SOTAVerified

Sleep Quality

( Image credit: DeepSleep )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 61 papers

TitleStatusHype
PARIS: Personalized Activity Recommendation for Improving Sleep Quality—0
Personalised recommendations of sleep behaviour with neural networks using sleep diaries captured in Sleepio—0
Privacy Protected Contactless Cardio-respiratory Monitoring using Defocused Cameras during Sleep—0
Quantifying Itch and its Impact on Sleep Using Machine Learning and Radio Signals—0
Revealing the Self: Brainwave-Based Human Trait Identification—0
Robust Automated Human Activity Recognition and its Application to Sleep Research—0
SERF: Interpretable Sleep Staging using Embeddings, Rules, and Features—0
SleepGMUformer: A gated multimodal temporal neural network for sleep staging—0
Sleep Position Classification using Transfer Learning for Bed-based Pressure Sensors—0
Sleep quality, chronotype and social jet lag of adolescents from a population with a very late chronotype—0
Sleep Quality Prediction from Wearables using Convolution Neural Networks and Ensemble Learning—0
Sleep Stage Classification Using Bidirectional LSTM in Wearable Multi-sensor Systems—0
Supportive psychotherapy on insomnia induced by COVID-19; Evaluation of patients and hospital staff—0
1D Convolutional Neural Network Models for Sleep Arousal Detection—0
The Interplay Between Physical Activity, Protein Consumption, and Sleep Quality in Muscle Protein Synthesis—0
Toward estimating personal well-being using voice—0
Towards a Personal Health Large Language Model—0
Toward Sensor-based Sleep Monitoring with Electrodermal Activity Measures—0
Towards Infant Sleep-Optimized Driving: Synergizing Wearable and Vehicle Sensing in Intelligent Cruise Control—0
The Dreem Headband as an Alternative to Polysomnography for EEG Signal Acquisition and Sleep Staging—0
A deep learning-enabled smart garment for accurate and versatile sleep conditions monitoring in daily life—0
A Closed-loop Sleep Modulation System with FPGA-Accelerated Deep Learning—0
Actigraphy-based Sleep/Wake Pattern Detection using Convolutional Neural Networks—0
Transparency in Sleep Staging: Deep Learning Method for EEG Sleep Stage Classification with Model Interpretability—0
A machine-learning sleep-wake classification model using a reduced number of features derived from photoplethysmography and activity signals—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Random ForestAccuracy75—Unverified