Literature DB >> 18328028

Telemonitoring and telerehabilitation of patients with Parkinson's disease: health technology assessment of a novel wearable step counter.

Daniele Giansanti1, Velio Macellari, Giovanni Maccioni.   

Abstract

Step counting is an important index of motion in telemonitoring. One of the most diffused wearable systems, designed for this purpose, is the pedometer. The accuracy of commercial pedometers has been reported in the literature. Several limits have been found in many commercial systems both in healthy subjects and in people with disabilities. Furthermore, commercial pedometers lack interoperability. This paper introduces a new wearable system for step counting for telemonitoring applications. This system is based on a wearable device with a force-sensing resistor. It is affixed on the gastrocnemius muscle for monitoring muscular expansion correlated with the gait. The data exchange is assured by the XTR-434H (Aurel, FC, Italy) telemetric system. The proposed gastrocnemius expansion measurement unit (GEMU) was tested on 5 subjects with Parkinsons disease at Level 3 of the Tinetti test of unbalance. Ten repetitions of 500 steps with three different speeds (fast, slow, and normal) were performed. The mean error was <0.5%. Results also showed that GEMU performed better than an accelerometer unit (considered in the literature the best solution for this disability). The study showed that GEMU had a high performance in subjects with Parkinsons disease, causing a high degree of unbalance that confounded motion style. The next phase will be the optimization of GEMU for long-term medical applications at the patients home.

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Year:  2008        PMID: 18328028     DOI: 10.1089/tmj.2007.0019

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


  8 in total

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Journal:  Cochrane Database Syst Rev       Date:  2015-04-09

2.  A Survey on Ambient Intelligence in Health Care.

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Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2013-12-01       Impact factor: 10.961

3.  Willingness of Parkinson's disease patients to participate in research using internet-based technology.

Authors:  David Shprecher; Katia Noyes; Kevin Biglan; Dongwen Wang; E Ray Dorsey; Roger Kurlan; Michael Jacob Adams
Journal:  Telemed J E Health       Date:  2012-09-06       Impact factor: 3.536

4.  The mHealth in the canine assisted therapy: the proposal of a conceptual model for the wearable monitoring.

Authors:  Daniele Giansanti; Giovanni Maccioni
Journal:  Mhealth       Date:  2019-12-02

5.  The mHealth in the canine assisted therapy: the design and application of a kit for the wearable monitoring during a walking session.

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Journal:  Mhealth       Date:  2020-04-05

6.  The Role of Engagement in Teleneurorehabilitation: A Systematic Review.

Authors:  Marta Matamala-Gomez; Marta Maisto; Jessica Isbely Montana; Petar Aleksandrov Mavrodiev; Francesca Baglio; Federica Rossetto; Fabrizia Mantovani; Giuseppe Riva; Olivia Realdon
Journal:  Front Neurol       Date:  2020-05-06       Impact factor: 4.003

Review 7.  Co-evolution of machine learning and digital technologies to improve monitoring of Parkinson's disease motor symptoms.

Authors:  Anirudha S Chandrabhatla; I Jonathan Pomeraniec; Alexander Ksendzovsky
Journal:  NPJ Digit Med       Date:  2022-03-18

8.  Teleneurorehabilitation for Parkinson's Disease: A Panacea for the Times to Come?

Authors:  Divyani Garg; Rajinder K Dhamija
Journal:  Ann Indian Acad Neurol       Date:  2020-10-26       Impact factor: 1.383

  8 in total

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