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Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study
BACKGROUND: Facioscapulohumeral dystrophy (FSHD) is a progressive muscle dystrophy disorder leading to significant disability. Currently, FSHD symptom severity is assessed by clinical assessments such as the FSHD clinical score and the Timed Up-and-Go test. These assessments are limited in their abi...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516375/ https://www.ncbi.nlm.nih.gov/pubmed/36098990 http://dx.doi.org/10.2196/31775 |
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author | Maleki, Ghobad Zhuparris, Ahnjili Koopmans, Ingrid Doll, Robert J Voet, Nicoline Cohen, Adam van Brummelen, Emilie Groeneveld, Geert Jan De Maeyer, Joris |
author_facet | Maleki, Ghobad Zhuparris, Ahnjili Koopmans, Ingrid Doll, Robert J Voet, Nicoline Cohen, Adam van Brummelen, Emilie Groeneveld, Geert Jan De Maeyer, Joris |
author_sort | Maleki, Ghobad |
collection | PubMed |
description | BACKGROUND: Facioscapulohumeral dystrophy (FSHD) is a progressive muscle dystrophy disorder leading to significant disability. Currently, FSHD symptom severity is assessed by clinical assessments such as the FSHD clinical score and the Timed Up-and-Go test. These assessments are limited in their ability to capture changes continuously and the full impact of the disease on patients’ quality of life. Real-world data related to physical activity, sleep, and social behavior could potentially provide additional insight into the impact of the disease and might be useful in assessing treatment effects on aspects that are important contributors to the functioning and well-being of patients with FSHD. OBJECTIVE: This study investigated the feasibility of using smartphones and wearables to capture symptoms related to FSHD based on a continuous collection of multiple features, such as the number of steps, sleep, and app use. We also identified features that can be used to differentiate between patients with FSHD and non-FSHD controls. METHODS: In this exploratory noninterventional study, 58 participants (n=38, 66%, patients with FSHD and n=20, 34%, non-FSHD controls) were monitored using a smartphone monitoring app for 6 weeks. On the first and last day of the study period, clinicians assessed the participants’ FSHD clinical score and Timed Up-and-Go test time. Participants installed the app on their Android smartphones, were given a smartwatch, and were instructed to measure their weight and blood pressure on a weekly basis using a scale and blood pressure monitor. The user experience and perceived burden of the app on participants’ smartphones were assessed at 6 weeks using a questionnaire. With the data collected, we sought to identify the behavioral features that were most salient in distinguishing the 2 groups (patients with FSHD and non-FSHD controls) and the optimal time window to perform the classification. RESULTS: Overall, the participants stated that the app was well tolerated, but 67% (39/58) noticed a difference in battery life using all 6 weeks of data, we classified patients with FSHD and non-FSHD controls with 93% accuracy, 100% sensitivity, and 80% specificity. We found that the optimal time window for the classification is the first day of data collection and the first week of data collection, which yielded an accuracy, sensitivity, and specificity of 95.8%, 100%, and 94.4%, respectively. Features relating to smartphone acceleration, app use, location, physical activity, sleep, and call behavior were the most salient features for the classification. CONCLUSIONS: Remotely monitored data collection allowed for the collection of daily activity data in patients with FSHD and non-FSHD controls for 6 weeks. We demonstrated the initial ability to detect differences in features in patients with FSHD and non-FSHD controls using smartphones and wearables, mainly based on data related to physical and social activity. TRIAL REGISTRATION: ClinicalTrials.gov NCT04999735; https://www.clinicaltrials.gov/ct2/show/NCT04999735 |
format | Online Article Text |
id | pubmed-9516375 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-95163752022-09-29 Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study Maleki, Ghobad Zhuparris, Ahnjili Koopmans, Ingrid Doll, Robert J Voet, Nicoline Cohen, Adam van Brummelen, Emilie Groeneveld, Geert Jan De Maeyer, Joris JMIR Form Res Original Paper BACKGROUND: Facioscapulohumeral dystrophy (FSHD) is a progressive muscle dystrophy disorder leading to significant disability. Currently, FSHD symptom severity is assessed by clinical assessments such as the FSHD clinical score and the Timed Up-and-Go test. These assessments are limited in their ability to capture changes continuously and the full impact of the disease on patients’ quality of life. Real-world data related to physical activity, sleep, and social behavior could potentially provide additional insight into the impact of the disease and might be useful in assessing treatment effects on aspects that are important contributors to the functioning and well-being of patients with FSHD. OBJECTIVE: This study investigated the feasibility of using smartphones and wearables to capture symptoms related to FSHD based on a continuous collection of multiple features, such as the number of steps, sleep, and app use. We also identified features that can be used to differentiate between patients with FSHD and non-FSHD controls. METHODS: In this exploratory noninterventional study, 58 participants (n=38, 66%, patients with FSHD and n=20, 34%, non-FSHD controls) were monitored using a smartphone monitoring app for 6 weeks. On the first and last day of the study period, clinicians assessed the participants’ FSHD clinical score and Timed Up-and-Go test time. Participants installed the app on their Android smartphones, were given a smartwatch, and were instructed to measure their weight and blood pressure on a weekly basis using a scale and blood pressure monitor. The user experience and perceived burden of the app on participants’ smartphones were assessed at 6 weeks using a questionnaire. With the data collected, we sought to identify the behavioral features that were most salient in distinguishing the 2 groups (patients with FSHD and non-FSHD controls) and the optimal time window to perform the classification. RESULTS: Overall, the participants stated that the app was well tolerated, but 67% (39/58) noticed a difference in battery life using all 6 weeks of data, we classified patients with FSHD and non-FSHD controls with 93% accuracy, 100% sensitivity, and 80% specificity. We found that the optimal time window for the classification is the first day of data collection and the first week of data collection, which yielded an accuracy, sensitivity, and specificity of 95.8%, 100%, and 94.4%, respectively. Features relating to smartphone acceleration, app use, location, physical activity, sleep, and call behavior were the most salient features for the classification. CONCLUSIONS: Remotely monitored data collection allowed for the collection of daily activity data in patients with FSHD and non-FSHD controls for 6 weeks. We demonstrated the initial ability to detect differences in features in patients with FSHD and non-FSHD controls using smartphones and wearables, mainly based on data related to physical and social activity. TRIAL REGISTRATION: ClinicalTrials.gov NCT04999735; https://www.clinicaltrials.gov/ct2/show/NCT04999735 JMIR Publications 2022-09-13 /pmc/articles/PMC9516375/ /pubmed/36098990 http://dx.doi.org/10.2196/31775 Text en ©Ghobad Maleki, Ahnjili Zhuparris, Ingrid Koopmans, Robert J Doll, Nicoline Voet, Adam Cohen, Emilie van Brummelen, Geert Jan Groeneveld, Joris De Maeyer. Originally published in JMIR Formative Research (https://formative.jmir.org), 13.09.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Maleki, Ghobad Zhuparris, Ahnjili Koopmans, Ingrid Doll, Robert J Voet, Nicoline Cohen, Adam van Brummelen, Emilie Groeneveld, Geert Jan De Maeyer, Joris Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study |
title | Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study |
title_full | Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study |
title_fullStr | Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study |
title_full_unstemmed | Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study |
title_short | Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study |
title_sort | objective monitoring of facioscapulohumeral dystrophy during clinical trials using a smartphone app and wearables: observational study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516375/ https://www.ncbi.nlm.nih.gov/pubmed/36098990 http://dx.doi.org/10.2196/31775 |
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