Signal features of surface electromyography in advanced Parkinson’s disease during different settings of deep brain stimulation

• Efficacy of deep brain stimulation (DBS) treatment was quantified here by using surface EMG and acceleration measurements.
• EMG signal features differed between different DBS settings for biceps brachii muscles.
• EMG features pointed to previously defined optimal settings in most of patients.

ObjectiveElectromyography (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.MethodsEMGs 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.ResultsThe 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.ConclusionsSurface EMG features differed between different DBS settings and DBS effect was unequal between upper and lower limb muscles.SignificanceEMG changes pointed to previously defined optimal settings in most of patients, which should be quantified even more deeply in the upcoming studies.