Co-production in sleep and circadian research: a scoping review of current practices and future directions DOI Creative Commons
Emma Louise Gale, Raahat Manrai, Lorna Caddick

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 3, 2024

Abstract Introduction: Sleep is essential for mental and physical health research in the field has substantially expanded over past fifty years. Co-production methodology been increasingly used within social care refers to collaboration between researchers, policy makers, community partners wider stakeholders. The aim of this scoping review was detail use co-production methods sleep research. Methods: A existing literature conducted using seven databases following PRISMA-ScR guidelines. Search terms included objective subjective outcomes, methodologies. Results: Sixteen studies were final review: ten solely qualitative inform intervention design development (sleep as a primary outcome (n=5) secondary (n=5)) six methodologies establish priority future Most consultation approaches interventions (n=8), instead co-design teams (n=2). Two focusing on recruited participants from clinical populations with poor sleep, other those underlying conditions or healthy population. Discussion: The most common limitations small sample size, researcher driven topics/domains PAR components, under-representative samples COVID-19 pressures. Future should consider study conceptualisation, through design, implementation further benefit intended

Language: Английский

Objective sleep monitoring at home in older adults: A scoping review DOI Creative Commons
Sarah Nauman Ghazi, Anders Behrens, Jessica Berner

et al.

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

Citations

5
Promoting vocabulary learning during sleep at home using closed‐loop targeted memory reactivation DOI Creative Commons
Federico Salfi, Aurora D’Atri,

Benedetto Arnone

et al.

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

Published: Feb. 10, 2025

Targeted memory reactivation represents an established technique for promoting sleep-dependent consolidation in laboratory studies. This investigation aimed to test the potentiality of a wearable electroencephalography-based closed-loop targeted system boost vocabulary learning home settings. In evening, 24 adults (23.58 years ± 3.36 years, 19 females) were asked learn Italian translation 40 pseudowords (test session). Subsequently, participants slept at their wearing electroencephalography headband (Dreem 2), and half acoustically re-presented (cued) following real-time detection slow waves. After awakening, recall translations was retested. The stimulation effect evaluated by comparing test-retest variations accuracy between cued uncued pseudowords. Moreover, we assessed event-related potentials spectral perturbations induced stimuli during sleep, electrophysiological correlates correctly translated with incorrectly ones retest session. Closed-loop increased (+8.6%), while no significant variation items observed (-4.6%). Time-frequency analysis indicated power increase spindle frequency band coinciding second positive peak sound-elicited wave as correlate successful morning recall. study extended effectiveness enhancing ecological environment, providing further support role activity effect. A could represent memory-enhancement tool real-world settings hallmark sleep electroencephalographic rhythms consolidation.

Language: Английский

Citations

0
Co‐production in sleep research: A scoping review of current practices and future directions DOI Creative Commons
Emma Louise Gale, Raahat Manrai, Lorna Caddick

et al.

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

Published: Feb. 9, 2025

Sleep is essential for mental and physical health, research in the field has substantially expanded over past 50 years. Co-production methodology been increasingly used within health social care research, refers to collaboration between researchers, policy makers, community partners wider stakeholders. The aim of this scoping review was detail use co-production methods sleep research. A existing literature conducted using seven databases following PRISMA-ScR guidelines. Search terms included objective subjective outcomes, methodologies. Sixteen studies were final review: 10 solely qualitative inform intervention design development (sleep as a primary outcome [n = 5] secondary 5]), six methodologies establish priority future Most consultation approaches interventions (n 8), instead co-design teams 2). Two focusing on recruiting participants from clinical populations with poor sleep, other recruited those underlying conditions or healthy population. most common limitations small sample size, researcher driven topics/domains PAR components, under-representative samples COVID-19 pressures. Future should consider study conceptualisation, through design, implementation further benefit intended

Language: Английский

Citations

0
The utility of wearable devices in the perioperative period DOI
Alexander Xiang,

J. F. Hu,

Karim S. Ladha

et al.

Current Opinion in Anaesthesiology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 12, 2025

Purpose of review Improved perioperative patient monitoring is a crucial step toward better predicting postoperative outcomes. Wearable devices capable measuring various health-related metrics represent novel tool that can assist healthcare providers. However, the literature surrounding wearables wide-ranging, preventing clinicians from drawing definitive conclusions regarding their utility. This intends to consolidate recent on and summarize most salient information. Recent findings cardiac output colonic motility have recently been piloted with mixed results. Novel measurement techniques for established also studied, including photoplethysmography heart rate blood pressure along resistance thermometers temperature. Nuanced methods synthesizing data piloted, machine-learning algorithms adverse events trajectory curves count progression. are generally well accepted, although adjuvant support systems improved satisfaction. Summary Perioperative valuable tools tracking health metrics, events, improving Future research removing barriers such as technological illiteracy, artifact generation, false-positive alarms would enable integration into hospital setting.

Language: Английский

Citations

0
Stretchable Clutter-Free E-Textile EEG Cap: Advancing Seamless Wearable Solutions for Emerging Neuroimaging Applications DOI

Kourosh Motiepor,

Simin Bakhtiyari,

Amir Jahanshahi

et al.

Sensors and Actuators A Physical, Journal Year: 2025, Volume and Issue: unknown, P. 116454 - 116454

Published: March 1, 2025

Language: Английский

Citations

0
Automated Sleep Staging in Epilepsy Using Deep Learning on Standard Electroencephalogram and Wearable Data DOI Creative Commons
Jaiver Macea, Elisabeth R. M. Heremans, Renée Proost

et al.

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

Published: April 3, 2025

Automated sleep staging on wearable data could improve our understanding and management of epilepsy. This study evaluated scoring by a deep learning model 223 night-sleep recordings from 50 patients measured in the hospital with an electroencephalogram (EEG) device. The scored stage every 30-s epoch EEG data, we compared output clinical expert 20 nights, each for different patient. Bland-Altman analysis examined differences automated both modalities, using mixed-effect models, explored between without seizures. Overall, found moderate accuracy Cohen's kappa standard (0.73 0.59) (0.61 0.43) versus expert. F1 scores also varied modalities. sensitivity was very low N1. Moreover, underestimated duration most macrostructure parameters except N2. On other hand, seizures during admission slept more night (6.37, 95% confidence interval [CI] 5.86-7.87) (5.68, CI 5.24-6.13), p = 0.001, but spent time In conclusion, accelerometry monitor epilepsy, approach can help automate analysis. However, further steps are essential to performance before implementation. Trial Registration: SeizeIT2 trial registered clinicaltrials.gov, NCT04284072.

Language: Английский

Citations

0
Scorerem: A User-Friendly Matlab-Gui for Rapid Eye Movement (Rem) Sleep Microstructure (Phasic/Tonic) Annotation and Quantification DOI
Kiran K G Ravindran, Derk‐Jan Dijk

Published: Jan. 1, 2024

Language: Английский

Citations

1
Recent Evidence of Non-Rapid Eye Movement Sleep Oscillation Abnormalities in Psychiatric Disorders DOI
Ahmad Mayeli,

Claudio Sanguineti,

Fabio Ferrarelli

et al.

Current Psychiatry Reports, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 14, 2024

Language: Английский

Citations

1
Sleep disorders in children: classification, evaluation, and management. A review DOI
Reinoud J. B. J. Gemke, P. C. Burger, Lindsay M. H. Steur

et al.

European Journal of Pediatrics, Journal Year: 2024, Volume and Issue: 184(1)

Published: Nov. 23, 2024

Language: Английский

Citations

1
Automatic sleep scoring for real-time monitoring and stimulation in individuals with and without sleep apnea DOI Creative Commons
Martín Esparza-Iaizzo,

María Sierra-Torralba,

Jens G. Klinzing

et al.

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

Published: June 13, 2024

Digital therapeutics, enabled by advanced machine learning algorithms and medical wearable devices, offer a promising approach to streamline diagnostics improve access healthcare. Within this framework, automatic sleep scoring can provide accurate efficient analysis from electrophysiological signals recorded with sensors, such as electroencephalography (EEG). However, the optimal configuration temporal dynamics of systems remain unclear, especially concerning their performance across different population samples. This study systematically investigates impact electrode setup, scope, characteristics on algorithms. Utilizing convolutional neural network (CNN) model, we analyzed various configurations using datasets comprising both healthy participants individuals apnea. Our findings reveal that based single frontal EEG channel demonstrates reliable congruency human expert scorers, minimal improvement observed additional sensors. Moreover, demonstrate real-time be achieved comparable accuracy offline methods, which rely past future information classify window interest. Remarkably, notable reduction in decoding is for disorders compared participants, highlighting challenges inherent accurately assessing stages clinical populations. solutions hold promise facilitating timely diagnoses personalized treatment plans, applications extending beyond include closed-loop neurostimulation interventions. valuable insights into complexities considerations development effective assessment tools research settings.

Language: Английский

Citations

0