In this paper, we apply novel techniques for characterizing leg muscle activation patterns via electromyograms (EMGs) and for relating them to changes in electroencephalogram (EEG) activity during gait experiments. Specifically, we investigate changes of leg-muscle EMG amplitudes and EMG frequencies during walking, intentional stops, and unintended freezing-of-gait (FOG) episodes. FOG is a frequent paroxysmal gait disturbance occurring in many patients suffering from Parkinson's disease (PD). We find that EMG amplitudes and frequencies do not change significantly during FOG episodes with respect to walking, while drastic changes occur during intentional stops. Phase synchronization between EMG signals is most pronounced during walking in controls and reduced in PD patients. By analyzing cross-correlations between changes in EMG patterns and brain-wave amplitudes (from EEGs), we find an increase in EEG-EMG coupling at the beginning of stop and FOG episodes. Our results may help to better understand the enigmatic pathophysiology of FOG, to differentiate between FOG events and other gait disturbances, and ultimately to improve diagnostic procedures for patients suffering from PD.
|Journal||Frontiers in Physiology|
|State||Published - 2019|
Bibliographical noteFunding Information:
This study was supported in part by the Israel Science Foundation (ISF) grant # 1657-16, the Israeli Ministry of Health grant # 3000-14527, and the German Israel Foundation (GIF) grant # I-1298-415.13/2015 and grant # I-1372-303.7/2016.
Copyright © 2019 Günther, Bartsch, Miron-Shahar, Hassin-Baer, Inzelberg, Kurths, Plotnik and Kantelhardt.
- Freezing of gait
- Non-linear coupling
- Parkinson's disease
- Phase synchronization
- Time series analysis