PURPOSE: Although polysomnography is necessary for diagnosis of most sleep disorders, it is also expensive, time-consuming, intrusive, and interferes with sleep. Field-based activity monitoring is increasingly used as an alternative measure that can be used to answer certain clinical and research questions. The purpose of this study was to evaluate the reliability and validity of a novel activity monitoring device (Fitbit) compared to both polysomnography and standard actigraphy (Actiwatch-64). METHODS: To test validity, simultaneous Fitbit and actigraph were worn during standard overnight polysomnography by 24 healthy adults at the West Virginia University sleep research laboratory. To test inter-Fitbit reliability, three participants also wore two of the Fitbit devices overnight at home. RESULTS: Fitbit showed high intradevice reliability = 96.5-99.1. Fitbit and actigraph differed significantly on recorded total sleep time and sleep efficiency between each other and polysomnography. Bland-Altman plots indicated that both Fitbit and actigraph overestimated sleep efficiency and total sleep time. Sensitivity of both Fitbit and actigraphy for accurately identifying sleep was high within all sleep stages and during arousals; specificity of both Fitbit and actigraph for accurately identifying wake was poor. Specificity of actigraph was higher except for wake before sleep onset; sensitivity of Fitbit was higher in all sleep stages and during arousals. CONCLUSIONS: The web-based Fitbit, available at a markedly reduced price and with several convenience factors compared to standard actigraphy, may be an acceptable activity measurement instrument for use with normative populations. However, Fitbit has the same specificity limitations as actigraphy; both devices consistently misidentify wake as sleep and thus overestimate both sleep time and quality. Use of the Fitbit will also require specific validation before it can be used to assess disordered populations and or different age groups.
PURPOSE: Although polysomnography is necessary for diagnosis of most sleep disorders, it is also expensive, time-consuming, intrusive, and interferes with sleep. Field-based activity monitoring is increasingly used as an alternative measure that can be used to answer certain clinical and research questions. The purpose of this study was to evaluate the reliability and validity of a novel activity monitoring device (Fitbit) compared to both polysomnography and standard actigraphy (Actiwatch-64). METHODS: To test validity, simultaneous Fitbit and actigraph were worn during standard overnight polysomnography by 24 healthy adults at the West Virginia University sleep research laboratory. To test inter-Fitbit reliability, three participants also wore two of the Fitbit devices overnight at home. RESULTS: Fitbit showed high intradevice reliability = 96.5-99.1. Fitbit and actigraph differed significantly on recorded total sleep time and sleep efficiency between each other and polysomnography. Bland-Altman plots indicated that both Fitbit and actigraph overestimated sleep efficiency and total sleep time. Sensitivity of both Fitbit and actigraphy for accurately identifying sleep was high within all sleep stages and during arousals; specificity of both Fitbit and actigraph for accurately identifying wake was poor. Specificity of actigraph was higher except for wake before sleep onset; sensitivity of Fitbit was higher in all sleep stages and during arousals. CONCLUSIONS: The web-based Fitbit, available at a markedly reduced price and with several convenience factors compared to standard actigraphy, may be an acceptable activity measurement instrument for use with normative populations. However, Fitbit has the same specificity limitations as actigraphy; both devices consistently misidentify wake as sleep and thus overestimate both sleep time and quality. Use of the Fitbit will also require specific validation before it can be used to assess disordered populations and or different age groups.
Authors: Luciane de Souza; Ana Amélia Benedito-Silva; Maria Laura Nogueira Pires; Dalva Poyares; Sergio Tufik; Helena Maria Calil Journal: Sleep Date: 2003-02-01 Impact factor: 5.849
Authors: Ping-Ru T Ko; Julie A Kientz; Eun Kyoung Choe; Matthew Kay; Carol A Landis; Nathaniel F Watson Journal: J Clin Sleep Med Date: 2015-12-15 Impact factor: 4.062
Authors: Ruby Fore; Jaime E Hart; Christine Choirat; Jennifer W Thompson; Kathleen Lynch; Francine Laden; Jorge E Chavarro; Peter James Journal: Cancer Epidemiol Biomarkers Prev Date: 2020-02-25 Impact factor: 4.254
Authors: Massimiliano de Zambotti; Stephanie Claudatos; Sarah Inkelis; Ian M Colrain; Fiona C Baker Journal: Chronobiol Int Date: 2015 Impact factor: 2.877