayesian repeated-measures ANOVA was applied to examine Time (pre vs post), Group (Biofeedback vs Control), and Time × Group interaction. Model comparison used Bayes factors (BF₁₀), and effect inclusion was assessed using BFincl values. MCID-normalized changes support clinical interpretation. Full statistics are in Appendix Table 1. At baseline, no significant differences were found between groups (p > .05), except on the MoCA Attention subscale, where the Biofeedback group scored higher (p = .032). Table 1 Demographic and Medical Characteristics of Participants by Group Control group (N = 15) Biofeedback group (N = 15) p value M (SD) M (SD) Age 72.67 (7.45) 71.07 (7.27) 0.604 Years of education 9.00 (3.40) 10.33 (3.58) 0.263 BMI 27.89 (6.04) 25.86 (4.88) 0.239 N (%) N (%) Sex 1.000 Male 14 (93.33) 14 (93.33) Female 1 (6.67) 1 (6.67) Medical condition Cardiomyopathy 6 (40.00) 7 (46.67) 1.000 Ischemic cardiopathy 1 (6.67) 1 (6.67) 1.000 Dilated cardiomyopathy 0 (0.00) 0 (0.00) — Hypertensive heart disease 5 (33.33) 4 (26.67) 1.000 High blood pressure 5 (33.33) 13 (86.67) 0.008 Atrial fibrillation 2 (13.33) 3 (20.00) 1.000 Dyslipidemia 6 (40.00) 8 (53.33) 0.715 Vasculopathy TSA/Aorta 4 (26.67) 4 (26.67) 1.000 Sarcopenia/Muscle Atrophy 2 (13.33) 4 (26.67) 0.651 Diabetes Mellitus 4 (26.67) 3 (20.00) 1.000 Respiratory failure Latent exertional respiratory failure 3 (20.00) 7 (46.67) 0.245 Chronic Hypoxemic 1 (6.67) 2 (13.33) 1.000 Chronic Hypoxemic-Hypercapnic 7 (46.67) 3 (20.00) 0.245 COPD Emphysematous 6 (40.00) 2 (13.33) 0.700 Overlap 9 (60.00) 13 (86.67) 0.700 Received therapy Oxygen therapy 13 (86.67) 9 (60.00) 0.215 CPAP/NIV 7 (46.67) 9 (60.00) 0.715 Endurance training Cycle Ergometer 0 Watt 6 (40.00) 5 (33.33) 1.000 Cyclette/Treadmill 9 (60.00) 10 (66.67) 1.000 Airway clearance 3 (20.00) 4 (26.67) 1.000 Note. p values refer to Mann–Whitney U tests (for continuous variables) and Fisher’s exact test (for categorical variables), used to examine potential statistical differences between groups. Respiratory Symptoms and Functional Outcomes Across the CAT, mMRC, and Barthel Dyspnea scales, the model including only the effect of Time was consistently best supported (BF₁₀ = 1). There was extreme evidence for improvement over time: CAT (BFincl = 1549.29), mMRC (BFincl = 28,464.29), and Barthel Dyspnea (BFincl = 81,913.38). Evidence for a Time × Group interaction was weak to moderate (BFincl range: 0.46–0.60). Functional measures followed a similar pattern. For the SPPB, Time was strongly supported (BFincl = 810.63), and interaction effects were minimal (BFincl = 0.55). The 6MWT also showed significant improvements over time (BFincl = 320.38), with weak support for interaction (BFincl = 0.78). These results indicate that both groups benefitted significantly from standard rehabilitation, with no additional gains from biofeedback in these domains. Quality of Life and Disease Impact The SGRQ total score improved significantly over time (BF₁₀ = 1; BFincl = 1276.50), with minimal support for interaction (BFincl = 1.31). Similarly, the EQ-5D showed moderate evidence for Time (BFincl = 2.26) and limited evidence against the interaction effect (BFincl = 0.54). While both groups improved, the Biofeedback group showed slightly greater improvements in the EQ-5D "Usual Activities" dimension, though overall group differences remained inconclusive. Cognitive and Emotional Outcomes Cognitive outcomes revealed more substantial differences. The MoCA total score favored the full model with Time, Group, and interaction effects (BF₁₀ = 1). Evidence was strong for Time (BFincl = 690.62), Group (BFincl = 15.10), and the Time × Group interaction (BFincl = 20.41). Subdomain analysis showed meaningful interaction effects in Memory Recall (BFincl = 4.71) and Naming (BFincl = 5.62), with greater gains in the Biofeedback group. Other domains, like Executive Function and Attention, showed higher baseline scores in the Biofeedback group but no significant interactions. For anxiety (HADS-A), the model including Time and Group was best supported (BF₁₀ = 1), with moderate evidence for both (BFincl = 2.65 and 3.01), and weak evidence against interaction (BFincl = 0.77). In contrast, depression scores (HADS-D) supported the full model (BF₁₀ = 1), with strong evidence for Time (BFincl = 5.40), Group (BFincl = 10.68), and interaction (BFincl = 8.92). These results indicate greater emotional improvements in the Biofeedback group, particularly for depression. A summary of changes in all main outcomes is presented in Fig. 2 . Normalized MCID To aid clinical interpretation, Fig. 3 presents pre-post changes normalized by MCID. Negative values reflect symptom improvement (e.g., dyspnea, depression), and positive values indicate functional or cognitive enhancement. Dashed lines at ± 1 represent clinical significance thresholds. Both groups experienced meaningful improvements in respiratory and functional domains. However, the Biofeedback group showed notably greater gains in cognitive and emotional outcomes. MoCA improvements exceeded four times the MCID, while changes in the Control group did not reach clinical relevance. Depression scores (HADS-D) improved beyond the MCID in the Biofeedback group only. Quality of life (SGRQ) improved in both groups, with slightly larger—but not clinically significant—gains in the Biofeedback group. In summary, while standard rehabilitation effectively improved physical and respiratory outcomes across groups, the biofeedback intervention was associated with greater benefits in cognitive and emotional functioning, suggesting a potentially unique therapeutic role for respiratory biofeedback in advanced COPD. 4. Discussion In contrast to prior studies reporting reductions in dyspnea following biofeedback interventions in COPD (Giardino et al., 2004 ; De Souto Barbosa et al., 2023 ), our Bayesian analysis did not support a clear advantage of biofeedback-enhanced physiotherapy over standard rehabilitation for reducing breathlessness. For instance, De Souto Barbosa et al. ( 2023 ) observed improvements in dyspnea and 6MWT performance, highlighting the synergistic potential of combining respiratory training with biofeedback. Similarly, Giardino et al. ( 2004 ) and Wu et al. ( 2024 ) reported broad benefits, including improved autonomic regulation and subjective respiratory relief, suggesting biofeedback exerts both physiological and psychological effects. Our study did not reveal significant between-group differences in standard clinical outcomes such as CAT, SPPB, or 6MWT. This divergence likely reflects differences in patient characteristics and treatment settings. Unlike prior studies involving patients with mild-to-moderate disease, our cohort consisted exclusively of individuals with very severe COPD (GOLD 4) in maximal pharmacological therapy, all undergoing comprehensive inpatient rehabilitation. These patients had already received maximal conventional therapy. In this context, biofeedback was implemented as a supplementary, last-resort intervention—potentially limiting its observable additive impact due to ceiling effects in physical performance. Although respiratory biofeedback may be more effective in earlier stages of the disease, when residual autonomic plasticity is preserved, our results demonstrated clinically meaningful within-group improvements in cognition (MoCA) and depressive symptoms (HADS-D) among patients in the biofeedback group. This suggests that biofeedback may provide unique benefits in neuropsychological domains often under-addressed by traditional pulmonary rehabilitation programs. These findings support emerging frameworks that emphasize the interconnectedness of physiological regulation and cognitive-emotional functioning in COPD (Dodd et al., 2010 ; Cleutjens et al., 2016 ). Cognitive impairments and affective disturbances are highly prevalent in late-stage COPD and often resist pharmacological and exercise-based interventions. The observed improvements in executive function, attention, and memory may reflect enhanced autonomic balance and cerebral perfusion, consistent with prior studies linking HRV biofeedback to modulation of fronto-limbic networks (Giardino et al., 2004 ; Wu et al., 2024 ). Furthermore, the significant reduction in depressive symptoms in the biofeedback group highlights its psychological utility. Mechanisms likely include increased self-efficacy, emotional self-regulation, and improved interoceptive awareness—factors known to enhance emotional resilience. These effects are consistent with prior research suggesting that biofeedback enhances perceived control and reduces psychological distress (Chen & Guo, 2016 ). Although physical performance did not significantly differ between groups, the biofeedback group reported larger improvements in health-related quality of life (SGRQ), nearing the threshold of clinical relevance. This suggests that biofeedback may indirectly influence functional outcomes by boosting emotional well-being and motivation. Given that poor adherence is a major barrier in COPD rehabilitation, improvements in engagement and mood could have long-term functional implications (Chen et al., 2015 ). Overall, our findings emphasize the importance of tailoring biofeedback interventions based on disease stage and therapeutic setting. While early-stage COPD patients may gain more from biofeedback in terms of physical outcomes, those with advanced disease may benefit primarily in cognitive and emotional domains. The use of MCID-normalized outcomes in our analysis underscores the clinical significance of these changes, even in the absence of between-group differences in conventional respiratory endpoints. Importantly, the observed gains in psychological and cognitive functioning—domains critical for long-term rehabilitation success—support the inclusion of biofeedback in multidimensional COPD care models. These results align with current calls for broader frameworks that incorporate neuropsychological and behavioral metrics alongside traditional pulmonary indices (Bonini et al., 2020 ; Demeyer et al., 2016). Our study also presents several methodological strengths. Conducted in a high-intensity, real-world rehabilitation setting, it provides strong translational relevance. By targeting a severely impaired clinical subgroup with limited treatment options, we address a significant gap in the literature. The protocol was rigorously standardized, delivered by trained personnel using validated, multimodal biofeedback tools, ensuring high fidelity and reproducibility. We also used a robust analytic framework, combining Bayesian statistics with MCID-based interpretation, offering nuanced insight into treatment effects in small, heterogeneous samples. Adherence to the intervention was high despite the complexity of the patient population, supporting its feasibility and acceptability in clinical practice. Future research should explore the neurobiological mechanisms underlying biofeedback's cognitive and emotional effects, potentially using fMRI or near-infrared spectroscopy to examine brain-heart interactions. Large-scale, multicenter trials with extended follow-up are needed to determine the durability of these effects and their impact on outcomes such as hospital readmissions and mortality. Combining biofeedback with behavioral therapies (e.g., CBT or mindfulness) may also enhance its psychological impact, particularly in patients with high emotional comorbidity. Implementation science will be essential to identify barriers in resource-limited or home-care environments. In conclusion, this pilot study contributes to the growing body of evidence supporting the use of respiratory biofeedback in advanced COPD. Although biofeedback did not yield superior outcomes in physical performance or dyspnea, it produced clinically meaningful improvements in cognitive function, depressive symptoms, and quality of life. These findings suggest that biofeedback may be a valuable adjunctive tool for addressing psychological and cognitive challenges in late-stage COPD, especially when conventional options have been exhausted. While not a replacement for standard rehabilitation, biofeedback offers a complementary approach that supports holistic, multidimensional care. Declarations Author Contributions: Conceptualization, G.L., M.N., G.C., M.G. Writing—original draft, G.L., M.N., M.G., M.G. Writing—review & editing, G.L., M.C., I.A.C., M.A., P.B.,S.T. P.G., All authors have read and agreed to the published version of the manuscript. Funding: This work was supported by the Ricerca Corrente funding scheme of the Ministry of Health, Italy. Informed Consent Statement: written informed consent was obtained from patients for publication of this study. The institutional ethics committee of IRCCS Maugeri of Bari approved this study. Acknowledgements: We extend our heartfelt gratitude to Prof. Giorgio Bertolotti, Dr. Luciana Lorenzon, Luca Righetto and Dr. Gabriele Ciccarese for their invaluable guidance, steadfast support, and unwavering commitment to compassionate care. We are equally grateful to the Biofeedback Federation of Europe Meetings, whose ongoing contributions to knowledge exchange and innovation continue to inspire our efforts to advance the management of complex medical conditions. Data Availability Statement: The patient’s personal data are protected according to the GDRP regulations of Italy and the EU. Conflicts of Interest: The authors declare no conflict of interest. References ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. (2002). ATS statement: guidelines for the six-minute walk test. American Journal Of Respiratory And Critical Care Medicine , 166 , 111–117. Balestroni, G., & Bertolotti, G. (2012). EuroQol-5D (EQ-5D): an instrument for measuring quality of life. Monaldi Archives for Chest Disease , 78 (3). Banzett, R. B., Dempsey, J. A., O'Donnell, D. E., & Wamboldt, M. Z. (2000). Symptom perception and respiratory sensation in asthma. American journal of respiratory and critical care medicine , 162 (3 Pt 1), 1178–1182. https://doi.org/10.1164/ajrccm.162.3.9909112 Bestall, J. C., Paul, E. A., Garrod, R., Garnham, R., Jones, P. W., & Wedzicha, J. A. (1999). Usefulness of the Medical Research Council (MRC) dyspnoea scale as a measure of disability in patients with chronic obstructive pulmonary disease. Thorax , 54 (7), 581–586. https://doi.org/10.1136/thx.54.7.581 Bonini, M., Di Paolo, M., Bagnasco, D., Baiardini, I., Braido, F., Caminati, M., Carpagnano, E., Contoli, M., Corsico, A., Del Giacco, S., Heffler, E., Lombardi, C., Menichini, I., Milanese, M., Scichilone, N., Senna, G., & Canonica, G. W. (2020). Minimal clinically important difference for asthma endpoints: an expert consensus report. European respiratory review: an official journal of the European Respiratory Society , 29 (156), 190137. https://doi.org/10.1183/16000617.0137-2019 Chen, Y., & Guo, S. (2016). Perceives and experiences of participating in a combined biofeedback with pulmonary rehabilitative exercise training program for patients with chronic obstructive pulmonary disease. European Respiratory Journal , 48. https://doi.org/10.1183/13993003.CONGRESS-2016.PA1387 Chen, Y., Huang, L., & Perng, W. (2015). Biofeedback for improving the effectiveness of pulmonary rehabilitation exercise in patients with chronic obstructive pulmonary disease. European Respiratory Journal , 46. https://doi.org/10.1183/13993003.CONGRESS-2015.PA542 Cleutjens, F. A., Franssen, F. M., Spruit, M. A., Vanfleteren, L. E., Gijsen, C., Dijkstra, J. B., Ponds, R. W., Wouters, E. F., & Janssen, D. J. (2016). Domain-specific cognitive impairment in patients with COPD and control subjects. International journal of chronic obstructive pulmonary disease , 12 , 1–11. https://doi.org/10.2147/COPD.S119633 De Peuter, S., Van Diest, I., Lemaigre, V., Verleden, G., Demedts, M., & Van den Bergh, O. (2004). Dyspnea: the role of psychological processes. Clinical psychology review , 24 (5), 557–581. https://doi.org/10.1016/j.cpr.2004.05.001 de Barbosa, S., Fernandes, J. V. N. S. F., da Silva, A. T., da Silva Leal, J. L., de Aquino Santos, L., de Souza Lima, M. L. B., J. M., & Leite, J. C. (2023). Effectiveness of Paced Breathing Guided by Biofeedback on Clinical and Functional Outcomes Patients with Chronic Obstructive Pulmonary Disease: An Uncontrolled Pilot Study. Applied psychophysiology and biofeedback , 48 (4), 423–432. https://doi.org/10.1007/s10484-023-09591-5 Delk, K. K., Gevirtz, R., Hicks, D. A., Carden, F., & Rucker, R. (1994). The effects of biofeedback assisted breathing retraining on lung functions in patients with cystic fibrosis. Chest , 105 (1), 23–28. https://doi.org/10.1378/chest.105.1.23 Demeyer, H., Burtin, C., Van Remoortel, H., Hornikx, M., Langer, D., Decramer, M., Gosselink, R., Janssens, W., & Troosters, T. (2014). Standardizing the analysis of physical activity in patients with COPD following a pulmonary rehabilitation program. Chest , 146 (2), 318–327. https://doi.org/10.1378/chest.13-1968 Dodd, J. W., Getov, S. V., & Jones, P. W. (2010). Cognitive function in COPD. The European respiratory journal , 35 (4), 913–922. https://doi.org/10.1183/09031936.00125109 Donner, C., Ambrosino, N., & Goldstein, R. S. (Eds.). (2020). Pulmonary rehabilitation . CRC. Estève, F., Blanc-Gras, N., Gallego, J., & Benchetrit, G. (1996). The effects of breathing pattern training on ventilatory function in patients with COPD. Biofeedback and self-regulation , 21 (4), 311–321. https://doi.org/10.1007/BF02214431 Fournié, C., Chouchou, F., Dalleau, G., Caderby, T., Cabrera, Q., & Verkindt, C. (2021). Heart rate variability biofeedback in chronic disease management: A systematic review. Complementary therapies in medicine , 60 , 102750. https://doi.org/10.1016/j.ctim.2021.102750 Gevirtz, R. (2013). The promise of heart rate variability biofeedback: Evidence-based application. Biofeedback , 41 (3), 110–120. https://doi.org/10.5298/1081-5937-41.3.01 Giardino, N. D., Chan, L., & Borson, S. (2004). Combined heart rate variability and pulse oximetry biofeedback for chronic obstructive pulmonary disease: preliminary findings. Applied psychophysiology and biofeedback , 29 (2), 121–133. https://doi.org/10.1023/b:apbi.0000026638.64386.89 Holland, A. E., Spruit, M. A., Troosters, T., Puhan, M. A., Pepin, V., Saey, D., McCormack, M. C., Carlin, B. W., Sciurba, F. C., Pitta, F., Wanger, J., MacIntyre, N., Kaminsky, D. A., Culver, B. H., Revill, S. M., Hernandes, N. A., Andrianopoulos, V., Camillo, C. A., Mitchell, K. E., Lee, A. L., & Singh, S. J. (2014). An official European Respiratory Society/American Thoracic Society technical standard: field walking tests in chronic respiratory disease. The European respiratory journal , 44 (6), 1428–1446. https://doi.org/10.1183/09031936.00150314 Iani, L., Lauriola, M., & Costantini, M. (2014). A confirmatory bifactor analysis of the Hospital Anxiety and Depression Scale in an Italian community sample. Health and quality of life outcomes , 12 , 84. https://doi.org/10.1186/1477-7525-12-84 Jack, S., Rossiter, H. B., Pearson, M. G., Ward, S. A., Warburton, C. J., & Whipp, B. J. (2004). Ventilatory responses to inhaled carbon dioxide, hypoxia, and exercise in idiopathic hyperventilation. American journal of respiratory and critical care medicine , 170 (2), 118–125. https://doi.org/10.1164/rccm.200207-720OC Jaeschke, R., Singer, J., & Guyatt, G. H. (1989). Measurement of health status. Ascertaining the minimal clinically important difference. Controlled clinical trials , 10 (4), 407–415. https://doi.org/10.1016/0197-2456(89)90005-6 JASP Team (2024). JASP (Version 0.19.3)[Computer software]. Jones, P. W., Harding, G., Berry, P., Wiklund, I., Chen, W. H., & Leidy, K., N (2009). Development and first validation of the COPD Assessment Test. The European respiratory journal , 34 (3), 648–654. https://doi.org/10.1183/09031936.00102509 Jones, P. W., Quirk, F. H., Baveystock, C. M., & Littlejohns, P. (1992). A self-complete measure of health status for chronic airflow limitation. The St. George's Respiratory Questionnaire. The American review of respiratory disease , 145 (6), 1321–1327. https://doi.org/10.1164/ajrccm/145.6.1321 Khazan, I. Z. (2013). The clinical handbook of biofeedback: A step-by-step guide for training and practice with mindfulness . Wiley. Lee, M. D., & Wagenmakers, E. J. (2014). Bayesian cognitive modeling: A practical course . Cambridge University Press. Lehrer, P., & Moritz, G. (2023). Biofeedback has therapeutic effects on asthma, although additional research is needed to document specificity. Policy Insights from the Behavioral and Brain Sciences , 10 (1), 83–89. https://doi.org/10.1177/23727322221145306 Lehrer, P. M., Vaschillo, E., Vaschillo, B., Lu, S. E., Scardella, A., Siddique, M., & Habib, R. H. (2004). Biofeedback treatment for asthma. Chest , 126 (2), 352–361. https://doi.org/10.1378/chest.126.2.352 Maltais, F., LeBlanc, P., Simard, C., Jobin, J., Bérubé, C., Bruneau, J., Carrier, L., & Belleau, R. (1996). Skeletal muscle adaptation to endurance training in patients with chronic obstructive pulmonary disease. American journal of respiratory and critical care medicine , 154 (2 Pt 1), 442–447. https://doi.org/10.1164/ajrccm.154.2.8756820 Kaja, R., Vaiyapuri, A., Sirajudeen, M. S., Muthusamy, H., Unnikrishnan, R., Waly, M., Devaraj, S. S. D., & Seyam, M. K.,S, G. N (2020). Biofeedback flutter device for managing the symptoms of patients with COPD. Technology and health care: official journal of the European Society for Engineering and Medicine , 28 (5), 477–485. https://doi.org/10.3233/THC-202222 Norman, G. R., Sloan, J. A., & Wyrwich, K. W. (2003). Interpretation of changes in health-related quality of life: the remarkable universality of half a standard deviation. Medical care , 41 (5), 582–592. https://doi.org/10.1097/01.MLR.0000062554.74615.4C Parshall, M. B., Schwartzstein, R. M., Adams, L., Banzett, R. B., Manning, H. L., Bourbeau, J., Calverley, P. M., Gift, A. G., Harver, A., Lareau, S. C., Mahler, D. A., Meek, P. M., O'Donnell, D. E., & American Thoracic Society Committee on Dyspnea. (2012). An official American Thoracic Society statement: update on the mechanisms, assessment, and management of dyspnea. American journal of respiratory and critical care medicine , 185 (4), 435–452. https://doi.org/10.1164/rccm.201111-2042ST Roche, N. (2009). Activity limitation: a major consequence of dyspnoea in COPD. European respiratory review: an official journal of the European Respiratory Society , 18 (112), 54–57. https://doi.org/10.1183/09059180.00001309 Santangelo, G., Siciliano, M., Pedone, R., Vitale, C., Falco, F., Bisogno, R., Siano, P., Barone, P., Grossi, D., Santangelo, F., & Trojano, L. (2015). Normative data for the Montreal Cognitive Assessment in an Italian population sample. Neurological sciences: official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology , 36 (4), 585–591. https://doi.org/10.1007/s10072-014-1995-y Schwartz, M. S., & Andrasik, F. (Eds.). (2017). Biofeedback: A practitioner's guide . Guilford. Spruit, M. A., Singh, S. J., Garvey, C., ZuWallack, R., Nici, L., Rochester, C., Hill, K., Holland, A. E., Lareau, S. C., Man, W. D., Pitta, F., Sewell, L., Raskin, J., Bourbeau, J., Crouch, R., Franssen, F. M., Casaburi, R., Vercoulen, J. H., Vogiatzis, I., & Gosselink, R. (2013). Society statement: key concepts and advances in pulmonary rehabilitation. American journal of respiratory and critical care medicine , 188 (8), e13–e64. https://doi.org/10.1164/rccm.201309-1634ST . ATS/ERS Task Force on Pulmonary RehabilitationAn official American Thoracic Society/European Respiratory. Teeter, J. G., & Bleecker, E. R. (1998). Relationship between airway obstruction and respiratory symptoms in adult asthmatics. Chest , 113 (2), 272–277. https://doi.org/10.1378/chest.113.2.272 Urbaniak, G. C., & Plous, S. (2023). Research randomizer (version 4.0)[computer software] . van Gestel, A. J., Kohler, M., Steier, J., Teschler, S., Russi, E. W., & Teschler, H. (2012). The effects of controlled breathing during pulmonary rehabilitation in patients with COPD. Respiration; international review of thoracic diseases , 83 (2), 115–124. https://doi.org/10.1159/000324449 Vitacca, M., Paneroni, M., Baiardi, P., De Carolis, V., Zampogna, E., Belli, S., Carone, M., Spanevello, A., Balbi, B., & Bertolotti, G. (2016). Development of a Barthel Index based on dyspnea for patients with respiratory diseases. International journal of chronic obstructive pulmonary disease , 11 , 1199–1206. https://doi.org/10.2147/COPD.S104376 Wu, D. W., Yang, P. C., & Lin, I. M. (2024). Effects of heart rate variability (HRV) biofeedback in pulmonary indicators and HRV indices among patients with chronic obstructive pulmonary disease. Applied Psychophysiology and Biofeedback , 1–12. Yucha, C., & Montgomery, D. (2008). Evidence-based practice in biofeedback and neurofeedback . AAPB. Additional Declarations No competing interests reported. Supplementary Files APPENDIX.docx Cite Share Download PDF Status: Published Journal Publication published 14 Jan, 2026 Read the published version in Applied Psychophysiology and Biofeedback → Version 1 posted Editorial decision: Revision requested 14 Nov, 2025 Reviews received at journal 12 Aug, 2025 Reviewers agreed at journal 15 Jul, 2025 Reviewers invited by journal 11 Jul, 2025 Editor assigned by journal 25 Jun, 2025 Submission checks completed at journal 25 Jun, 2025 First submitted to journal 25 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6974767","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":484982800,"identity":"b210ccee-798d-4c10-a914-9c8813dd499a","order_by":0,"name":"Gianvito Lagravinese","email":"data:image/png;base64,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","orcid":"","institution":"Istituti Clinici Scientifici Maugeri, Laboratory of Neuropsychology","correspondingAuthor":true,"prefix":"","firstName":"Gianvito","middleName":"","lastName":"Lagravinese","suffix":""},{"id":484982801,"identity":"4eae7389-1b39-45da-9a1e-e6e7898ab7d9","order_by":1,"name":"Giorgio Castellana","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri, Respiratory Unit of Bari Institute","correspondingAuthor":false,"prefix":"","firstName":"Giorgio","middleName":"","lastName":"Castellana","suffix":""},{"id":484982802,"identity":"b5126c57-1a92-4679-aae3-25921b107b1e","order_by":2,"name":"Maddalena Genco","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri, Respiratory Unit of Bari Institute","correspondingAuthor":false,"prefix":"","firstName":"Maddalena","middleName":"","lastName":"Genco","suffix":""},{"id":484982803,"identity":"be8984d2-279d-4049-9d5e-e811d2df5a78","order_by":3,"name":"Marialuisa Guglielmo","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri, Laboratory of Neuropsychology","correspondingAuthor":false,"prefix":"","firstName":"Marialuisa","middleName":"","lastName":"Guglielmo","suffix":""},{"id":484982804,"identity":"8ff7afb0-d094-420f-84bb-f958fff1513b","order_by":4,"name":"Serena Tagliente","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri, Laboratory of Neuropsychology","correspondingAuthor":false,"prefix":"","firstName":"Serena","middleName":"","lastName":"Tagliente","suffix":""},{"id":484982805,"identity":"64a3c535-f73d-4131-9833-1385851d4ea1","order_by":5,"name":"Patrizia Guido","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri, Respiratory Unit of Bari Institute","correspondingAuthor":false,"prefix":"","firstName":"Patrizia","middleName":"","lastName":"Guido","suffix":""},{"id":484982808,"identity":"55d8f5b5-d7d2-4b3e-b7cb-4be860324e5e","order_by":6,"name":"Ioannis Alexandros Charitos","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri, Respiratory Unit of Bari Institute","correspondingAuthor":false,"prefix":"","firstName":"Ioannis","middleName":"Alexandros","lastName":"Charitos","suffix":""},{"id":484982809,"identity":"44c9b3d6-4b27-450e-ba38-225a228094cb","order_by":7,"name":"Maria Aliani","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri, Respiratory Unit of Bari Institute","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Aliani","suffix":""},{"id":484982811,"identity":"14d71fc6-47ad-4b8e-8c2e-3ce37dcec66d","order_by":8,"name":"Petronilla Battista","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri, Laboratory of Neuropsychology","correspondingAuthor":false,"prefix":"","firstName":"Petronilla","middleName":"","lastName":"Battista","suffix":""},{"id":484982812,"identity":"924c87fa-fe16-4d86-9b2d-646d8b5f0018","order_by":9,"name":"Mattia Nese","email":"","orcid":"","institution":"Sigmund Freud University","correspondingAuthor":false,"prefix":"","firstName":"Mattia","middleName":"","lastName":"Nese","suffix":""},{"id":484982814,"identity":"b2a1d7b4-af20-461a-af10-59c894607891","order_by":10,"name":"Mauro Carone","email":"","orcid":"","institution":"Istituti Clinici Scientifici Maugeri, Respiratory Unit of Bari Institute","correspondingAuthor":false,"prefix":"","firstName":"Mauro","middleName":"","lastName":"Carone","suffix":""}],"badges":[],"createdAt":"2025-06-25 12:38:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6974767/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6974767/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10484-025-09763-5","type":"published","date":"2026-01-14T16:29:59+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":87030461,"identity":"7b163831-04a0-440f-8ca6-c0e356b675db","added_by":"auto","created_at":"2025-07-18 12:44:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49951,"visible":true,"origin":"","legend":"\u003cp\u003eStudy protocol\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6974767/v1/87c60c963f29f13c820491f3.png"},{"id":87030464,"identity":"9913d1fe-3db7-49cc-a6eb-82a938277544","added_by":"auto","created_at":"2025-07-18 12:44:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":150506,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePre- Post-interventions Changes in All Outcome Measures.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6974767/v1/a1181f264de63d39a4c323c9.png"},{"id":87030466,"identity":"595570e2-9911-4ef6-aabd-003bb439a3e6","added_by":"auto","created_at":"2025-07-18 12:44:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38859,"visible":true,"origin":"","legend":"\u003cp\u003eMean pre-post change normalized by Minimal Clinically Important Difference (MCID)\u003c/p\u003e\n\u003cp\u003eNote. Bars represent 95% confidence intervals. Values \u0026lt; 0 indicate symptom improvement; values \u0026gt; 0 indicate functional or cognitive enhancement. Dashed lines at ±1 represent the threshold for clinical significance.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6974767/v1/fd0fa0598496c5ccffe0690e.png"},{"id":100614742,"identity":"2241830f-a78f-44f2-aa9a-ac13b6982786","added_by":"auto","created_at":"2026-01-19 17:23:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":852609,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6974767/v1/61ba899a-83ff-40a4-b8cb-351ebdb6ecb4.pdf"},{"id":87030460,"identity":"97bcdd68-81b1-4544-91cb-8e0adcfa7be1","added_by":"auto","created_at":"2025-07-18 12:44:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27463,"visible":true,"origin":"","legend":"","description":"","filename":"APPENDIX.docx","url":"https://assets-eu.researchsquare.com/files/rs-6974767/v1/5f21674b53c4a3f8e207cc3c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Respiratory Biofeedback Training as an Adjunct Intervention in Pulmonary Rehabilitation for Late-Stage COPD: A Pilot Trial","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eChronic obstructive pulmonary disease (COPD) is a progressive respiratory disorder characterized by airflow limitation, dyspnea, and significant extrapulmonary manifestations, including cognitive and emotional impairments (Dodd et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Cleutjens et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The Official American Thoracic Society Statement defines dyspnea as a subjective experience of respiratory discomfort characterized by sensations that vary in intensity, unpleasantness, and emotional-behavioral significance (Parshall et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Its mechanisms are complex, involving physiological, psychological, and emotional factors (Parshall et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Notably, there is often a disconnect between the severity of dyspnea and the clinical severity of the underlying disease; some patients report intense dyspnea despite mild disease, while others with severe pathology remain minimally symptomatic (Banzett et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Jack et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Teeter \u0026amp; Bleecker, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). For this reason. dyspnea in COPD is thought to arise from two interconnected mechanisms: a discriminative process that brings respiratory sensations into awareness and a cognitive-affective process shaped by attention, expectation, mood, and interpretation (De Peuter et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). As dyspnea worsens, it contributes to a cycle of physical inactivity, muscle deconditioning, and kinesiophobia, reducing adherence to rehabilitation and diminishing quality of life (Roche, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Pulmonary rehabilitation improves exercise capacity, reduces symptoms, and enhances quality of life in chronic respiratory disease (Donner et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Spruit et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), but some patients continue to experience debilitating dyspnea despite optimal treatment.\u003c/p\u003e\u003cp\u003eAlthough breathing is primarily automatic, it can be consciously modulated. Biofeedback facilitates this by providing real-time physiological feedback, enabling voluntary control over breathing (Khazan, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Schwartz \u0026amp; Andrasik, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It has shown benefits in conditions including hypertension, anxiety, sleep disturbances, and chronic pain (Fourni\u0026eacute; et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), with emerging evidence supporting its role in respiratory diseases (Gevirtz, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Lehrer \u0026amp; Moritz, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Est\u0026egrave;ve et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). In asthma, heart rate variability biofeedback has reduced medication use and improved symptom severity, though pulmonary function changes may include placebo effects (Lehrer et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Lehrer \u0026amp; Moritz, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite positive outcomes, broader adoption is hindered by incomplete understanding of the intervention\u0026rsquo;s key components (Lehrer \u0026amp; Moritz, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In COPD, devices like Flutter have improved lung function and sputum clearance (Kaja et al., 2023), with biofeedback training also linked to improved function and quality of life (Giardino et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Yucha \u0026amp; Montgomery, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Similar results have been reported in cystic fibrosis (Delk et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1994\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study investigates the efficacy of respiratory biofeedback training in hospitalized COPD patients, focusing on dyspnea reduction, cognitive-affective outcomes, functional capacity, and quality of life.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv class=\"BlockQuote\"\u003e\n\u003cp\u003eThe study included 35 inpatients with COPD, diagnosed according to GOLD guidelines, admitted to the Pulmonary Rehabilitation Unit at ICS Maugeri in Bari, Italy. Inclusion criteria required FEV1 post brodilatation\u0026thinsp;\u0026lt;\u0026thinsp;30% (GOLD stage 4) and an mMRC dyspnea score of \u0026ge;\u0026thinsp;3 despite maximal pharmacological therapy (Bestall et al., \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e). Exclusion criteria included acute exacerbations, non-respiratory conditions, neurological or psychiatric disorders, cognitive deficits, or contraindications to rehabilitation. Participants were randomly assigned to a control or RBT group using Research Randomizer software (Urbaniak \u0026amp; Plous, n.d.) (see Fig.\u0026nbsp;1).\u003c/p\u003e\n\u003cp\u003eAll participants underwent a standard pulmonary rehabilitation program: two weekly 30-minute strength training sessions with elastic bands or weights (target Borg score 4\u0026ndash;5), five weekly 36-minute endurance sessions on a cycle ergometer beginning at 60% of peak 6MWT performance and adjusted per Maltais et al. (\u003cspan class=\"CitationRef\"\u003e1996\u003c/span\u003e), and one weekly 45-minute educational session addressing lifestyle, dyspnea management, and COPD therapies. The RBT group also received 15 respiratory training sessions (35 minutes/day, five days/week for three weeks), modeled on van Gestel et al. (\u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e). Training focused on correcting dysfunctional breathing patterns\u0026mdash;rapid shallow breathing, irregular rhythm, and thoracic over-reliance\u0026mdash;through diaphragmatic techniques guided by real-time visual and auditory feedback. Physiological signals were monitored via abdominal sensors and BVP on the index finger, transmitted to the ProComp5 Infiniti system and visualized through Biograph Infiniti software (Thought Technology, Montreal, Canada). At baseline assessments included the mMRC (Bestall et al., \u003cspan class=\"CitationRef\"\u003e1999\u003c/span\u003e), Barthel Dyspnea Index (Vitacca et al, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e), CAT (Jones et al, 2014), six-minute walk test (6MWT) (Holland et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e; ATS, 2002), ABG, spirometry, and quality of life questionnaires (EUROQOL-5D, SGRQ) (Jones et al., \u003cspan class=\"CitationRef\"\u003e1992\u003c/span\u003e; Balestroni et al., 2012). Psychological and cognitive assessments comprised the MoCA and HADS (Santangelo et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Iani et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Medication use, oxygen therapy, and ventilation were tracked during the intervention. At the end of the training period, a re-test was conducted employing psychological, cognitive, respiratory, and quality of life questionnaires.\u003c/p\u003e\n\u003cp\u003eData analysis used Bayesian repeated-measures ANOVA (JASP, Version 0.19.3) to evaluate main effects of Time, Group, and their interaction, with model selection guided by Bayes factors (BF₁₀, BFincl) (Lee et al., 2014). Pre-post changes were normalized using MCIDs to assess clinical relevance (Norman et al., \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e; Jaeschke et al., \u003cspan class=\"CitationRef\"\u003e1989\u003c/span\u003e), with values\u0026thinsp;\u0026ge;\u0026thinsp;1 reflecting meaningful improvement.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eA total of 30 participants (Biofeedback group\u0026thinsp;=\u0026thinsp;15; Control group\u0026thinsp;=\u0026thinsp;15) completed the study. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e presents demographic and clinical characteristics. Five participants did not complete the intervention: two withdrew, one was discharged early, one was transferred due to complications, and one deceased. On average, participants completed 13.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68 of the 15 planned sessions.\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003eResults are reported across three domains: (1) respiratory symptoms and functional performance, (2) quality of life and disease impact, and (3) cognitive and emotional functioning. Bayesian repeated-measures ANOVA was applied to examine Time (pre vs post), Group (Biofeedback vs Control), and Time \u0026times; Group interaction. Model comparison used Bayes factors (BF₁₀), and effect inclusion was assessed using BFincl values. MCID-normalized changes support clinical interpretation. Full statistics are in Appendix Table\u0026nbsp;1.\u003c/p\u003e\n\u003cp\u003eAt baseline, no significant differences were found between groups (p\u0026thinsp;\u0026gt;\u0026thinsp;.05), except on the MoCA Attention subscale, where the Biofeedback group scored higher (p\u0026thinsp;=\u0026thinsp;.032).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cem\u003eDemographic and Medical Characteristics of Participants by Group\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControl group\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBiofeedback group\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72.67 (7.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71.07 (7.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYears of education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.00 (3.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.33 (3.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.263\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.89 (6.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.86 (4.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (93.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (93.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (6.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (6.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedical condition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCardiomyopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (40.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (46.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIschemic cardiopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (6.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (6.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDilated cardiomyopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertensive heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (33.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh blood pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (33.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (86.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAtrial fibrillation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (13.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (40.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (53.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.715\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVasculopathy TSA/Aorta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSarcopenia/Muscle Atrophy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (13.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.651\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLatent exertional respiratory failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (46.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic Hypoxemic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (6.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (13.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic Hypoxemic-Hypercapnic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (46.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmphysematous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (40.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (13.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverlap\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (60.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (86.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReceived therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOxygen therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (86.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (60.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCPAP/NIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (46.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (60.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.715\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEndurance training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCycle Ergometer 0 Watt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (40.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (33.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCyclette/Treadmill\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (60.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (66.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAirway clearance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (26.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003e\u003cem\u003eNote. p values refer to Mann\u0026ndash;Whitney U tests (for continuous variables) and Fisher\u0026rsquo;s exact test (for categorical variables), used to examine potential statistical differences between groups.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cspan class=\"Underline\"\u003eRespiratory Symptoms and Functional Outcomes\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003eAcross the CAT, mMRC, and Barthel Dyspnea scales, the model including only the effect of Time was consistently best supported (BF₁₀ = 1). There was extreme evidence for improvement over time: CAT (BFincl\u0026thinsp;=\u0026thinsp;1549.29), mMRC (BFincl\u0026thinsp;=\u0026thinsp;28,464.29), and Barthel Dyspnea (BFincl\u0026thinsp;=\u0026thinsp;81,913.38). Evidence for a Time \u0026times; Group interaction was weak to moderate (BFincl range: 0.46\u0026ndash;0.60).\u003c/p\u003e\n \u003cp\u003eFunctional measures followed a similar pattern. For the SPPB, Time was strongly supported (BFincl\u0026thinsp;=\u0026thinsp;810.63), and interaction effects were minimal (BFincl\u0026thinsp;=\u0026thinsp;0.55). The 6MWT also showed significant improvements over time (BFincl\u0026thinsp;=\u0026thinsp;320.38), with weak support for interaction (BFincl\u0026thinsp;=\u0026thinsp;0.78). These results indicate that both groups benefitted significantly from standard rehabilitation, with no additional gains from biofeedback in these domains.\u003c/p\u003e\n \u003cp\u003e\u003cspan class=\"Underline\"\u003eQuality of Life and Disease Impact\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003eThe SGRQ total score improved significantly over time (BF₁₀ = 1; BFincl\u0026thinsp;=\u0026thinsp;1276.50), with minimal support for interaction (BFincl\u0026thinsp;=\u0026thinsp;1.31). Similarly, the EQ-5D showed moderate evidence for Time (BFincl\u0026thinsp;=\u0026thinsp;2.26) and limited evidence against the interaction effect (BFincl\u0026thinsp;=\u0026thinsp;0.54). While both groups improved, the Biofeedback group showed slightly greater improvements in the EQ-5D \u0026quot;Usual Activities\u0026quot; dimension, though overall group differences remained inconclusive.\u003c/p\u003e\n \u003cp\u003e\u003cspan class=\"Underline\"\u003eCognitive and Emotional Outcomes\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003eCognitive outcomes revealed more substantial differences. The MoCA total score favored the full model with Time, Group, and interaction effects (BF₁₀ = 1). Evidence was strong for Time (BFincl\u0026thinsp;=\u0026thinsp;690.62), Group (BFincl\u0026thinsp;=\u0026thinsp;15.10), and the Time \u0026times; Group interaction (BFincl\u0026thinsp;=\u0026thinsp;20.41). Subdomain analysis showed meaningful interaction effects in Memory Recall (BFincl\u0026thinsp;=\u0026thinsp;4.71) and Naming (BFincl\u0026thinsp;=\u0026thinsp;5.62), with greater gains in the Biofeedback group. Other domains, like Executive Function and Attention, showed higher baseline scores in the Biofeedback group but no significant interactions.\u003c/p\u003e\n \u003cp\u003eFor anxiety (HADS-A), the model including Time and Group was best supported (BF₁₀ = 1), with moderate evidence for both (BFincl\u0026thinsp;=\u0026thinsp;2.65 and 3.01), and weak evidence against interaction (BFincl\u0026thinsp;=\u0026thinsp;0.77). In contrast, depression scores (HADS-D) supported the full model (BF₁₀ = 1), with strong evidence for Time (BFincl\u0026thinsp;=\u0026thinsp;5.40), Group (BFincl\u0026thinsp;=\u0026thinsp;10.68), and interaction (BFincl\u0026thinsp;=\u0026thinsp;8.92). These results indicate greater emotional improvements in the Biofeedback group, particularly for depression. A summary of changes in all main outcomes is presented in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eNormalized MCID\u003c/p\u003e\n \u003cp\u003eTo aid clinical interpretation, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e presents pre-post changes normalized by MCID. Negative values reflect symptom improvement (e.g., dyspnea, depression), and positive values indicate functional or cognitive enhancement. Dashed lines at \u0026plusmn;\u0026thinsp;1 represent clinical significance thresholds.\u003c/p\u003e\n \u003cp\u003eBoth groups experienced meaningful improvements in respiratory and functional domains. However, the Biofeedback group showed notably greater gains in cognitive and emotional outcomes. MoCA improvements exceeded four times the MCID, while changes in the Control group did not reach clinical relevance. Depression scores (HADS-D) improved beyond the MCID in the Biofeedback group only. Quality of life (SGRQ) improved in both groups, with slightly larger\u0026mdash;but not clinically significant\u0026mdash;gains in the Biofeedback group.\u003c/p\u003e\n \u003cp\u003eIn summary, while standard rehabilitation effectively improved physical and respiratory outcomes across groups, the biofeedback intervention was associated with greater benefits in cognitive and emotional functioning, suggesting a potentially unique therapeutic role for respiratory biofeedback in advanced COPD.\u003c/p\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eIn contrast to prior studies reporting reductions in dyspnea following biofeedback interventions in COPD (Giardino et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; De Souto Barbosa et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), our Bayesian analysis did not support a clear advantage of biofeedback-enhanced physiotherapy over standard rehabilitation for reducing breathlessness. For instance, De Souto Barbosa et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) observed improvements in dyspnea and 6MWT performance, highlighting the synergistic potential of combining respiratory training with biofeedback. Similarly, Giardino et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and Wu et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) reported broad benefits, including improved autonomic regulation and subjective respiratory relief, suggesting biofeedback exerts both physiological and psychological effects.\u003c/p\u003e\u003cp\u003eOur study did not reveal significant between-group differences in standard clinical outcomes such as CAT, SPPB, or 6MWT. This divergence likely reflects differences in patient characteristics and treatment settings. Unlike prior studies involving patients with mild-to-moderate disease, our cohort consisted exclusively of individuals with very severe COPD (GOLD 4) in maximal pharmacological therapy, all undergoing comprehensive inpatient rehabilitation. These patients had already received maximal conventional therapy. In this context, biofeedback was implemented as a supplementary, last-resort intervention\u0026mdash;potentially limiting its observable additive impact due to ceiling effects in physical performance.\u003c/p\u003e\u003cp\u003eAlthough respiratory biofeedback may be more effective in earlier stages of the disease, when residual autonomic plasticity is preserved, our results demonstrated clinically meaningful within-group improvements in cognition (MoCA) and depressive symptoms (HADS-D) among patients in the biofeedback group. This suggests that biofeedback may provide unique benefits in neuropsychological domains often under-addressed by traditional pulmonary rehabilitation programs.\u003c/p\u003e\u003cp\u003eThese findings support emerging frameworks that emphasize the interconnectedness of physiological regulation and cognitive-emotional functioning in COPD (Dodd et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Cleutjens et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Cognitive impairments and affective disturbances are highly prevalent in late-stage COPD and often resist pharmacological and exercise-based interventions. The observed improvements in executive function, attention, and memory may reflect enhanced autonomic balance and cerebral perfusion, consistent with prior studies linking HRV biofeedback to modulation of fronto-limbic networks (Giardino et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFurthermore, the significant reduction in depressive symptoms in the biofeedback group highlights its psychological utility. Mechanisms likely include increased self-efficacy, emotional self-regulation, and improved interoceptive awareness\u0026mdash;factors known to enhance emotional resilience. These effects are consistent with prior research suggesting that biofeedback enhances perceived control and reduces psychological distress (Chen \u0026amp; Guo, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough physical performance did not significantly differ between groups, the biofeedback group reported larger improvements in health-related quality of life (SGRQ), nearing the threshold of clinical relevance. This suggests that biofeedback may indirectly influence functional outcomes by boosting emotional well-being and motivation. Given that poor adherence is a major barrier in COPD rehabilitation, improvements in engagement and mood could have long-term functional implications (Chen et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOverall, our findings emphasize the importance of tailoring biofeedback interventions based on disease stage and therapeutic setting. While early-stage COPD patients may gain more from biofeedback in terms of physical outcomes, those with advanced disease may benefit primarily in cognitive and emotional domains. The use of MCID-normalized outcomes in our analysis underscores the clinical significance of these changes, even in the absence of between-group differences in conventional respiratory endpoints.\u003c/p\u003e\u003cp\u003eImportantly, the observed gains in psychological and cognitive functioning\u0026mdash;domains critical for long-term rehabilitation success\u0026mdash;support the inclusion of biofeedback in multidimensional COPD care models. These results align with current calls for broader frameworks that incorporate neuropsychological and behavioral metrics alongside traditional pulmonary indices (Bonini et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Demeyer et al., 2016).\u003c/p\u003e\u003cp\u003eOur study also presents several methodological strengths. Conducted in a high-intensity, real-world rehabilitation setting, it provides strong translational relevance. By targeting a severely impaired clinical subgroup with limited treatment options, we address a significant gap in the literature. The protocol was rigorously standardized, delivered by trained personnel using validated, multimodal biofeedback tools, ensuring high fidelity and reproducibility. We also used a robust analytic framework, combining Bayesian statistics with MCID-based interpretation, offering nuanced insight into treatment effects in small, heterogeneous samples.\u003c/p\u003e\u003cp\u003eAdherence to the intervention was high despite the complexity of the patient population, supporting its feasibility and acceptability in clinical practice.\u003c/p\u003e\u003cp\u003eFuture research should explore the neurobiological mechanisms underlying biofeedback's cognitive and emotional effects, potentially using fMRI or near-infrared spectroscopy to examine brain-heart interactions. Large-scale, multicenter trials with extended follow-up are needed to determine the durability of these effects and their impact on outcomes such as hospital readmissions and mortality. Combining biofeedback with behavioral therapies (e.g., CBT or mindfulness) may also enhance its psychological impact, particularly in patients with high emotional comorbidity. Implementation science will be essential to identify barriers in resource-limited or home-care environments.\u003c/p\u003e\u003cp\u003eIn conclusion, this pilot study contributes to the growing body of evidence supporting the use of respiratory biofeedback in advanced COPD. Although biofeedback did not yield superior outcomes in physical performance or dyspnea, it produced clinically meaningful improvements in cognitive function, depressive symptoms, and quality of life. These findings suggest that biofeedback may be a valuable adjunctive tool for addressing psychological and cognitive challenges in late-stage COPD, especially when conventional options have been exhausted. While not a replacement for standard rehabilitation, biofeedback offers a complementary approach that supports holistic, multidimensional care.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConceptualization, G.L., M.N., G.C., M.G.\u003c/p\u003e\n\u003cp\u003eWriting—original draft, G.L., M.N., M.G., M.G.\u003c/p\u003e\n\u003cp\u003eWriting—review \u0026amp; editing, G.L., M.C., I.A.C., M.A., P.B.,S.T. P.G.,\u003c/p\u003e\n\u003cp\u003eAll authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This work was supported by the Ricerca Corrente funding scheme of the Ministry of Health, Italy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u003c/strong\u003e written informed consent was obtained from patients for publication of this study. The institutional ethics committee of IRCCS Maugeri of Bari approved this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u003c/strong\u003e We extend our heartfelt gratitude to Prof. Giorgio Bertolotti, Dr. Luciana Lorenzon, Luca Righetto and Dr. Gabriele Ciccarese for their invaluable guidance, steadfast support, and unwavering commitment to compassionate care. We are equally grateful to the Biofeedback Federation of Europe Meetings, whose ongoing contributions to knowledge exchange and innovation continue to inspire our efforts to advance the management of complex medical conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The patient’s personal data are protected according to the GDRP regulations of Italy and the EU.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. (2002). ATS statement: guidelines for the six-minute walk test. \u003cem\u003eAmerican Journal Of Respiratory And Critical Care Medicine\u003c/em\u003e, \u003cem\u003e166\u003c/em\u003e, 111\u0026ndash;117.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBalestroni, G., \u0026amp; Bertolotti, G. (2012). EuroQol-5D (EQ-5D): an instrument for measuring quality of life. \u003cem\u003eMonaldi Archives for Chest Disease\u003c/em\u003e, \u003cem\u003e78\u003c/em\u003e(3).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBanzett, R. B., Dempsey, J. A., O'Donnell, D. E., \u0026amp; Wamboldt, M. Z. (2000). Symptom perception and respiratory sensation in asthma. \u003cem\u003eAmerican journal of respiratory and critical care medicine\u003c/em\u003e, \u003cem\u003e162\u003c/em\u003e(3 Pt 1), 1178\u0026ndash;1182. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1164/ajrccm.162.3.9909112\u003c/span\u003e\u003cspan address=\"10.1164/ajrccm.162.3.9909112\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBestall, J. C., Paul, E. A., Garrod, R., Garnham, R., Jones, P. W., \u0026amp; Wedzicha, J. A. (1999). Usefulness of the Medical Research Council (MRC) dyspnoea scale as a measure of disability in patients with chronic obstructive pulmonary disease. \u003cem\u003eThorax\u003c/em\u003e, \u003cem\u003e54\u003c/em\u003e(7), 581\u0026ndash;586. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/thx.54.7.581\u003c/span\u003e\u003cspan address=\"10.1136/thx.54.7.581\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBonini, M., Di Paolo, M., Bagnasco, D., Baiardini, I., Braido, F., Caminati, M., Carpagnano, E., Contoli, M., Corsico, A., Del Giacco, S., Heffler, E., Lombardi, C., Menichini, I., Milanese, M., Scichilone, N., Senna, G., \u0026amp; Canonica, G. W. (2020). Minimal clinically important difference for asthma endpoints: an expert consensus report. \u003cem\u003eEuropean respiratory review: an official journal of the European Respiratory Society\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(156), 190137. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1183/16000617.0137-2019\u003c/span\u003e\u003cspan address=\"10.1183/16000617.0137-2019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen, Y., \u0026amp; Guo, S. (2016). Perceives and experiences of participating in a combined biofeedback with pulmonary rehabilitative exercise training program for patients with chronic obstructive pulmonary disease. \u003cem\u003eEuropean Respiratory Journal\u003c/em\u003e, 48. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1183/13993003.CONGRESS-2016.PA1387\u003c/span\u003e\u003cspan address=\"10.1183/13993003.CONGRESS-2016.PA1387\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen, Y., Huang, L., \u0026amp; Perng, W. (2015). Biofeedback for improving the effectiveness of pulmonary rehabilitation exercise in patients with chronic obstructive pulmonary disease. \u003cem\u003eEuropean Respiratory Journal\u003c/em\u003e, 46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1183/13993003.CONGRESS-2015.PA542\u003c/span\u003e\u003cspan address=\"10.1183/13993003.CONGRESS-2015.PA542\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCleutjens, F. A., Franssen, F. M., Spruit, M. A., Vanfleteren, L. E., Gijsen, C., Dijkstra, J. B., Ponds, R. W., Wouters, E. F., \u0026amp; Janssen, D. J. (2016). Domain-specific cognitive impairment in patients with COPD and control subjects. \u003cem\u003eInternational journal of chronic obstructive pulmonary disease\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e, 1\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2147/COPD.S119633\u003c/span\u003e\u003cspan address=\"10.2147/COPD.S119633\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDe Peuter, S., Van Diest, I., Lemaigre, V., Verleden, G., Demedts, M., \u0026amp; Van den Bergh, O. (2004). Dyspnea: the role of psychological processes. \u003cem\u003eClinical psychology review\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(5), 557\u0026ndash;581. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cpr.2004.05.001\u003c/span\u003e\u003cspan address=\"10.1016/j.cpr.2004.05.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ede Barbosa, S., Fernandes, J. V. N. S. F., da Silva, A. T., da Silva Leal, J. L., de Aquino Santos, L., de Souza Lima, M. L. B., J. M., \u0026amp; Leite, J. C. (2023). Effectiveness of Paced Breathing Guided by Biofeedback on Clinical and Functional Outcomes Patients with Chronic Obstructive Pulmonary Disease: An Uncontrolled Pilot Study. \u003cem\u003eApplied psychophysiology and biofeedback\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(4), 423\u0026ndash;432. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10484-023-09591-5\u003c/span\u003e\u003cspan address=\"10.1007/s10484-023-09591-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDelk, K. K., Gevirtz, R., Hicks, D. A., Carden, F., \u0026amp; Rucker, R. (1994). The effects of biofeedback assisted breathing retraining on lung functions in patients with cystic fibrosis. \u003cem\u003eChest\u003c/em\u003e, \u003cem\u003e105\u003c/em\u003e(1), 23\u0026ndash;28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1378/chest.105.1.23\u003c/span\u003e\u003cspan address=\"10.1378/chest.105.1.23\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDemeyer, H., Burtin, C., Van Remoortel, H., Hornikx, M., Langer, D., Decramer, M., Gosselink, R., Janssens, W., \u0026amp; Troosters, T. (2014). Standardizing the analysis of physical activity in patients with COPD following a pulmonary rehabilitation program. \u003cem\u003eChest\u003c/em\u003e, \u003cem\u003e146\u003c/em\u003e(2), 318\u0026ndash;327. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1378/chest.13-1968\u003c/span\u003e\u003cspan address=\"10.1378/chest.13-1968\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDodd, J. W., Getov, S. V., \u0026amp; Jones, P. W. (2010). Cognitive function in COPD. \u003cem\u003eThe European respiratory journal\u003c/em\u003e, \u003cem\u003e35\u003c/em\u003e(4), 913\u0026ndash;922. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1183/09031936.00125109\u003c/span\u003e\u003cspan address=\"10.1183/09031936.00125109\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDonner, C., Ambrosino, N., \u0026amp; Goldstein, R. S. (Eds.). (2020). \u003cem\u003ePulmonary rehabilitation\u003c/em\u003e. CRC.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEst\u0026egrave;ve, F., Blanc-Gras, N., Gallego, J., \u0026amp; Benchetrit, G. (1996). The effects of breathing pattern training on ventilatory function in patients with COPD. \u003cem\u003eBiofeedback and self-regulation\u003c/em\u003e, \u003cem\u003e21\u003c/em\u003e(4), 311\u0026ndash;321. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF02214431\u003c/span\u003e\u003cspan address=\"10.1007/BF02214431\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFourni\u0026eacute;, C., Chouchou, F., Dalleau, G., Caderby, T., Cabrera, Q., \u0026amp; Verkindt, C. (2021). Heart rate variability biofeedback in chronic disease management: A systematic review. \u003cem\u003eComplementary therapies in medicine\u003c/em\u003e, \u003cem\u003e60\u003c/em\u003e, 102750. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ctim.2021.102750\u003c/span\u003e\u003cspan address=\"10.1016/j.ctim.2021.102750\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGevirtz, R. (2013). The promise of heart rate variability biofeedback: Evidence-based application. \u003cem\u003eBiofeedback\u003c/em\u003e, \u003cem\u003e41\u003c/em\u003e(3), 110\u0026ndash;120. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5298/1081-5937-41.3.01\u003c/span\u003e\u003cspan address=\"10.5298/1081-5937-41.3.01\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGiardino, N. D., Chan, L., \u0026amp; Borson, S. (2004). Combined heart rate variability and pulse oximetry biofeedback for chronic obstructive pulmonary disease: preliminary findings. \u003cem\u003eApplied psychophysiology and biofeedback\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(2), 121\u0026ndash;133. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1023/b:apbi.0000026638.64386.89\u003c/span\u003e\u003cspan address=\"10.1023/b:apbi.0000026638.64386.89\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHolland, A. E., Spruit, M. A., Troosters, T., Puhan, M. A., Pepin, V., Saey, D., McCormack, M. C., Carlin, B. W., Sciurba, F. C., Pitta, F., Wanger, J., MacIntyre, N., Kaminsky, D. A., Culver, B. H., Revill, S. M., Hernandes, N. A., Andrianopoulos, V., Camillo, C. A., Mitchell, K. E., Lee, A. L., \u0026amp; Singh, S. J. (2014). An official European Respiratory Society/American Thoracic Society technical standard: field walking tests in chronic respiratory disease. \u003cem\u003eThe European respiratory journal\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(6), 1428\u0026ndash;1446. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1183/09031936.00150314\u003c/span\u003e\u003cspan address=\"10.1183/09031936.00150314\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIani, L., Lauriola, M., \u0026amp; Costantini, M. (2014). A confirmatory bifactor analysis of the Hospital Anxiety and Depression Scale in an Italian community sample. \u003cem\u003eHealth and quality of life outcomes\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e, 84. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1477-7525-12-84\u003c/span\u003e\u003cspan address=\"10.1186/1477-7525-12-84\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJack, S., Rossiter, H. B., Pearson, M. G., Ward, S. A., Warburton, C. J., \u0026amp; Whipp, B. J. (2004). Ventilatory responses to inhaled carbon dioxide, hypoxia, and exercise in idiopathic hyperventilation. \u003cem\u003eAmerican journal of respiratory and critical care medicine\u003c/em\u003e, \u003cem\u003e170\u003c/em\u003e(2), 118\u0026ndash;125. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1164/rccm.200207-720OC\u003c/span\u003e\u003cspan address=\"10.1164/rccm.200207-720OC\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJaeschke, R., Singer, J., \u0026amp; Guyatt, G. H. (1989). Measurement of health status. Ascertaining the minimal clinically important difference. \u003cem\u003eControlled clinical trials\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(4), 407\u0026ndash;415. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0197-2456(89)90005-6\u003c/span\u003e\u003cspan address=\"10.1016/0197-2456(89)90005-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJASP Team (2024). JASP (Version 0.19.3)[Computer software].\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJones, P. W., Harding, G., Berry, P., Wiklund, I., Chen, W. H., \u0026amp; Leidy, K., N (2009). Development and first validation of the COPD Assessment Test. \u003cem\u003eThe European respiratory journal\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(3), 648\u0026ndash;654. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1183/09031936.00102509\u003c/span\u003e\u003cspan address=\"10.1183/09031936.00102509\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJones, P. W., Quirk, F. H., Baveystock, C. M., \u0026amp; Littlejohns, P. (1992). A self-complete measure of health status for chronic airflow limitation. The St. George's Respiratory Questionnaire. \u003cem\u003eThe American review of respiratory disease\u003c/em\u003e, \u003cem\u003e145\u003c/em\u003e(6), 1321\u0026ndash;1327. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1164/ajrccm/145.6.1321\u003c/span\u003e\u003cspan address=\"10.1164/ajrccm/145.6.1321\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhazan, I. Z. (2013). \u003cem\u003eThe clinical handbook of biofeedback: A step-by-step guide for training and practice with mindfulness\u003c/em\u003e. Wiley.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee, M. D., \u0026amp; Wagenmakers, E. J. (2014). \u003cem\u003eBayesian cognitive modeling: A practical course\u003c/em\u003e. Cambridge University Press.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLehrer, P., \u0026amp; Moritz, G. (2023). Biofeedback has therapeutic effects on asthma, although additional research is needed to document specificity. \u003cem\u003ePolicy Insights from the Behavioral and Brain Sciences\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(1), 83\u0026ndash;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/23727322221145306\u003c/span\u003e\u003cspan address=\"10.1177/23727322221145306\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLehrer, P. M., Vaschillo, E., Vaschillo, B., Lu, S. E., Scardella, A., Siddique, M., \u0026amp; Habib, R. H. (2004). Biofeedback treatment for asthma. \u003cem\u003eChest\u003c/em\u003e, \u003cem\u003e126\u003c/em\u003e(2), 352\u0026ndash;361. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1378/chest.126.2.352\u003c/span\u003e\u003cspan address=\"10.1378/chest.126.2.352\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaltais, F., LeBlanc, P., Simard, C., Jobin, J., B\u0026eacute;rub\u0026eacute;, C., Bruneau, J., Carrier, L., \u0026amp; Belleau, R. (1996). Skeletal muscle adaptation to endurance training in patients with chronic obstructive pulmonary disease. \u003cem\u003eAmerican journal of respiratory and critical care medicine\u003c/em\u003e, \u003cem\u003e154\u003c/em\u003e(2 Pt 1), 442\u0026ndash;447. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1164/ajrccm.154.2.8756820\u003c/span\u003e\u003cspan address=\"10.1164/ajrccm.154.2.8756820\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaja, R., Vaiyapuri, A., Sirajudeen, M. S., Muthusamy, H., Unnikrishnan, R., Waly, M., Devaraj, S. S. D., \u0026amp; Seyam, M. K.,S, G. N (2020). Biofeedback flutter device for managing the symptoms of patients with COPD. \u003cem\u003eTechnology and health care: official journal of the European Society for Engineering and Medicine\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(5), 477\u0026ndash;485. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3233/THC-202222\u003c/span\u003e\u003cspan address=\"10.3233/THC-202222\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNorman, G. R., Sloan, J. A., \u0026amp; Wyrwich, K. W. (2003). Interpretation of changes in health-related quality of life: the remarkable universality of half a standard deviation. \u003cem\u003eMedical care\u003c/em\u003e, \u003cem\u003e41\u003c/em\u003e(5), 582\u0026ndash;592. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/01.MLR.0000062554.74615.4C\u003c/span\u003e\u003cspan address=\"10.1097/01.MLR.0000062554.74615.4C\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParshall, M. B., Schwartzstein, R. M., Adams, L., Banzett, R. B., Manning, H. L., Bourbeau, J., Calverley, P. M., Gift, A. G., Harver, A., Lareau, S. C., Mahler, D. A., Meek, P. M., O'Donnell, D. E., \u0026amp; American Thoracic Society Committee on Dyspnea. (2012). An official American Thoracic Society statement: update on the mechanisms, assessment, and management of dyspnea. \u003cem\u003eAmerican journal of respiratory and critical care medicine\u003c/em\u003e, \u003cem\u003e185\u003c/em\u003e(4), 435\u0026ndash;452. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1164/rccm.201111-2042ST\u003c/span\u003e\u003cspan address=\"10.1164/rccm.201111-2042ST\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoche, N. (2009). Activity limitation: a major consequence of dyspnoea in COPD. \u003cem\u003eEuropean respiratory review: an official journal of the European Respiratory Society\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(112), 54\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1183/09059180.00001309\u003c/span\u003e\u003cspan address=\"10.1183/09059180.00001309\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSantangelo, G., Siciliano, M., Pedone, R., Vitale, C., Falco, F., Bisogno, R., Siano, P., Barone, P., Grossi, D., Santangelo, F., \u0026amp; Trojano, L. (2015). Normative data for the Montreal Cognitive Assessment in an Italian population sample. \u003cem\u003eNeurological sciences: official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology\u003c/em\u003e, \u003cem\u003e36\u003c/em\u003e(4), 585\u0026ndash;591. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10072-014-1995-y\u003c/span\u003e\u003cspan address=\"10.1007/s10072-014-1995-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchwartz, M. S., \u0026amp; Andrasik, F. (Eds.). (2017). \u003cem\u003eBiofeedback: A practitioner's guide\u003c/em\u003e. Guilford.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSpruit, M. A., Singh, S. J., Garvey, C., ZuWallack, R., Nici, L., Rochester, C., Hill, K., Holland, A. E., Lareau, S. C., Man, W. D., Pitta, F., Sewell, L., Raskin, J., Bourbeau, J., Crouch, R., Franssen, F. M., Casaburi, R., Vercoulen, J. H., Vogiatzis, I., \u0026amp; Gosselink, R. (2013). Society statement: key concepts and advances in pulmonary rehabilitation. \u003cem\u003eAmerican journal of respiratory and critical care medicine\u003c/em\u003e, \u003cem\u003e188\u003c/em\u003e(8), e13\u0026ndash;e64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1164/rccm.201309-1634ST\u003c/span\u003e\u003cspan address=\"10.1164/rccm.201309-1634ST\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. ATS/ERS Task Force on Pulmonary RehabilitationAn official American Thoracic Society/European Respiratory.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTeeter, J. G., \u0026amp; Bleecker, E. R. (1998). Relationship between airway obstruction and respiratory symptoms in adult asthmatics. \u003cem\u003eChest\u003c/em\u003e, \u003cem\u003e113\u003c/em\u003e(2), 272\u0026ndash;277. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1378/chest.113.2.272\u003c/span\u003e\u003cspan address=\"10.1378/chest.113.2.272\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUrbaniak, G. C., \u0026amp; Plous, S. (2023). \u003cem\u003eResearch randomizer (version 4.0)[computer software]\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003evan Gestel, A. J., Kohler, M., Steier, J., Teschler, S., Russi, E. W., \u0026amp; Teschler, H. (2012). The effects of controlled breathing during pulmonary rehabilitation in patients with COPD. \u003cem\u003eRespiration; international review of thoracic diseases\u003c/em\u003e, \u003cem\u003e83\u003c/em\u003e(2), 115\u0026ndash;124. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1159/000324449\u003c/span\u003e\u003cspan address=\"10.1159/000324449\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVitacca, M., Paneroni, M., Baiardi, P., De Carolis, V., Zampogna, E., Belli, S., Carone, M., Spanevello, A., Balbi, B., \u0026amp; Bertolotti, G. (2016). Development of a Barthel Index based on dyspnea for patients with respiratory diseases. \u003cem\u003eInternational journal of chronic obstructive pulmonary disease\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e, 1199\u0026ndash;1206. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2147/COPD.S104376\u003c/span\u003e\u003cspan address=\"10.2147/COPD.S104376\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu, D. W., Yang, P. C., \u0026amp; Lin, I. M. (2024). Effects of heart rate variability (HRV) biofeedback in pulmonary indicators and HRV indices among patients with chronic obstructive pulmonary disease. \u003cem\u003eApplied Psychophysiology and Biofeedback\u003c/em\u003e, 1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYucha, C., \u0026amp; Montgomery, D. (2008). \u003cem\u003eEvidence-based practice in biofeedback and neurofeedback\u003c/em\u003e. AAPB.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"COPD, biofeedback, dyspnea, pulmonary rehabilitation, cognition, depression, quality of life","lastPublishedDoi":"10.21203/rs.3.rs-6974767/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6974767/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eChronic obstructive pulmonary disease (COPD) is associated with persistent dyspnea, reduced functional capacity, and significant cognitive and affective impairments. Pulmonary rehabilitation improves the physical and psychological condition , however residual symptoms often remain, especially in patients with advanced disease. Respiratory biofeedback training (RBT) may help modulate autonomic and emotional responses to dyspnea, offering a potential adjunctive intervention.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis pilot study investigated the effects of RBT integrated into a standard program of pulmonary rehabilitation for hospitalized patients with very severe COPD (GOLD stage 4 and an mMRC dyspnea score of ≥3 despite maximal pharmacological therapy). Thirty patients were randomized to receive either standard pulmonary rehabilitation alone (control group) or in combination with daily RBT sessions for three weeks (biofeedback group). Pre- and post-treatment assessments included measures of dyspnea, functional performance, quality of life, cognitive function and mood. Data were analyzed using Bayesian repeated-measures ANOVA, and results were normalized using Minimal Clinically Important Differences (MCIDs).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eBoth groups showed significant improvements in respiratory and functional outcomes (e.g., mMRC, 6MWT), with no group differences. However, the biofeedback group demonstrated greater improvements in cognitive performance (MoCA) and depressive symptoms (HADS-D).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eWhile RBT did not enhance dyspnea or physical performance in patients receiving inpatient pulmonary rehabilitation, it was associated with significant gains in cognitive and emotional outcomes. These findings suggest that RBT may serve as a valuable neuropsychological adjunct in the management of late-stage COPD.\u003c/p\u003e","manuscriptTitle":"Respiratory Biofeedback Training as an Adjunct Intervention in Pulmonary Rehabilitation for Late-Stage COPD: A Pilot Trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-18 12:44:28","doi":"10.21203/rs.3.rs-6974767/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-14T21:59:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-12T17:00:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201517447164659571576884477552131015116","date":"2025-07-16T02:36:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-11T16:20:12+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-25T17:12:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-25T17:12:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Applied Psychophysiology and Biofeedback","date":"2025-06-25T12:31:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"58ca637f-e6a8-4bd1-908b-73f42d6b6c9a","owner":[],"postedDate":"July 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-19T16:48:20+00:00","versionOfRecord":{"articleIdentity":"rs-6974767","link":"https://doi.org/10.1007/s10484-025-09763-5","journal":{"identity":"applied-psychophysiology-and-biofeedback","isVorOnly":false,"title":"Applied Psychophysiology and Biofeedback"},"publishedOn":"2026-01-14 16:29:59","publishedOnDateReadable":"January 14th, 2026"},"versionCreatedAt":"2025-07-18 12:44:28","video":"","vorDoi":"10.1007/s10484-025-09763-5","vorDoiUrl":"https://doi.org/10.1007/s10484-025-09763-5","workflowStages":[]},"version":"v1","identity":"rs-6974767","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6974767","identity":"rs-6974767","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}