Analysis of Jitter and Shimmer for Parkinson’s Disease Diagnosis Using Telehealth

Abstract

The future of telecommunications is premised on high fidelity net-works with extreme precision, which in turn capacitates deployment of tele-diagnostic tools. Parkinson’s disease (PD) clinical characterization is based on, speech problems, tremors in hands, arms, legs and face, body swelling, muscle rigidity and movement problems. Speech problems are cited as one of the earliest prodromal for PD. However, using clinical diagnosis it takes upto five or more years to detect PD. Therefore with this regard speech can be used as an early biomarker for PD. Features of interest for detecting PD will be prosodic, spectral, vocal tract and excitation source speech features. We infer from the analysis, MFFC with jitter and shimmer feature extraction provides a promising method that can help the clinicians in diagnostic process.