Literature DB >> 29969384

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

Erika Rovini1, Carlo Maremmani2, Filippo Cavallo1.   

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.

Entities:  

Mesh:

Year:  2018        PMID: 29969384     DOI: 10.1089/tmj.2018.0035

Source DB:  PubMed          Journal:  Telemed J E Health        ISSN: 1530-5627            Impact factor:   3.536


  9 in total

Review 1.  Closing the loop for patients with Parkinson disease: where are we?

Authors:  Hazhir Teymourian; Farshad Tehrani; Katherine Longardner; Kuldeep Mahato; Tatiana Podhajny; Jong-Min Moon; Yugender Goud Kotagiri; Juliane R Sempionatto; Irene Litvan; Joseph Wang
Journal:  Nat Rev Neurol       Date:  2022-06-09       Impact factor: 44.711

2.  Impaired Touchscreen Skills in Parkinson's Disease and Effects of Medication.

Authors:  Joni De Vleeschhauwer; Sanne Broeder; Luc Janssens; Elke Heremans; Alice Nieuwboer; Evelien Nackaerts
Journal:  Mov Disord Clin Pract       Date:  2021-03-12

3.  Objective and automatic classification of Parkinson disease with Leap Motion controller.

Authors:  A H Butt; E Rovini; C Dolciotti; G De Petris; P Bongioanni; M C Carboncini; F Cavallo
Journal:  Biomed Eng Online       Date:  2018-11-12       Impact factor: 2.819

4.  A Multi-Sensor Wearable System for the Quantitative Assessment of Parkinson's Disease.

Authors:  Han Zhang; Chuantao Li; Wei Liu; Jingying Wang; Junhong Zhou; Shouyan Wang
Journal:  Sensors (Basel)       Date:  2020-10-29       Impact factor: 3.576

5.  Wearable Health Technology to Quantify the Functional Impact of Peripheral Neuropathy on Mobility in Parkinson's Disease: A Systematic Review.

Authors:  Marta Francisca Corrà; Elke Warmerdam; Nuno Vila-Chã; Walter Maetzler; Luís Maia
Journal:  Sensors (Basel)       Date:  2020-11-19       Impact factor: 3.576

6.  Continuous home monitoring of Parkinson's disease using inertial sensors: A systematic review.

Authors:  Marco Sica; Salvatore Tedesco; Colum Crowe; Lorna Kenny; Kevin Moore; Suzanne Timmons; John Barton; Brendan O'Flynn; Dimitrios-Sokratis Komaris
Journal:  PLoS One       Date:  2021-02-04       Impact factor: 3.240

7.  Toward Improved Treatment and Empowerment of Individuals With Parkinson Disease: Design and Evaluation of an Internet of Things System.

Authors:  Liran Karni; Ilir Jusufi; Dag Nyholm; Gunnar Oskar Klein; Mevludin Memedi
Journal:  JMIR Form Res       Date:  2022-06-09

Review 8.  A Review of Converging Technologies in eHealth Pertaining to Artificial Intelligence.

Authors:  Iuliu Alexandru Pap; Stefan Oniga
Journal:  Int J Environ Res Public Health       Date:  2022-09-10       Impact factor: 4.614

9.  How People with Parkinson's Disease and Health Care Professionals Wish to Partner in Care Using eHealth: Co-Design Study.

Authors:  Carolina Wannheden; Åsa Revenäs
Journal:  J Med Internet Res       Date:  2020-09-21       Impact factor: 5.428

  9 in total

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