Journal article

Signal quality and patient experience with wearable devices for epilepsy management

Mona Nasseri, Ewan Nurse, Martin Glasstetter, Sebastian Boettcher, Nicholas M Gregg, Aiswarya Laks Nandakumar, Boney Joseph, Tal Pal Attia, Pedro F Viana, Elisa Bruno, Andrea Biondi, Mark Cook, Gregory A Worrell, Andreas Schulze-Bonhage, Matthias Duempelmann, Dean R Freestone, Mark P Richardson, Benjamin H Brinkmann

Epilepsia | WILEY | Published : 2020

Abstract

Noninvasive wearable devices have great potential to aid the management of epilepsy, but these devices must have robust signal quality, and patients must be willing to wear them for long periods of time. Automated machine learning classification of wearable biosensor signals requires quantitative measures of signal quality to automatically reject poor-quality or corrupt data segments. In this study, commercially available wearable sensors were placed on patients with epilepsy undergoing in-hospital or in-home electroencephalographic (EEG) monitoring, and healthy volunteers. Empatica E4 and Biovotion Everion were used to record accelerometry (ACC), photoplethysmography (PPG), and electroderma..

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Grants

Funding Acknowledgements

This work was funded by the My Seizure Gauge grant provided by the Epilepsy Innovation Institute, a research program of the The Epilepsy Foundation of America's Epilepsy Innovation Institute My Seizure Gauge project. The authors thank Sherry Klingerman, Dan Crepeau, Dominique Eden, William Hart, and Shannon McCollough for technical assistance and coordination.