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Biosensor vital sign detects multiple sclerosis progression

OBJECTIVE: To determine whether a small, wearable multisensor device can discriminate between progressive versus relapsing multiple sclerosis (MS) and capture limb progression over a short interval, using finger and foot tap data. METHODS: Patients with MS were followed prospectively during routine...

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Autores principales: Krysko, Kristen M., Akhbardeh, Alireza, Arjona, Jennifer, Nourbakhsh, Bardia, Waubant, Emmanuelle, Antoine Gourraud, Pierre, 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/PMC7818086/
https://www.ncbi.nlm.nih.gov/pubmed/33211403
http://dx.doi.org/10.1002/acn3.51187
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author Krysko, Kristen M.
Akhbardeh, Alireza
Arjona, Jennifer
Nourbakhsh, Bardia
Waubant, Emmanuelle
Antoine Gourraud, Pierre
Graves, Jennifer S.
author_facet Krysko, Kristen M.
Akhbardeh, Alireza
Arjona, Jennifer
Nourbakhsh, Bardia
Waubant, Emmanuelle
Antoine Gourraud, Pierre
Graves, Jennifer S.
author_sort Krysko, Kristen M.
collection PubMed
description OBJECTIVE: To determine whether a small, wearable multisensor device can discriminate between progressive versus relapsing multiple sclerosis (MS) and capture limb progression over a short interval, using finger and foot tap data. METHODS: Patients with MS were followed prospectively during routine clinic visits approximately every 6 months. At each visit, participants performed finger and foot taps wearing the MYO‐band, which includes accelerometer, gyroscope, and surface electromyogram sensors. Metrics of within‐patient limb progression were created by combining the change in signal waveform features over time. The resulting upper (UE) and lower (LE) extremity metrics’ discrimination of progressive versus relapsing MS were evaluated with calculation of AUROC. Comparisons with Expanded Disability Status Scale (EDSS) scores were made with Pearson correlation. RESULTS: Participants included 53 relapsing and 15 progressive MS (72% female, baseline mean age 48 years, median disease duration 11 years, median EDSS 2.5, median 10 months follow‐up). The final summary metrics differentiated relapsing from secondary progressive MS with AUROC UE 0.93 and LE 0.96. The metrics were associated with baseline EDSS (UE P = 0.0003, LE P = 0.0007). While most had no change in EDSS during the short follow‐up, several had evidence of progression by the multisensor metrics. INTERPRETATION: Within a short follow‐up interval, this novel multisensor algorithm distinguished progressive from relapsing MS and captured changes in limb function. Inexpensive, noninvasive and easy to use, this novel outcome is readily adaptable to clinical practice and trials as a MS vital sign. This approach also holds promise to monitor limb dysfunction in other neurological diseases.
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spelling pubmed-78180862021-01-29 Biosensor vital sign detects multiple sclerosis progression Krysko, Kristen M. Akhbardeh, Alireza Arjona, Jennifer Nourbakhsh, Bardia Waubant, Emmanuelle Antoine Gourraud, Pierre Graves, Jennifer S. Ann Clin Transl Neurol Research Articles OBJECTIVE: To determine whether a small, wearable multisensor device can discriminate between progressive versus relapsing multiple sclerosis (MS) and capture limb progression over a short interval, using finger and foot tap data. METHODS: Patients with MS were followed prospectively during routine clinic visits approximately every 6 months. At each visit, participants performed finger and foot taps wearing the MYO‐band, which includes accelerometer, gyroscope, and surface electromyogram sensors. Metrics of within‐patient limb progression were created by combining the change in signal waveform features over time. The resulting upper (UE) and lower (LE) extremity metrics’ discrimination of progressive versus relapsing MS were evaluated with calculation of AUROC. Comparisons with Expanded Disability Status Scale (EDSS) scores were made with Pearson correlation. RESULTS: Participants included 53 relapsing and 15 progressive MS (72% female, baseline mean age 48 years, median disease duration 11 years, median EDSS 2.5, median 10 months follow‐up). The final summary metrics differentiated relapsing from secondary progressive MS with AUROC UE 0.93 and LE 0.96. The metrics were associated with baseline EDSS (UE P = 0.0003, LE P = 0.0007). While most had no change in EDSS during the short follow‐up, several had evidence of progression by the multisensor metrics. INTERPRETATION: Within a short follow‐up interval, this novel multisensor algorithm distinguished progressive from relapsing MS and captured changes in limb function. Inexpensive, noninvasive and easy to use, this novel outcome is readily adaptable to clinical practice and trials as a MS vital sign. This approach also holds promise to monitor limb dysfunction in other neurological diseases. John Wiley and Sons Inc. 2020-11-19 /pmc/articles/PMC7818086/ /pubmed/33211403 http://dx.doi.org/10.1002/acn3.51187 Text en © 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Krysko, Kristen M.
Akhbardeh, Alireza
Arjona, Jennifer
Nourbakhsh, Bardia
Waubant, Emmanuelle
Antoine Gourraud, Pierre
Graves, Jennifer S.
Biosensor vital sign detects multiple sclerosis progression
title Biosensor vital sign detects multiple sclerosis progression
title_full Biosensor vital sign detects multiple sclerosis progression
title_fullStr Biosensor vital sign detects multiple sclerosis progression
title_full_unstemmed Biosensor vital sign detects multiple sclerosis progression
title_short Biosensor vital sign detects multiple sclerosis progression
title_sort biosensor vital sign detects multiple sclerosis progression
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7818086/
https://www.ncbi.nlm.nih.gov/pubmed/33211403
http://dx.doi.org/10.1002/acn3.51187
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