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Updated: Apr 16, 2026
Controlling Parkinson's Disease With Adaptive Deep Brain Stimulation
Published on: July 16, 2014
Signal features of surface electromyography in advanced Parkinson's disease during different settings of deep brain
Saara M Rissanen1, Verneri Ruonala1, Eero Pekkonen2
1Department of Applied Physics, University of Eastern Finland, Finland.
Objective:
Electromyography (EMG) and acceleration (ACC) measurements are potential methods for quantifying efficacy of deep brain stimulation (DBS) treatment in Parkinson's disease (PD). The treatment efficacy depends on the settings of DBS parameters (pulse amplitude, frequency and width). This study quantified, if EMG and ACC signal features differ between different DBS settings and if DBS effect is unequal between different muscles.
Methods:
EMGs were measured from biceps brachii (BB) and tibialis anterior (TA) muscles of 13 PD patients. ACCs were measured from wrists. Measurements were performed during seven different settings of DBS and analyzed using methods based on spectral analysis, signal morphology and nonlinear dynamics.
Results:
The results showed significant within-subject differences in the EMG signal kurtosis, correlation dimension, recurrence rate and EMG-ACC coherence between different DBS settings for BB but not for TA muscles. Correlations between EMG feature values and clinical rest tremor and rigidity scores were weak but significant.
Conclusions:
Surface EMG features differed between different DBS settings and DBS effect was unequal between upper and lower limb muscles.
Significance:
EMG changes pointed to previously defined optimal settings in most of patients, which should be quantified even more deeply in the upcoming studies.
