Exploratory Validation of Sleep-Tracking Devices in Patients with Psychiatric Disorders

Masaya Ogasawara; Masahiro Takeshima; Shumpei Kosaka; Aya Imanishi; Yu Itoh; Dai Fujiwara; Kazuhisa Yoshizawa; Norio Ozaki; Kazuyuki Nakagome; Kazuo Mishima

doi:10.2147/NSS.S400944

Exploratory Validation of Sleep-Tracking Devices in Patients with Psychiatric Disorders

Nat Sci Sleep. 2023 Apr 24:15:301-312. doi: 10.2147/NSS.S400944. eCollection 2023.

Authors

Affiliations

¹ Department of Neuropsychiatry, Akita University Graduate School of Medicine, Akita, Japan.
² Department of Psychiatry, Akita Prefectural Center for Rehabilitation and Psychiatric Medicine, Daisen, Japan.
³ Department of Pathophysiology of Mental Disorders, Nagoya University Graduate School of Medicine, Nagoya, Japan.
⁴ Department of Psychiatry, National Center of Neurology and Psychiatry, Tokyo, Japan.

Abstract

Purpose: Sleep-tracking devices have performed well in recent studies that evaluated their use in healthy adults by comparing them with the gold standard sleep assessment technique, polysomnography (PSG). These devices have not been validated for use in patients with psychiatric disorders. Therefore, we tested the performance of three sleep-tracking devices against PSG in patients with psychiatric disorders.

Patients and methods: In total, 52 patients (32 women; 48.1 ± 17.2 years, mean ± SD; 18 patients diagnosed with schizophrenia, 19 with depressive disorder, 3 with bipolar disorder, and 12 with sleep disorder cases) were tested in a sleep laboratory with PSG, along with portable electroencephalography (EEG) device (Sleepgraph), actigraphy (MTN-220/221) and consumer sleep-tracking device (Fitbit Sense).

Results: Epoch-by-epoch sensitivity (for sleep) and specificity (for wake), respectively, were as follows: Sleepgraph (0.95, 0.76), Fitbit Sense (0.95, 0.45) and MTN-220/221 (0.93, 0.40). Portable EEG (Sleepgraph) had the best sleep stage-tracking performance. Sleep-wake summary metrics demonstrated lower performance on poor sleep (ice, shorter total sleep time, lower sleep efficiency, longer sleep latency, longer wake after sleep onset).

Conclusion: Devices demonstrated similar sleep-wake detecting performance as compared with previous studies that evaluated sleep in healthy adults. Consumer sleep device may exhibit poor sleep stage-tracking performance in patients with psychiatric disorders due to factors that affect the sleep determination algorithm, such as changes in autonomic nervous system activity. However, Sleepgraph, a portable EEG device, demonstrated higher performance in mental disorders than the Fitbit Sense and actigraphy.

Keywords: actigraphy; consumer sleep technologies; polysomnography; portable EEG; psychiatric patients.

Grants and funding

This research was supported by research grants from AMED (JP21dk0307103KM), the Japanese Ministry of Education, Science, and Technology (22H02992), and the National Center of Neurology and Psychiatry (2-1).