Literature DB >> 28391201

Using Wearable Technology to Generate Objective Parkinson's Disease Dyskinesia Severity Score: Possibilities for Home Monitoring.

Mehdi Delrobaei, Navid Baktash, Greydon Gilmore, Kenneth McIsaac, Mandar Jog.   

Abstract

A variety of clinical scales are available to assess dyskinesia severity in Parkinson's disease patients; however, such assessments are subjective, do not provide long term monitoring, and their use is subject to inter- and intra-rater variability. In this paper, an objective dyskinesia score was developed using an IMU -based motion capture system. Deep brain stimulation (DBS) surgery is currently the only acute intervention that results in the rapidly progressive reduction of dyskinesia's severity; hence, this form of therapy was selected as a model to validate the proposed method. Thirteen Parkinson's disease participants undergoing DBS surgery and 12 age-matched healthy control participants were assessed using the motion capture system. Concurrent Unified Dyskinesia Rating Scale (UDysRS) ratings were also performed. Parkinson's disease participants were assessed pre-operatively and for five visits post-operatively while seated at rest, during arms outstretched and while performing an action task. The kinematic data were used to develop an objective measure defined as the dyskinesia severity score. Generally, a strong correlation was observed between the UDysRS ratings and the full-body dyskinesia severity scores. The results suggest that it is feasible and clinically meaningful to utilize an objective full-body dyskinesia score for the assessment of dyskinesia. The portable motion capture system along with the developed software can be used remotely to monitor the full-body severity of dyskinesia, necessary for therapeutic optimization, especially in the patients home environment.

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Year:  2017        PMID: 28391201     DOI: 10.1109/TNSRE.2017.2690578

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  7 in total

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Authors:  Ritam Bandopadhyay; Nainshi Mishra; Ruhi Rana; Gagandeep Kaur; Mohammed M Ghoneim; Sultan Alshehri; Gulam Mustafa; Javed Ahmad; Nabil A Alhakamy; Awanish Mishra
Journal:  Front Pharmacol       Date:  2022-04-07       Impact factor: 5.988

2.  Vision-based assessment of parkinsonism and levodopa-induced dyskinesia with pose estimation.

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Journal:  J Neuroeng Rehabil       Date:  2018-11-06       Impact factor: 4.262

3.  Application of Wavelet in Quantitative Evaluation of Gait Events of Parkinson's Disease.

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Review 4.  Remote Patient Monitoring for Neuropsychiatric Disorders: A Scoping Review of Current Trends and Future Perspectives from Recent Publications and Upcoming Clinical Trials.

Authors:  Tetsuo Sakamaki; Yoshihiko Furusawa; Ayako Hayashi; Masaru Otsuka; Jovelle Fernandez
Journal:  Telemed J E Health       Date:  2022-01-24       Impact factor: 5.033

5.  Objective assessment of bradykinesia in Parkinson's disease using evolutionary algorithms: clinical validation.

Authors:  Chao Gao; Stephen Smith; Michael Lones; Stuart Jamieson; Jane Alty; Jeremy Cosgrove; Pingchen Zhang; Jin Liu; Yimeng Chen; Juanjuan Du; Shishuang Cui; Haiyan Zhou; Shengdi Chen
Journal:  Transl Neurodegener       Date:  2018-08-16       Impact factor: 8.014

Review 6.  An update on adaptive deep brain stimulation in Parkinson's disease.

Authors:  Jeroen G V Habets; Margot Heijmans; Mark L Kuijf; Marcus L F Janssen; Yasin Temel; Pieter L Kubben
Journal:  Mov Disord       Date:  2018-10-24       Impact factor: 10.338

7.  Monitoring Parkinson's disease symptoms during daily life: a feasibility study.

Authors:  Margot Heijmans; Jeroen G V Habets; Christian Herff; Jos Aarts; An Stevens; Mark L Kuijf; Pieter L Kubben
Journal:  NPJ Parkinsons Dis       Date:  2019-09-30
  7 in total

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