Performance evaluation of an under‐mattress sleep sensor versus polysomnography in > 400 nights with healthy and unhealthy sleep

Journal of Sleep Research, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 28, 2025

Consumer sleep trackers provide useful insight into sleep. However, large-scale performance evaluation studies are needed to properly understand tracker accuracy. This study evaluated of an under-mattress sensor estimate and wake versus polysomnography in a large sample, including individuals with without disorders during day night opportunities, across multiple in-laboratory studies. One-hundred eighty-three participants (51%/49% male/female, mean [SD] age = 45 [18] years) attended the laboratory for research simultaneous (Withings Sleep Analyser) recordings. Epoch-by-epoch analyses determined accuracy, sensitivity specificity Withings Analyser polysomnography. Bland-Altman plots examined bias duration, efficiency, onset-latency, after onset. Overall sleep-wake classification accuracy was 83%, 95% 37%. The significantly overestimated total time (48 [81] min), efficiency (9 [15]%) sleep-onset latency (6 [26] underestimated onset (54 [78] min). Accuracy were higher daytime opportunities healthy (89% 47% 82% 26%, respectively, p < 0.05). also 97%) those (81% 91%, is comparable other consumer trackers, high but poor compared reasonably stable, more variable people disorder. Contactless, sensors show promise accurate monitoring, noting tendency over-estimate particularly where high.

Language: Английский

---

Diagnostic Modalities in Sleep Disordered Breathing: Current and Emerging Technology and Its Potential to Transform Diagnostics

Respirology, Journal Year: 2025, Volume and Issue: unknown

Published: March 3, 2025

ABSTRACT Underpinned by rigorous clinical trial data, the use of existing home sleep apnoea testing is now commonly employed for disordered breathing diagnostics in most centres globally. This has been a welcome addition field given considerable burden disease, cost, and access limitations with in‐laboratory polysomnography testing. However, approaches predominantly aim to replicate elements conventional different forms focus on estimation apnoea‐hypopnoea index. New, simplified technology screening, detection/diagnosis, or monitoring expanded exponentially recent years. Emerging innovations go beyond simple single‐night replication varying numbers signals setting. These novel have potential provide important new insights overcome many transform disease diagnosis management improve outcomes patients. Accordingly, current review summarises evidence study people suspected sleep‐related disorders, discusses emerging technologies according three key categories: (1) wearables (e.g., body‐worn sensors including wrist finger sensors), (2) nearables bed‐embedded bedside (3) airables audio video recordings), outlines their disruptive role care.

Language: Английский

---

A Comparative Study of Polysomnography‐Derived Sleep Disturbance in People Living With Multiple Sclerosis Compared to Matched Controls From the General Population

Journal of Sleep Research, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

ABSTRACT Sleep structure and sleep disorders were compared between people with multiple sclerosis (MS; n = 39) age, sex, BMI‐matched members of the general population ( using overnight polysomnography (PSG). Compared to controls, MS had a higher prevalence periodic limb movement disorder (PLMD; 59% vs. 18%, p < 0.001) PLM‐related arousals (PLMI: 21.1 0.8, 0.001); as well longer duration (402.9 [59.8] 370.4 [54.0] min, 0.014), median latency (12.4 min) reduced proportion total time in stage N1 (8.5% 14.8%, more N2 (54.4% 48.0%, 0.001). architecture appeared differ for MS, even context no recent exacerbations or relapse. Managing leg movements during may help improve quality MS.

Language: Английский

---

Objective sleep monitoring at home in older adults: A scoping review

Journal of Sleep Research, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 9, 2024

Summary Inadequate sleep in older adults is linked to health issues such as frailty, cognitive impairment and cardiovascular disorders. Maintaining regular patterns important for healthy aging, making effective monitoring essential. While polysomnography the gold‐standard diagnosing disorders, its use home settings limited. Alternative objective methods can offer insights into natural factors affecting them without limitations of polysomnography. This scoping review aims examine current technologies, sensors parameters used home‐based adults. It also explore various predictors outcomes associated with understand at home. We identified 54 relevant articles using PubMed, Scopus, Web Science an AI tool (Research Rabbit), 48 studies wearable technologies eight non‐wearable technologies. Further, six types were utilized. The most common technology employed was actigraphy wearables, while ballistocardiography electroencephalography less common. frequent measured total time, wakeup after onset efficiency, only evaluating architecture terms stages. Additionally, categories analysed, including Health‐related, Environmental, Interventional, Behavioural, Time Place, Social associations. These associations correlate include in‐bed behaviours, exterior housing conditions, aerobic exercise, living place, relationship status, seasonal thermal environments.

Language: Английский

---

Development and Validation of Machine Learning Models to Predict Postoperative Delirium Using Clinical Features and Polysomnography Variables

Journal of Clinical Medicine, Journal Year: 2024, Volume and Issue: 13(18), P. 5485 - 5485

Published: Sept. 16, 2024

Background: Delirium affects up to 50% of patients following high-risk surgeries and is associated with poor long-term prognosis. This study employed machine learning predict delirium using polysomnography (PSG) sleep-disorder questionnaire data, aimed identify key sleep-related factors for improved interventions patient outcomes. Methods: We studied 912 adults who underwent surgery under general anesthesia at a tertiary hospital (2013–2024) had PSG within 5 years surgery. was assessed via clinical diagnoses, antipsychotic prescriptions, psychiatric consultations 14 days postoperatively. Sleep-related data were collected questionnaires. Machine predictions performed postoperative delirium, focusing on model accuracy feature importance. Results: divided the into an internal training set (700) external test (212). Univariate analysis identified significant risk factors: midazolam use, prolonged duration, hypoalbuminemia. variables such as fewer rapid eye movement (REM) episodes higher daytime sleepiness also linked delirium. An extreme gradient-boosting-based classification task achieved AUC 0.81 variables, 0.60 alone, 0.84 both, demonstrating added value data. Analysis Shapley additive explanations values highlighted important predictors: age, PSG-derived oxygen saturation nadir, periodic limb index, REM episodes, relationship between sleep patterns Conclusions: The artificial intelligence integrates reliably identifies that contribute its identification. Predicting high developing closely monitoring them could reduce costs complications

Language: Английский

---

A ballistocardiogram dataset with reference sensor signals in long-term natural sleep environments

Scientific Data, Journal Year: 2024, Volume and Issue: 11(1)

Published: Oct. 5, 2024

To facilitate unobtrusive and continuous sleep monitoring promote intelligent quality assessment, we present a dataset that includes multiple nights of ballistocardiogram (BCG) data collected using piezoelectric film sensors from 32 subjects in their regular environments. Besides, the referenced heart rate respiratory are also recorded by reference to validate accuracy cardiac components extracted BCG signals. The serves as foundation for research on vital sign based signals, offering support evaluation optimization quality.

Language: Английский

---

CNN-SENet: A Convolutional Neural Network Model for Audio Snoring Detection Based on Channel Attention Mechanism

Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 24 - 35

Published: Jan. 1, 2024

Language: Английский

---

Mandibular device treatment in obstructive sleep apnea -A structured therapy adjustment considering night-to-night variability night-to-night variability in mandibular devices

Sleep And Breathing, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 6, 2024

Language: Английский

---

Performance evaluation of an under-mattress sleep sensor versus polysomnography in >400 nights with healthy and unhealthy sleep

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 11, 2024

Abstract Consumer sleep trackers can provide useful insight into and patterns. However, large scale performance evaluation studies against direct measures are needed to comprehensively understand tracker accuracy. This study evaluated of an under-mattress sensor estimate wake versus polysomnography, during multiple in-laboratory protocols in a sample including individuals with without disorders day night opportunities. 183 participants (51% male, mean[SD] age=45[18] years) attended the laboratory for research that included simultaneous polysomnography (Withings Sleep Analyzer [WSA]) recordings. Epoch-by-epoch analyses confusion matrices were used determine accuracy, sensitivity, specificity WSA polysomnography. Bland-Altman plots examined bias duration, efficiency, onset-latency, after onset. Overall sleep-wake classification accuracy was 83%, sensitivity 95%, 37%. The significantly overestimated total time (48[81]minutes), efficiency (9[15]%), onset latency (6[26]), underestimated (54[78]), p<0.05. Accuracy higher daytime opportunities healthy (89% 47% 82% 26% respectively, p<0.05). also 97%) those (81% 91%, is comparable other consumer trackers, high but poor compared Poorer night-time likely due increased reduced efficiency. Contactless, sensors show promise accurate monitoring, noting tendency over-estimate particularly where high.

Language: Английский

---

Utility of wearable devices

The American Journal of Medicine, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 1, 2024

Language: Английский

---