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

摘要

The future of telecommunications is premised on high fidelity networks with extreme precision, which in turn capacitates deployment of telediagnostic 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 up to 5 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 the diagnostic process.