SYNCHRONIZATION OF PHYSIOLOGICAL SIGNALS COLLECTED OVER TWO RESEARCH GRADE SOURCES

This is a preprint and has not been peer reviewed. Data may be preliminary. SYNCHRONIZATION OF PHYSIOLOGICAL SIGNALS COLLECTED OVER TWO RESEARCH GRADE SOURCES Abstract Wearable devices enable continuous monitoring of physiological signals in real‐world settings, but their interoperability across platforms remains understudied. In this work, we compared signal‐level agreement in terms of waveform similarity, amplitude distribution, spectral content, and extracted features, between the 2 research‐grade devices, Empatica E4 and EmbracePlus, to determine their interchangeability for longitudinal and multi‐site studies. Specifically, we aimed to determine how well these devices agree at the signal level and to identify which physiological signals are most robust to device‐specific variability. We collected up to 48 hours of concurrent recordings from 31 participants wearing both devices on their non‐dominant wrist. Raw signals (Blood Volume Pulse (BVP), Electrodermal activity (EDA), Accelerometer (ACC), Temperature (TEMP)) were resampled, aligned by dynamic time warping, amplitude‐corrected via wavelet transforms, and standardized. We computed Pearson and concordance correlation coefficients, Bland–Altman bias and limits of agreement, root mean squared error (RMSE), KL divergence, spectral coherence, mutual information, and feature‐level correlations using NeuroKit2 and FLIRT. Results showed near‐perfect agreement for BVP (Concordance Correlation Coefficient (CCC) ≈1.0; coherence ≤ 0.98) and phasic EDA features (CCC 0.85–0.99), whereas tonic EDA, temperature, and accelerometry exhibited systematic amplitude biases (EmbracePlus lower) and axis‐dependent variability (Z‐axis CCC = 0.85; Y‐axis = 0.19). Relative signal dynamics were preserved across devices despite absolute differences. These findings support integration of BVP, EDA, TEMP data across E4 and EmbracePlus with proper preprocessing, while highlighting calibration needs for movement signals. Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Metrics & Citations Metrics Article Usage 327views 85downloads Citations Download citation Selin Acan, Clàudia Valenzuela‐Pascual †, Filippo Corponi, et al. SYNCHRONIZATION OF PHYSIOLOGICAL SIGNALS COLLECTED OVER TWO RESEARCH GRADE SOURCES. Authorea. 21 August 2025. DOI: https://doi.org/10.22541/au.175578507.72833619/v1 DOI: https://doi.org/10.22541/au.175578507.72833619/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.