[HTML][HTML] A systematic review of sensing technologies for wearable sleep staging
SA Imtiaz - Sensors, 2021 - mdpi.com
Designing wearable systems for sleep detection and staging is extremely challenging due to
the numerous constraints associated with sensing, usability, accuracy, and regulatory …
the numerous constraints associated with sensing, usability, accuracy, and regulatory …
Automatic sleep stage classification: From classical machine learning methods to deep learning
RN Sekkal, F Bereksi-Reguig… - … Signal Processing and …, 2022 - Elsevier
Background and objectives The classification of sleep stages is a preliminary exam that
contributes to the diagnosis of possible sleep disorders. However, it is a tedious and time …
contributes to the diagnosis of possible sleep disorders. However, it is a tedious and time …
At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch
Obstructive sleep apnea (OSA) affects more than 900 million adults globally and can create
serious health complications when untreated; however, 80% of cases remain undiagnosed …
serious health complications when untreated; however, 80% of cases remain undiagnosed …
[HTML][HTML] Relationship between major depression symptom severity and sleep collected using a wristband wearable device: multicenter longitudinal observational …
Background Sleep problems tend to vary according to the course of the disorder in
individuals with mental health problems. Research in mental health has associated sleep …
individuals with mental health problems. Research in mental health has associated sleep …
A novel pedal musculoskeletal response based on differential spatio-temporal LSTM for human activity recognition
Human activity recognition (HAR) with wearable devices has shown superior usability in
everyday life tracking and healthcare monitoring in recent years. To solve the existing …
everyday life tracking and healthcare monitoring in recent years. To solve the existing …
[HTML][HTML] Sleep classification using Consumer Sleep Technologies and AI: A review of the current landscape
Classifying sleep stages in real-time represents considerable potential, for instance in
enabling interactive noise masking in noisy environments when persons are in a state of …
enabling interactive noise masking in noisy environments when persons are in a state of …
Transferable self-supervised instance learning for sleep recognition
Although the importance of sleep is increasingly recognized, the lack of general and
transferable algorithms hinders scalable sleep assessment in healthy persons and those …
transferable algorithms hinders scalable sleep assessment in healthy persons and those …
[HTML][HTML] Lower limb kinematics trajectory prediction using long short-term memory neural networks
This study determined whether the kinematics of lower limb trajectories during walking could
be extrapolated using long short-term memory (LSTM) neural networks. It was hypothesised …
be extrapolated using long short-term memory (LSTM) neural networks. It was hypothesised …
Non-invasive techniques for monitoring different aspects of sleep: A comprehensive review
Quality sleep is very important for a healthy life. Nowadays, many people around the world
are not getting enough sleep, which has negative impacts on their lifestyles. Studies are …
are not getting enough sleep, which has negative impacts on their lifestyles. Studies are …
[HTML][HTML] An automated wavelet-based sleep scoring model using EEG, EMG, and EOG signals with more than 8000 subjects
Human life necessitates high-quality sleep. However, humans suffer from a lower quality of
life because of sleep disorders. The identification of sleep stages is necessary to predict the …
life because of sleep disorders. The identification of sleep stages is necessary to predict the …