ReviewSensors (Basel, Switzerland)2021
Deconstructing Commercial Wearable Technology: Contributions toward Accurate and Free-Living Monitoring of Sleep.
Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed.
- Comparing sleep measures in cancer survivors: self-reported sleep diary versus objective wearable sleep tracker.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Trial
- Integrating Wearable Temperature, Activity, Melanopic Light, and Lifelog Data to Assess Circadian-Behavioral Coupling in Free-Living Conditions.Sensors (Basel, Switzerland) · 2026Article
- Guidelines for rigor and reproducibility of heart rate variability within human cardiovascular research.American journal of physiology. Heart and circulatory physiology · 2026Review
- Wearable Devices and Machine Learning in Cardiovascular Monitoring: Current Evidence and Future Directions for Precision Medicine.Journal of personalized medicine · 2026Review
- Artificial intelligence in biology and medicine.Die Naturwissenschaften · 2025Review
- 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
- On-the-Fly Sleep Scoring Algorithm with Heart Rate, RR Intervals and Accelerometer as Input.Sensors (Basel, Switzerland) · 2025Article
- A Comprehensive Review of Home Sleep Monitoring Technologies: Smartphone Apps, Smartwatches, and Smart Mattresses.Sensors (Basel, Switzerland) · 2025Review
- A guide to consumer-grade wearables in cardiovascular clinical care and population health for non-experts.NPJ cardiovascular health · 2025Review
- Performance Evaluation of a New Sport Watch in Sleep Tracking: A Comparison against Overnight Polysomnography in Young Adults.Sensors (Basel, Switzerland) · 2024Article
- Relevance of sleep for wellness: New trends in using artificial intelligence and machine learning.World journal of clinical cases · 2024Article
- From Pulses to Sleep Stages: Towards Optimized Sleep Classification Using Heart-Rate Variability.Sensors (Basel, Switzerland) · 2023Article
- Comparing sleep measures in cancer survivors: Self-reported sleep diary versus objective wearable sleep tracker.Research square · 2023Article
- Wearables in Cardiovascular Disease.Journal of cardiovascular translational research · 2023Review
- Digital health in chronic obstructive pulmonary disease.Chronic diseases and translational medicine · 2023Review
- Stellate Ganglion Block Improves Postoperative Sleep Quality and Analgesia in Patients with Breast Cancer: A Randomized Controlled Trial.Pain and therapy · 2023Article
- Applications of Smart Material Sensors and Soft Electronics in Healthcare Wearables for Better User Compliance.Micromachines · 2022Review
- Smart Consumer Wearables as Digital Diagnostic Tools: A Review.Diagnostics (Basel, Switzerland) · 2022Review
- Full-Body Photobiomodulation Therapy Is Associated with Reduced Sleep Durations and Augmented Cardiorespiratory Indicators of Recovery.Sports (Basel, Switzerland) · 2022Article
- Burnout and Cardiovascular Risk in Healthcare Professionals During the COVID-19 Pandemic.Frontiers in psychiatry · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite prolific demands and sales, commercial sleep assessment is primarily limited by the inability to "measure" sleep itself; rather, secondary physiological signals are captured, combined, and subsequently classified as sleep or a specific sleep state. Using markedly different approaches compared with gold-standard polysomnography, wearable companies purporting to measure sleep have rapidly developed during recent decades. These devices are advertised to monitor sleep via sensors such as accelerometers, electrocardiography, photoplethysmography, and temperature, alone or in combination, to estimate sleep stage based upon physiological patterns. However, without regulatory oversight, this market has historically manufactured products of poor accuracy, and rarely with third-party validation. Specifically, these devices vary in their capacities to capture a signal of interest, process the signal, perform physiological calculations, and ultimately classify a state (sleep vs. wake) or sleep stage during a given time domain. Device performance depends largely on success in all the aforementioned requirements. Thus, this review provides context surrounding the complex hardware and software developed by wearable device companies in their attempts to estimate sleep-related phenomena, and outlines considerations and contributing factors for overall device success.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.