Detecting negative myoclonus during long-term home measurements using wearables

Aku Sinokki; Laura Säisänen; Jelena Hyppönen; Katri Silvennoinen; Reetta Kälviäinen; Esa Mervaala; Pasi A Karjalainen; Saara M Rissanen

doi:10.1016/j.clinph.2023.10.005

Detecting negative myoclonus during long-term home measurements using wearables

Clin Neurophysiol. 2023 Dec:156:166-174. doi: 10.1016/j.clinph.2023.10.005. Epub 2023 Oct 26.

Authors

Aku Sinokki¹, Laura Säisänen², Jelena Hyppönen³, Katri Silvennoinen⁴, Reetta Kälviäinen⁵, Esa Mervaala³, Pasi A Karjalainen⁶, Saara M Rissanen⁷

Affiliations

¹ Department of Technical Physics, University of Eastern Finland, Kuopio, Finland. Electronic address: aku.sinokki@uef.fi.
² Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Kuopio Epilepsy Center, Department of Clinical Neurophysiology, Kuopio University Hospital, Full Member of ERN EpiCARE, Kuopio, Finland.
³ Kuopio Epilepsy Center, Department of Clinical Neurophysiology, Kuopio University Hospital, Full Member of ERN EpiCARE, Kuopio, Finland; Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.
⁴ Kuopio Epilepsy Center, Neurocenter, Kuopio University Hospital, Full Member of ERN EpiCARE, Kuopio, Finland; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.
⁵ Institute of Clinical Medicine, School of Medicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland; Kuopio Epilepsy Center, Neurocenter, Kuopio University Hospital, Full Member of ERN EpiCARE, Kuopio, Finland.
⁶ Department of Technical Physics, University of Eastern Finland, Kuopio, Finland.
⁷ Department of Technical Physics, University of Eastern Finland, Kuopio, Finland; Adamant Health Ltd, Kuopio, Finland.

PMID: 37952446
DOI: 10.1016/j.clinph.2023.10.005

Abstract

Objective: The aim of this study was to develop a feasible method for the detection of negative myoclonus (NM) through long-term home measurements in patients with progressive myoclonus epilepsy type 1.

Methods: The number and duration of silent periods (SP) associated with NM were detected during a 48 h home recording using wearable surface electromyography (EMG) sensors.

Results: A newly developed algorithm was able to find short (50-69 ms), intermediate (70-100 ms), and long (101- 500 ms) SPs from EMG data. Negative myoclonus assessed by the algorithm correlated significantly with the video-recorded and physician-evaluated unified myoclonus rating scale (UMRS) scores of NM and action myoclonus. Silent period duration, number, and their combination, correlated strongly and significantly also with the Singer score, which assesses functional status and ambulation.

Conclusions: Negative myoclonus can be determined objectively using long-term EMG measurements in home environment. With long-term measurements, we can acquire more reliable quantified information about NM as a symptom, compared to short evaluation at the clinic.

Significance: As measured using SPs, NM may be a clinically useful measure for monitoring disease progression or assessing antimyoclonic drug effects objectively.

Keywords: EPM1; Home monitoring; Progressive myoclonus epilepsy type 1; Silent period; Surface electromyography (EMG); Unverricht-Lundborg disease.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Electromyography
Humans
Myoclonus* / diagnosis
Unverricht-Lundborg Syndrome*
Wearable Electronic Devices*