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Novel MS vital sign: multi‐sensor captures upper and lower limb dysfunction

OBJECTIVE: To create a novel neurological vital sign and reliably capture MS‐related limb disability in less than 5 min. METHODS: Consecutive patients meeting the 2010 MS diagnostic criteria and healthy controls were offered enrollment. Participants completed finger and foot taps wearing the MYO‐ban...

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Autores principales: Akhbardeh, Alireza, Arjona, Jennifer K., Krysko, Kristen M., Nourbakhsh, Bardia, Gourraud, Pierre Antoine, Graves, Jennifer S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085995/
https://www.ncbi.nlm.nih.gov/pubmed/32101388
http://dx.doi.org/10.1002/acn3.50988
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author Akhbardeh, Alireza
Arjona, Jennifer K.
Krysko, Kristen M.
Nourbakhsh, Bardia
Gourraud, Pierre Antoine
Graves, Jennifer S.
author_facet Akhbardeh, Alireza
Arjona, Jennifer K.
Krysko, Kristen M.
Nourbakhsh, Bardia
Gourraud, Pierre Antoine
Graves, Jennifer S.
author_sort Akhbardeh, Alireza
collection PubMed
description OBJECTIVE: To create a novel neurological vital sign and reliably capture MS‐related limb disability in less than 5 min. METHODS: Consecutive patients meeting the 2010 MS diagnostic criteria and healthy controls were offered enrollment. Participants completed finger and foot taps wearing the MYO‐band© (accelerometer, gyroscope, and surface electromyogram sensors). Signal processing was performed to extract spatiotemporal features from raw sensor data. Intraclass correlation coefficients (ICC) assessed intertest reproducibility. Spearman correlation and multivariable regression methods compared extracted features to physician‐ and patient‐reported disability outcomes. Partial least squares regression identified the most informative extracted textural features. RESULTS: Baseline data for 117 participants with MS (EDSS 1.0–7.0) and 30 healthy controls were analyzed. ICCs for final selected features ranged from 0.80 to 0.87. Time‐based features distinguished cases from controls (P = 0.002). The most informative combination of extracted features from all three sensors strongly correlated with physician EDSS (finger taps r(s) = 0.77, P < 0.0001; foot taps r(s) = 0.82, P < 0.0001) and had equally strong associations with patient‐reported outcomes (WHODAS, finger taps r(s) = 0.82, P < 0.0001; foot taps r(s) = 0.82, P < 0.0001). Associations remained with multivariable modeling adjusted for age and sex. CONCLUSIONS: Extracted features from the multi‐sensor demonstrate striking correlations with gold standard outcomes. Ideal for future generalizability, the assessments take only a few minutes, can be performed by nonclinical personnel, and wearing the band is nondisruptive to routine practice. This novel paradigm holds promise as a new neurological vital sign.
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spelling pubmed-70859952020-03-24 Novel MS vital sign: multi‐sensor captures upper and lower limb dysfunction Akhbardeh, Alireza Arjona, Jennifer K. Krysko, Kristen M. Nourbakhsh, Bardia Gourraud, Pierre Antoine Graves, Jennifer S. Ann Clin Transl Neurol Research Articles OBJECTIVE: To create a novel neurological vital sign and reliably capture MS‐related limb disability in less than 5 min. METHODS: Consecutive patients meeting the 2010 MS diagnostic criteria and healthy controls were offered enrollment. Participants completed finger and foot taps wearing the MYO‐band© (accelerometer, gyroscope, and surface electromyogram sensors). Signal processing was performed to extract spatiotemporal features from raw sensor data. Intraclass correlation coefficients (ICC) assessed intertest reproducibility. Spearman correlation and multivariable regression methods compared extracted features to physician‐ and patient‐reported disability outcomes. Partial least squares regression identified the most informative extracted textural features. RESULTS: Baseline data for 117 participants with MS (EDSS 1.0–7.0) and 30 healthy controls were analyzed. ICCs for final selected features ranged from 0.80 to 0.87. Time‐based features distinguished cases from controls (P = 0.002). The most informative combination of extracted features from all three sensors strongly correlated with physician EDSS (finger taps r(s) = 0.77, P < 0.0001; foot taps r(s) = 0.82, P < 0.0001) and had equally strong associations with patient‐reported outcomes (WHODAS, finger taps r(s) = 0.82, P < 0.0001; foot taps r(s) = 0.82, P < 0.0001). Associations remained with multivariable modeling adjusted for age and sex. CONCLUSIONS: Extracted features from the multi‐sensor demonstrate striking correlations with gold standard outcomes. Ideal for future generalizability, the assessments take only a few minutes, can be performed by nonclinical personnel, and wearing the band is nondisruptive to routine practice. This novel paradigm holds promise as a new neurological vital sign. John Wiley and Sons Inc. 2020-02-26 /pmc/articles/PMC7085995/ /pubmed/32101388 http://dx.doi.org/10.1002/acn3.50988 Text en © 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Akhbardeh, Alireza
Arjona, Jennifer K.
Krysko, Kristen M.
Nourbakhsh, Bardia
Gourraud, Pierre Antoine
Graves, Jennifer S.
Novel MS vital sign: multi‐sensor captures upper and lower limb dysfunction
title Novel MS vital sign: multi‐sensor captures upper and lower limb dysfunction
title_full Novel MS vital sign: multi‐sensor captures upper and lower limb dysfunction
title_fullStr Novel MS vital sign: multi‐sensor captures upper and lower limb dysfunction
title_full_unstemmed Novel MS vital sign: multi‐sensor captures upper and lower limb dysfunction
title_short Novel MS vital sign: multi‐sensor captures upper and lower limb dysfunction
title_sort novel ms vital sign: multi‐sensor captures upper and lower limb dysfunction
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085995/
https://www.ncbi.nlm.nih.gov/pubmed/32101388
http://dx.doi.org/10.1002/acn3.50988
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