Comparison of wearable and clinical devices for acquisition of peripheral nervous system signals

Abstract

A key access point to the functioning of the Autonomic Nervous System is the investigation of peripheral signals. Wearable Devices (WDs) enable the acquisition and quantification of peripheral signals in a wide range of contexts, from personal uses to scientific research. WDs have lower costs and higher portability than medical-grade devices. But achievable data quality can be lower, subject to artifacts due to body movements and data losses. It is therefore crucial to evaluate the reliability and validity of WDs before their use in research. In this study we introduce methods and scientific software for the assessment of WDs for multivariate physiological signals. The quality of cardiac and Electrodermal Activity signals is validated with a standard set of Signal Quality Indicators, available as open source in the pyphysio Python package. We apply the indicators for the analysis of signal quality on data simultaneously recorded from a clinical-grade device and two WDs. The dataset provides signals of 6 different physiological measures collected from 18 subjects with WDs. This study indicates the need of validating the use of WD in experimental settings for research and the importance of both technological and signal processing aspects to obtain reliable signals and reproducibility of results.

Acquisition and Processing of Brain Signals

“…Specifically, this use case focused on identifying the influence of intra-operative events on cardiovascular and prefrontal cortex changes. Bizzego and colleagues [ 21 ] presented a framework for the validation of devices for physiological signal acquisition for research purposes. In particular, the study dealt with the issue of assessing the replicability of physiological measures, when computed on lower quality data from wearable devices.…”