MonParLoc: A Speech-Based System for Parkinson’s Disease Analysis and Monitoring

Patients suffering from Parkinson's Disease (PD) manifest relevant changes in their speech, consisting of specific landmarks in articulation, phonation, fluency, and prosody. Usually, phonation and articulation changes are estimated and evaluated using different methods and statistical frameworks. Speech is especially relevant as a vehicular mechanism to monitor neurological evolution using well-known features extracted from sustained phonations (mainly vowels), diadochokinetic exercises, or running speech. Recent studies have shown that acoustic neurostimulation using binaural beats influences the cognitive and neuromotor conditions of patients with PD, at least temporarily after stimulation. The aim of this study is to describe an added-value solution considering the cooperation of both previously mentioned methods: speech analysis-based monitoring called within the project, Monitoring Parkinson using Locution (MonParLoc), and acoustical neurostimulation, called within project neuro-Acoustic-stimulation Parkinson (AcousticPar). The applications designed in both projects are embedded into a global solution denominated Teca-Park which consists of four main activities: speech evaluation, neurostimulation, motor symptom longitudinally, and questionnaires. This framework is conceived to be a powerful tool for treating and monitoring longitudinally remotely and contact-free. MonParLoc was tested and validated in real scenarios involving patient associations. Validation results produced in these associations demonstrating the utility of this approach are given in the study, particularly in reference to protocol vulnerability and robustness. This paper proposes a complete framework (a mobile app and a scorecard solution) including different services for Parkinson's clinical monitoring and patient management using speech, movement, and acoustic stimulation.