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Volume 15 No. 07
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Accepted Papers





Emerging Technologies

Sleep Validity of a Non-Contact Bedside Movement and Respiration-Sensing Device

Margeaux M. Schade, PhD1,2; Christopher E. Bauer, PhD1,3; Billie R. Murray, BS1; Luke Gahan, MEng4; Emer P. Doheny, PhD4; Hannah Kilroy, MAI4; Alberto Zaffaroni, MEng4; Hawley E. Montgomery-Downs, PhD1
1Department of Psychology, West Virginia University, Morgantown, West Virginia; 2Department of Biobehavioral Health, Pennsylvania State University, State College, Pennsylvania; 3Department of Neuroscience, University of Kentucky, Lexington, Kentucky; 4ResMed Sensor Technologies Ltd., Dublin, Ireland

Study Objectives:

To assess the sleep detection and staging validity of a non-contact, commercially available bedside bio-motion sensing device (S+, ResMed) and evaluate the impact of algorithm updates.

Methods:

Polysomnography data from 27 healthy adult participants was compared epoch-by-epoch to synchronized data that were recorded and staged by actigraphy and S+. An update to the S+ algorithm (common in the rapidly evolving commercial sleep tracker industry) permitted comparison of the original (S+V1) and updated (S+V2) versions.

Results:

Sleep detection accuracy by S+V1 (93.3%), S+V2 (93.8%), and actigraphy (96.0%) was high; wake detection accuracy by each (69.6%, 73.1%, and 47.9%, respectively) was low. Higher overall S+ specificity, compared to actigraphy, was driven by higher accuracy in detecting wake before sleep onset (WBSO), which differed between S+V2 (90.4%) and actigraphy (46.5%). Stage detection accuracy by the S+ did not exceed 67.6% (for stage N2 sleep, by S+V2) for any stage. Performance is compared to previously established variance in polysomnography scored by humans: a performance standard which commercial devices should ideally strive to reach.

Conclusions:

Similar limitations in detecting wake after sleep onset (WASO) were found for the S+ as have been previously reported for actigraphy and other commercial sleep tracking devices. S+ WBSO detection was higher than actigraphy, and S+V2 algorithm further improved WASO accuracy. Researchers and clinicians should remain aware of the potential for algorithm updates to impact validity.

Commentary:

A commentary on this article appears in this issue on page 935.

Citation:

Schade MM, Bauer CE, Murray BR, Gahan L, Doheny EP, Kilroy H, Zaffaroni A, Montgomery-Downs HE. Sleep validity of a non-contact bedside movement and respiration-sensing device. J Clin Sleep Med. 2019;15(7):1051–1061.


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