Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices

Abstract Patients with atopic dermatitis experience increased nocturnal pruritus which leads to scratching and sleep disturbances that significantly contribute to poor quality of life. Objective measurements of nighttime scratching and sleep quantity can help assess the efficacy of an intervention....

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Autores principales:	Nikhil Mahadevan, Yiorgos Christakis, Junrui Di, Jonathan Bruno, Yao Zhang, E. Ray Dorsey, Wilfred R. Pigeon, Lisa A. Beck, Kevin Thomas, Yaqi Liu, Madisen Wicker, Chris Brooks, Nina Shaafi Kabiri, Jaspreet Bhangu, Carrie Northcott, Shyamal Patel
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/c452dd45a9f942c3b5036e412aa9cded
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spelling	oai:doaj.org-article:c452dd45a9f942c3b5036e412aa9cded2021-12-02T15:54:14ZDevelopment of digital measures for nighttime scratch and sleep using wrist-worn wearable devices10.1038/s41746-021-00402-x2398-6352https://doaj.org/article/c452dd45a9f942c3b5036e412aa9cded2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41746-021-00402-xhttps://doaj.org/toc/2398-6352Abstract Patients with atopic dermatitis experience increased nocturnal pruritus which leads to scratching and sleep disturbances that significantly contribute to poor quality of life. Objective measurements of nighttime scratching and sleep quantity can help assess the efficacy of an intervention. Wearable sensors can provide novel, objective measures of nighttime scratching and sleep; however, many current approaches were not designed for passive, unsupervised monitoring during daily life. In this work, we present the development and analytical validation of a method that sequentially processes epochs of sample-level accelerometer data from a wrist-worn device to provide continuous digital measures of nighttime scratching and sleep quantity. This approach uses heuristic and machine learning algorithms in a hierarchical paradigm by first determining when the patient intends to sleep, then detecting sleep–wake states along with scratching episodes, and lastly deriving objective measures of both sleep and scratch. Leveraging reference data collected in a sleep laboratory (NCT ID: NCT03490877), results show that sensor-derived measures of total sleep opportunity (TSO; time when patient intends to sleep) and total sleep time (TST) correlate well with reference polysomnography data (TSO: r = 0.72, p < 0.001; TST: r = 0.76, p < 0.001; N = 32). Log transformed sensor derived measures of total scratching duration achieve strong agreement with reference annotated video recordings (r = 0.82, p < 0.001; N = 25). These results support the use of wearable sensors for objective, continuous measurement of nighttime scratching and sleep during daily life.Nikhil MahadevanYiorgos ChristakisJunrui DiJonathan BrunoYao ZhangE. Ray DorseyWilfred R. PigeonLisa A. BeckKevin ThomasYaqi LiuMadisen WickerChris BrooksNina Shaafi KabiriJaspreet BhanguCarrie NorthcottShyamal PatelNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 4, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Nikhil Mahadevan Yiorgos Christakis Junrui Di Jonathan Bruno Yao Zhang E. Ray Dorsey Wilfred R. Pigeon Lisa A. Beck Kevin Thomas Yaqi Liu Madisen Wicker Chris Brooks Nina Shaafi Kabiri Jaspreet Bhangu Carrie Northcott Shyamal Patel Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices
description	Abstract Patients with atopic dermatitis experience increased nocturnal pruritus which leads to scratching and sleep disturbances that significantly contribute to poor quality of life. Objective measurements of nighttime scratching and sleep quantity can help assess the efficacy of an intervention. Wearable sensors can provide novel, objective measures of nighttime scratching and sleep; however, many current approaches were not designed for passive, unsupervised monitoring during daily life. In this work, we present the development and analytical validation of a method that sequentially processes epochs of sample-level accelerometer data from a wrist-worn device to provide continuous digital measures of nighttime scratching and sleep quantity. This approach uses heuristic and machine learning algorithms in a hierarchical paradigm by first determining when the patient intends to sleep, then detecting sleep–wake states along with scratching episodes, and lastly deriving objective measures of both sleep and scratch. Leveraging reference data collected in a sleep laboratory (NCT ID: NCT03490877), results show that sensor-derived measures of total sleep opportunity (TSO; time when patient intends to sleep) and total sleep time (TST) correlate well with reference polysomnography data (TSO: r = 0.72, p < 0.001; TST: r = 0.76, p < 0.001; N = 32). Log transformed sensor derived measures of total scratching duration achieve strong agreement with reference annotated video recordings (r = 0.82, p < 0.001; N = 25). These results support the use of wearable sensors for objective, continuous measurement of nighttime scratching and sleep during daily life.
format	article
author	Nikhil Mahadevan Yiorgos Christakis Junrui Di Jonathan Bruno Yao Zhang E. Ray Dorsey Wilfred R. Pigeon Lisa A. Beck Kevin Thomas Yaqi Liu Madisen Wicker Chris Brooks Nina Shaafi Kabiri Jaspreet Bhangu Carrie Northcott Shyamal Patel
author_facet	Nikhil Mahadevan Yiorgos Christakis Junrui Di Jonathan Bruno Yao Zhang E. Ray Dorsey Wilfred R. Pigeon Lisa A. Beck Kevin Thomas Yaqi Liu Madisen Wicker Chris Brooks Nina Shaafi Kabiri Jaspreet Bhangu Carrie Northcott Shyamal Patel
author_sort	Nikhil Mahadevan
title	Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices
title_short	Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices
title_full	Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices
title_fullStr	Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices
title_full_unstemmed	Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices
title_sort	development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/c452dd45a9f942c3b5036e412aa9cded
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Development of digital measures for nighttime scratch and sleep using wrist-worn wearable devices

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