Diagnosis of Parkinson's Disease by Electrophysiological Methods

Abstract

INTRO....Effective differential diagnosis of Parkinson’s disease (PD) needs in informative indices that objectively reflect the functional state of the extrapyramidal system. And also, when evaluating an efficacy of antiparkinsonian therapy, it is essential to have both, qualitative and quantitative characteristics, permitting to correct treatment and predict a disease course. One of informative diagnostic method in PD is surface (interference) electromyography. As know, a nigrostriatal dopamine deficit results in disturbances of the central supraspinal control over the muscle tonic activity and voluntary movements (Valls-Solé & Valldeoriola, 2002). Electromyographically, the extrapyradimal insufficiency shows itself by a high level of bioelectrical activity of muscles at rest, changes of motor unit conduction velocity and synchronization (Farina et al., 2004; Semmler & Nordstrom, 1999). The traditional methods to evaluate surface electromyograms (EMGs) are based on amplitude and spectral analysis. However, myoelectric signals are nonlinear by its nature (Nieminen & Takala, 1996). A surface EMG is formed by the summation of a number of single muscle fiber action potentials. Therefore different world clinics have been searching for new relevant methods based on nonlinear time-series analyses of EMG to quantify the motor features of the disorder in PD (Del Santo et al., 2007; Meigal et al., 2009). Some other novel EMG characteristics, such as dimensionality based on fractal analysis or higher order statistics of EMG distribution have also proved to be sensitive to neuromuscular status (Swie et al., 2005)