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MHealth Technologies towards Parkinson's Disease Detection and Monitoring in Daily Life: A Comprehensive Review

  • Hanbin Zhang
  • , Chen Song
  • , Aditya Singh Rathore
  • , Ming Chun Huang
  • , Yuan Zhang
  • , Wenyao Xu
  • SUNY Buffalo
  • Case Western Reserve University
  • Southwest University

Research output: Contribution to journalReview articlepeer-review

47 Scopus citations

Abstract

Parkinson's disease (PD) can gradually affect people's lives thus attracting tremendous attention. Early PD detection and treatment can help control the disease progress, relief from the symptoms and improve the patients' life quality. However, the current practice of PD diagnosis is conducted in a clinical setup and administrated by a PD specialist due to the early signs of PD are not noticeable in daily life. According to the report of CDC/NIH, the diagnosed time of PD ranges from 2-10 years after onset. Therefore, a more accessible PD diagnosis approach is urgently demanded. In recent years, mobile health (for short mHealth) technology has been intensively investigated for preventive medicine, particularly in chronic disease management. Notably, many types of research have explored the possibility of using mobile and wearable personal devices to detect the symptom of PD and shown promising results. It provides opportunities for transforming early PD detection from clinical to daily life. This survey paper attempts to conduct a comprehensive review of mHealth technologies for PD detection from 2000 to 2019, and compares their pros and cons in practical applications and provides insights to close the performance gap between state-of-the-art clinical approaches and mHealth technologies.

Original languageEnglish
Article number9084244
Pages (from-to)71-81
Number of pages11
JournalIEEE Reviews in Biomedical Engineering
Volume14
DOIs
StatePublished - 2021

Keywords

  • body sensor networks
  • Mobile computing
  • public healthcare

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