Automated assessment of movement impairment in Huntington's disease

Bennasar, M, Hicks, Y. A. ORCID: https://orcid.org/0000-0002-7179-4587, Clinch, S. P., Jones, P ORCID: https://orcid.org/0000-0003-2240-691X, Holt, C ORCID: https://orcid.org/0000-0002-0428-8078, Rosser, A ORCID: https://orcid.org/0000-0002-4716-4753 and Busse-Morris, M. ORCID: https://orcid.org/0000-0002-5331-5909 2018. Automated assessment of movement impairment in Huntington's disease. IEEE Transactions on Neural Systems and Rehabilitation Engineering 26 (10) , pp. 2062-2069. 10.1109/TNSRE.2018.2868170

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Abstract

Quantitative assessment of movement impairment in Huntington’s disease (HD) is essential to monitoring of disease progression. This study aimed to develop and validate a novel low cost, objective automated system for the evaluation of upper limb movement impairment in HD in order to eliminate the inconsistency of the assessor and offer a more sensitive, continuous assessment scale. Patients with genetically confirmed HD and healthy controls were recruited to this observational study. Demographic data including age (years), gender and Unified Huntington’s Disease Rating Scale Total Motor Score (UHDRS-TMS) were recorded. For the purposes of this study a modified upper limb motor impairment score (mULMS) was generated from the UHDRS-TMS. All participants completed a brief, standardized clinical assessment of upper limb dexterity whilst wearing a tri-axial accelerometer on each wrist and on the sternum. The captured acceleration data were used to develop an automatic classification system for discriminating between healthy and HD participants and to automatically generate a continuous Movement Impairment Score (MIS) that reflected the degree of the movement impairment. Data from 48 healthy and 44 HD participants was used to validate the developed system, which achieved 98.78% accuracy in discriminating between healthy and HD participants. The Pearson correlation coefficient between the automatic MIS and the clinician rated mULMS was 0.77 with a p-value < 0.01. The approach presented in this study demonstrates the possibility of an automated objective, consistent and sensitive assessment of the HD movement impairment.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Biosciences Engineering Centre for Trials Research (CNTRR) Medicine
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
ISSN:	1534-4320
Date of First Compliant Deposit:	5 September 2018
Date of Acceptance:	1 August 2018
Last Modified:	13 Nov 2024 13:30
URI:	https://orca.cardiff.ac.uk/id/eprint/114671

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