Detecting negative myoclonus during long-term home measurements using wearables

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.

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.

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.

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.

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