Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …
application areas. Since multi-sensor is defined by the presence of more than one model or …
Automated sleep apnea detection in raw respiratory signals using long short-term memory neural networks
T Van Steenkiste, W Groenendaal… - IEEE journal of …, 2018 - ieeexplore.ieee.org
Sleep apnea is one of the most common sleep disorders and the consequences of
undiagnosed sleep apnea can be very severe, ranging from increased blood pressure to …
undiagnosed sleep apnea can be very severe, ranging from increased blood pressure to …
Automatic detection of obstructive sleep apnea using wavelet transform and entropy-based features from single-lead ECG signal
Obstructive sleep apnea (OSA) is a prevalent sleep disorder and highly affects the quality of
human life. Currently, gold standard for OSA detection is polysomnogram. Since this method …
human life. Currently, gold standard for OSA detection is polysomnogram. Since this method …
Automatic classification of apnea and normal subjects using new features extracted from HRV and ECG-derived respiration signals
A novel framework for automatic detection of obstructive sleep apnea (OSA) is introduced in
which a symbolic dynamics method, alphabet entropy, along with other well-known features …
which a symbolic dynamics method, alphabet entropy, along with other well-known features …
Automated detection of sleep apnea using sparse residual entropy features with various dictionaries extracted from heart rate and EDR signals
CSSS Viswabhargav, RK Tripathy… - Computers in biology and …, 2019 - Elsevier
Sleep is a prominent physiological activity in our daily life. Sleep apnea is the category of
sleep disorder during which the breathing of the person diminishes causing the alternation …
sleep disorder during which the breathing of the person diminishes causing the alternation …
Snore-GANs: Improving automatic snore sound classification with synthesized data
One of the frontier issues that severely hamper the development of automatic snore sound
classification (ASSC) associates to the lack of sufficient supervised training data. To cope …
classification (ASSC) associates to the lack of sufficient supervised training data. To cope …
Sleep apnea detection based on rician modeling of feature variation in multiband EEG signal
A Bhattacharjee, S Saha, SA Fattah… - IEEE journal of …, 2018 - ieeexplore.ieee.org
Sleep apnea, a serious sleep disorder affecting a large population, causes disruptions in
breathing during sleep. In this paper, an automatic apnea detection scheme is proposed …
breathing during sleep. In this paper, an automatic apnea detection scheme is proposed …
Automated sleep apnea detection from cardio-pulmonary signal using bivariate fast and adaptive EMD coupled with cross time–frequency analysis
Sleep apnea is a sleep related pathology in which breathing or respiratory activity of an
individual is obstructed, resulting in variations in the cardio-pulmonary (CP) activity. The …
individual is obstructed, resulting in variations in the cardio-pulmonary (CP) activity. The …
[HTML][HTML] Classification and detection of breathing patterns with wearable sensors and deep learning
K McClure, B Erdreich, JHT Bates, RS McGinnis… - Sensors, 2020 - mdpi.com
Rapid assessment of breathing patterns is important for several emergency medical
situations. In this research, we developed a non-invasive breathing analysis system that …
situations. In this research, we developed a non-invasive breathing analysis system that …
Obstructive sleep apnea detection scheme based on manually generated features and parallel heterogeneous deep learning model under IoMT
Obstructive sleep apnea (OSA) syndrome is a common sleep disorder and a key cause of
cardiovascular and cerebrovascular diseases that seriously affect the lives and health of …
cardiovascular and cerebrovascular diseases that seriously affect the lives and health of …