An intelligent E-skin with spatiotemporal vibrotactile cues enable personalized gait rehabilitation in Parkinson's disease

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Abstract Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, severely impairs gait and mobility. Pharmacologic and surgical therapies have important limitations, and existing wearable cueing devices remain clunky and poorly adaptive. To address this, we developed a novel flexible patch characterized by ultra-miniaturization and superior adaptability (FlexAdapt Patch) for gait rehabilitation in people with PD. The FlexAdapt Patch integrates a single IMU with Gait-Phase-Adaptive (GPA) algorithm and a continuously updated, personalized gait-processing strategy, delivering pre-emptive, leg-lifting vibrotactile cues. Across walking speeds, the algorithm achieved 97.79% agreement with optical motion capture as the gold standard. In a cohort of 35 PD patients, spatiotemporal vibration outperformed no stimulation and constant vibration, reducing the variance of stride length, gait-cycle duration, and support-phase ratio by 49.1–61.1%, decreasing discrepancies in hip and knee angle trajectories relative to normative curves by 38.8% and 38.2%, and lowering fatigue in four lower-limb muscles by 16.9–30.2%. In summary, the FlexAdapt Patch enables routine, home-based, personalized gait rehabilitation for PD.
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An intelligent E-skin with spatiotemporal vibrotactile cues enable personalized gait rehabilitation in Parkinson's disease | 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 Article An intelligent E-skin with spatiotemporal vibrotactile cues enable personalized gait rehabilitation in Parkinson's disease Fuhao MO, Tiefeng Cheng, Ying Kong, Ke Wu, Ziyang Liang, Bo Yang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8883462/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, severely impairs gait and mobility. Pharmacologic and surgical therapies have important limitations, and existing wearable cueing devices remain clunky and poorly adaptive. To address this, we developed a novel flexible patch characterized by ultra-miniaturization and superior adaptability (FlexAdapt Patch) for gait rehabilitation in people with PD. The FlexAdapt Patch integrates a single IMU with Gait-Phase-Adaptive (GPA) algorithm and a continuously updated, personalized gait-processing strategy, delivering pre-emptive, leg-lifting vibrotactile cues. Across walking speeds, the algorithm achieved 97.79% agreement with optical motion capture as the gold standard. In a cohort of 35 PD patients, spatiotemporal vibration outperformed no stimulation and constant vibration, reducing the variance of stride length, gait-cycle duration, and support-phase ratio by 49.1–61.1%, decreasing discrepancies in hip and knee angle trajectories relative to normative curves by 38.8% and 38.2%, and lowering fatigue in four lower-limb muscles by 16.9–30.2%. In summary, the FlexAdapt Patch enables routine, home-based, personalized gait rehabilitation for PD. Physical sciences/Engineering/Biomedical engineering Health sciences/Diseases/Neurological disorders/Parkinson's disease Physical sciences/Engineering/Mechanical engineering Health sciences/Health care/Geriatrics Physical sciences/Mathematics and computing/Computational science FlexAdapt Patch Parkinson's disease spatiotemporal vibrotactile cues algorithm gait parameters Full Text Additional Declarations There is NO Competing Interest. Supplementary Files PD35musclefatiguesummary.xlsx PD35_muscle_fatigue_summary PD35gaitstridedurationsupportsummary.xlsx PD35_gait_stride_duration_support_summary SupplementaryInformation.docx Supplementary Information PD35anglehipkneesummary.xlsx PD35_angle_hip_knee_summary VS2.Patientswalkingwithvibrationstimulator.mp4 Video S2. Patients walking with vibration stimulator VS1.Patientswalkingwithoutvibrationstimulator.mp4 Video S1. Patients walking without vibration stimulator Cite Share Download PDF Status: Under Review Version 1 posted 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-8883462","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":592800893,"identity":"928a314e-b3e1-4a72-bf49-99e7ba7ef3d6","order_by":0,"name":"Fuhao 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