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Parkinson's disease (PD) is a gradual progressive central neurodegenerative disorder that affects body movement and is characterized by symptoms such as muscle rigidity, resting tremors, loss of facial expression, hypophonia, diminished blinking, and akinesia . This work aims at providing new insights on the Parkinson's disease fragmentation problem using wavelets [1, 2, 3]. The present work describes a computer model to provide a more accurate picture of the Parkinson's disease (PD) signaldoi:10.47893/ijess.2011.1006 fatcat:rtd3dw7a5jab7ghcu3vusi4lai