Automated Systems Based on Wearable Sensors for the Management of Parkinson's Disease at Home: A Systematic Review.

Automated Systems Based on Wearable Sensors for the Management of Parkinson's Disease at Home: A Systematic Review.

Automated Systems Based on Wearable Sensors for the Management of Parkinson's Disease at Home: A Systematic Review.

Telemed J E Health. 2018 Jul 03;:

Authors: Rovini E, Maremmani C, Cavallo F

Abstract
BACKGROUND: Parkinson's disease is a common neurodegenerative pathology that significantly influences quality of life (QoL) of people affected. The increasing interest and development in telemedicine services and internet of things technologies aim to implement automated smart systems for remote assistance of patients. The wide variability of Parkinson's disease in the clinical expression, as well as in the symptom progression, seems to address the patients' care toward a personalized therapy.
OBJECTIVES: This review addresses automated systems based on wearable/portable devices for the remote treatment and management of Parkinson's disease. The idea is to obtain an overview of the telehealth and automated systems currently developed to address the impairments due to the pathology to allow clinicians to improve the quality of care for Parkinson's disease with benefits for patients in QoL.
DATA SOURCES: The research was conducted within three databases: IEEE Xplore®, Web of Science®, and PubMed Central®, between January 2008 and September 2017.
STUDY ELIGIBILITY CRITERIA: Accurate exclusion criteria and selection strategy were applied to screen the 173 articles found.
RESULTS: Ultimately, 55 articles were fully evaluated and included in this review. Divided into three categories, they were automated systems actually tested at home, implemented mobile applications for Parkinson's disease assessment, or described a telehealth system architecture.
CONCLUSION: This review would provide an exhaustive overview of wearable systems for the remote management and automated assessment of Parkinson's disease, taking into account the reliability and acceptability of the implemented technologies.

PMID: 29969384 [PubMed - as supplied by publisher]