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Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson’s disease in Japan

Continuous, objective monitoring of motor signs and symptoms may help improve tracking of disease progression and treatment response in Parkinson’s disease (PD). This study assessed the analytical and clinical validity of multi-sensor smartwatch measurements in hospitalized and home-based settings (...

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Autores principales: Oyama, Genko, Burq, Maximilien, Hatano, Taku, Marks, William J., Kapur, Ritu, Fernandez, Jovelle, Fujikawa, Keita, Furusawa, Yoshihiko, Nakatome, Keisuke, Rainaldi, Erin, Chen, Chen, Ho, King Chung, Ogawa, Takashi, Kamo, Hikaru, Oji, Yutaka, Takeshige-Amano, Haruka, Taniguchi, Daisuke, Nakamura, Ryota, Sasaki, Fuyuko, Ueno, Shinichi, Shiina, Kenta, Hattori, Anri, Nishikawa, Noriko, Ishiguro, Mayu, Saiki, Shinji, Hayashi, Ayako, Motohashi, Masatoshi, Hattori, Nobutaka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10015076/
https://www.ncbi.nlm.nih.gov/pubmed/36918552
http://dx.doi.org/10.1038/s41598-023-29382-6
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author Oyama, Genko
Burq, Maximilien
Hatano, Taku
Marks, William J.
Kapur, Ritu
Fernandez, Jovelle
Fujikawa, Keita
Furusawa, Yoshihiko
Nakatome, Keisuke
Rainaldi, Erin
Chen, Chen
Ho, King Chung
Ogawa, Takashi
Kamo, Hikaru
Oji, Yutaka
Takeshige-Amano, Haruka
Taniguchi, Daisuke
Nakamura, Ryota
Sasaki, Fuyuko
Ueno, Shinichi
Shiina, Kenta
Hattori, Anri
Nishikawa, Noriko
Ishiguro, Mayu
Saiki, Shinji
Hayashi, Ayako
Motohashi, Masatoshi
Hattori, Nobutaka
author_facet Oyama, Genko
Burq, Maximilien
Hatano, Taku
Marks, William J.
Kapur, Ritu
Fernandez, Jovelle
Fujikawa, Keita
Furusawa, Yoshihiko
Nakatome, Keisuke
Rainaldi, Erin
Chen, Chen
Ho, King Chung
Ogawa, Takashi
Kamo, Hikaru
Oji, Yutaka
Takeshige-Amano, Haruka
Taniguchi, Daisuke
Nakamura, Ryota
Sasaki, Fuyuko
Ueno, Shinichi
Shiina, Kenta
Hattori, Anri
Nishikawa, Noriko
Ishiguro, Mayu
Saiki, Shinji
Hayashi, Ayako
Motohashi, Masatoshi
Hattori, Nobutaka
author_sort Oyama, Genko
collection PubMed
description Continuous, objective monitoring of motor signs and symptoms may help improve tracking of disease progression and treatment response in Parkinson’s disease (PD). This study assessed the analytical and clinical validity of multi-sensor smartwatch measurements in hospitalized and home-based settings (96 patients with PD; mean wear time 19 h/day) using a twice-daily virtual motor examination (VME) at times representing medication OFF/ON states. Digital measurement performance was better during inpatient clinical assessments for composite V-scores than single-sensor–derived features for bradykinesia (Spearman |r|= 0.63, reliability = 0.72), tremor (|r|= 0.41, reliability = 0.65), and overall motor features (|r|= 0.70, reliability = 0.67). Composite levodopa effect sizes during hospitalization were 0.51–1.44 for clinical assessments and 0.56–1.37 for VMEs. Reliability of digital measurements during home-based VMEs was 0.62–0.80 for scores derived from weekly averages and 0.24–0.66 for daily measurements. These results show that unsupervised digital measurements of motor features with wrist-worn sensors are sensitive to medication state and are reliable in naturalistic settings. Trial Registration: Japan Pharmaceutical Information Center Clinical Trials Information (JAPIC-CTI): JapicCTI-194825; Registered June 25, 2019.
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spelling pubmed-100150762023-03-16 Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson’s disease in Japan Oyama, Genko Burq, Maximilien Hatano, Taku Marks, William J. Kapur, Ritu Fernandez, Jovelle Fujikawa, Keita Furusawa, Yoshihiko Nakatome, Keisuke Rainaldi, Erin Chen, Chen Ho, King Chung Ogawa, Takashi Kamo, Hikaru Oji, Yutaka Takeshige-Amano, Haruka Taniguchi, Daisuke Nakamura, Ryota Sasaki, Fuyuko Ueno, Shinichi Shiina, Kenta Hattori, Anri Nishikawa, Noriko Ishiguro, Mayu Saiki, Shinji Hayashi, Ayako Motohashi, Masatoshi Hattori, Nobutaka Sci Rep Article Continuous, objective monitoring of motor signs and symptoms may help improve tracking of disease progression and treatment response in Parkinson’s disease (PD). This study assessed the analytical and clinical validity of multi-sensor smartwatch measurements in hospitalized and home-based settings (96 patients with PD; mean wear time 19 h/day) using a twice-daily virtual motor examination (VME) at times representing medication OFF/ON states. Digital measurement performance was better during inpatient clinical assessments for composite V-scores than single-sensor–derived features for bradykinesia (Spearman |r|= 0.63, reliability = 0.72), tremor (|r|= 0.41, reliability = 0.65), and overall motor features (|r|= 0.70, reliability = 0.67). Composite levodopa effect sizes during hospitalization were 0.51–1.44 for clinical assessments and 0.56–1.37 for VMEs. Reliability of digital measurements during home-based VMEs was 0.62–0.80 for scores derived from weekly averages and 0.24–0.66 for daily measurements. These results show that unsupervised digital measurements of motor features with wrist-worn sensors are sensitive to medication state and are reliable in naturalistic settings. Trial Registration: Japan Pharmaceutical Information Center Clinical Trials Information (JAPIC-CTI): JapicCTI-194825; Registered June 25, 2019. Nature Publishing Group UK 2023-03-14 /pmc/articles/PMC10015076/ /pubmed/36918552 http://dx.doi.org/10.1038/s41598-023-29382-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Oyama, Genko
Burq, Maximilien
Hatano, Taku
Marks, William J.
Kapur, Ritu
Fernandez, Jovelle
Fujikawa, Keita
Furusawa, Yoshihiko
Nakatome, Keisuke
Rainaldi, Erin
Chen, Chen
Ho, King Chung
Ogawa, Takashi
Kamo, Hikaru
Oji, Yutaka
Takeshige-Amano, Haruka
Taniguchi, Daisuke
Nakamura, Ryota
Sasaki, Fuyuko
Ueno, Shinichi
Shiina, Kenta
Hattori, Anri
Nishikawa, Noriko
Ishiguro, Mayu
Saiki, Shinji
Hayashi, Ayako
Motohashi, Masatoshi
Hattori, Nobutaka
Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson’s disease in Japan
title Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson’s disease in Japan
title_full Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson’s disease in Japan
title_fullStr Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson’s disease in Japan
title_full_unstemmed Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson’s disease in Japan
title_short Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson’s disease in Japan
title_sort analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with parkinson’s disease in japan
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10015076/
https://www.ncbi.nlm.nih.gov/pubmed/36918552
http://dx.doi.org/10.1038/s41598-023-29382-6
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