ArticleNature and science of sleep2022
Multi-Night at-Home Evaluation of Improved Sleep Detection and Classification with a Memory-Enhanced Consumer Sleep Tracker.
Article in Nature and science of sleep, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Performance evaluation of finger-worn devices for sleep stage classification and sleep apnea detection: a systematic review and meta-analysis.Journal of translational medicine · 2026Pooled it
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- Sleep and temperature data from wearable devices support noninvasive detection of diabetes mellitus in a large-scale, retrospective analysis.Communications medicine · 2026Article
- Performance evaluation of consumer sleep-tracking wearables and nearables in healthy young and older adults.Sleep advances : a journal of the Sleep Research Society · 2026Article
- ReSTech project on Xiaomi wearable devices for monitoring and detecting obstructive sleep apnoea: observational study protocol.BMJ open · 2025Article
- The Impact of Domain Shift on Predicting Perceived Sleep Quality from Wearables.Sensors (Basel, Switzerland) · 2025Article
- Enhancing artificial intelligence-driven sleep apnea diagnosis: The critical importance of input signal proficiency with a focus on mandibular jaw movements.Journal of prosthodontics : official journal of the American College of Prosthodontists · 2025Article
- Validation of a Wireless, Self-Applied Device for Sleep Recording in the Paediatric Population.Nature and science of sleep · 2025Article
- Deriving Accurate Nocturnal Heart Rate, rMSSD and Frequency HRV from the Oura Ring.Sensors (Basel, Switzerland) · 2024Article
- Five million nights: temporal dynamics in human sleep phenotypes.NPJ digital medicine · 2024Article
- Noninvasive monitoring technologies to identify discomfort and distressing symptoms in persons with limited communication at the end of life: a scoping review.BMC palliative care · 2024Article
- Evaluating reliability in wearable devices for sleep staging.NPJ digital medicine · 2024Review
- Review
- The WE SENSE study protocol: A controlled, longitudinal clinical trial on the use of wearable sensors for early detection and tracking of viral respiratory tract infections.Contemporary clinical trials · 2023Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To evaluate the benefits of applying an improved sleep detection and staging algorithm on minimally processed multi-sensor wearable data collected from older generation hardware. Patients and Methods: 58 healthy, East Asian adults aged 23-69 years (M = 37.10, SD = 13.03, 32 males), each underwent 3 nights of PSG at home, wearing 2 Results: Gen 3 outperformed its predecessor with a mean (SD) accuracy of 92.6% (0.04), sensitivity of 94.9% (0.03), and specificity of 78.5% (0.11); corresponding to a 3%, 2.8% and 6.2% improvement from Gen2 across the three nights, with Cohen's d values >0.39, t values >2.69, and p values <0.01. Notably, Gen 3 showed robust performance comparable to PSG in its assessment of sleep latency, light sleep, rapid eye movement (REM), and wake after sleep onset (WASO) duration. Participants <40 years of age benefited more from the upgrade with less measurement bias for total sleep time (TST), WASO, light sleep and sleep efficiency compared to those ≥40 years. Males showed greater improvements on TST and REM sleep measurement bias compared to females, while females benefitted more for deep sleep measures compared to males. Conclusion: These results affirm the benefits of applying machine learning and a diverse training dataset to improve sleep measurement of a consumer wearable device. Importantly, collecting raw data with appropriate hardware allows for future advancements in algorithm development or sleep physiology to be retrospectively applied to enhance the value of longitudinal sleep studies.
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