News.Health.004 Parkinson's Telemonitoring

Context

Introduction

Parkinson’s disease management faces challenges due to the need for frequent clinical assessments, especially for patients with mobility issues or living remotely. Leeds Teaching Hospitals has introduced a smartphone app to facilitate remote symptom tracking and improve patient care. The learner will work with a telemonitoring dataset containing speech recordings and clinical scores from Parkinson’s patients to explore remote symptom monitoring.

Role

The learner acts as a Healthcare Data Scientist embedded within the hospital’s digital health team. Their responsibility is to develop and validate predictive models that translate voice data into reliable symptom severity indicators. They must address challenges including variability in patient speech, real-world noise, and integration of outputs into clinical workflows to enhance patient monitoring.

Business Objectives

The task is to build a remote monitoring system using speech data to support clinicians in tracking Parkinson’s disease progression without frequent in-person visits.

Products

The key deliverable is a voice-based symptom monitoring tool that automatically analyzes patient speech recordings and generates symptom severity scores.

Codebook

subject, age, sex, test\_time, motor\_updrs, total\_updrs, jitter, jitter\_abs, jitter\_rap, jitter\_ppq5, jitter\_ddp, shimmer, shimmer\_db, shimmer\_apq3, shimmer\_apq5, shimmer\_apq11, shimmer\_dda, nhr, hnr, rpde, dfa, ppe