Machine learning for microcontroller-class hardware: A review
The advancements in machine learning (ML) opened a new opportunity to bring intelligence
to the low-end Internet-of-Things (IoT) nodes, such as microcontrollers. Conventional ML …
to the low-end Internet-of-Things (IoT) nodes, such as microcontrollers. Conventional ML …
Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works
Apnea is a sleep disorder that stops or reduces airflow for a short time during sleep. Sleep
apnea may last for a few seconds and happen for many while slee**. This reduction in …
apnea may last for a few seconds and happen for many while slee**. This reduction in …
Phinets: A scalable backbone for low-power ai at the edge
In the Internet of Things era, where we see many interconnected and heterogeneous mobile
and fixed smart devices, distributing the intelligence from the cloud to the edge has become …
and fixed smart devices, distributing the intelligence from the cloud to the edge has become …
Multistage pruning of CNN based ECG classifiers for edge devices
Using smart wearable devices to monitor patients' electrocardiogram (ECG) for real-time
detection of arrhythmias can significantly improve healthcare outcomes. Convolutional …
detection of arrhythmias can significantly improve healthcare outcomes. Convolutional …
MPCNN: A Novel Matrix Profile Approach for CNN-based Single Lead Sleep Apnea In Classification Problem
Sleep apnea (SA) is a significant respiratory condition that poses a major global health
challenge. Deep Learning (DL) has emerged as an efficient tool for the classification …
challenge. Deep Learning (DL) has emerged as an efficient tool for the classification …
A spatio-temporal learning-based model for sleep apnea detection using single-lead ECG signals
J Chen, M Shen, W Ma, W Zheng - Frontiers in Neuroscience, 2022 - frontiersin.org
Sleep apnea (SA) is a common chronic sleep breathing disorder, which would cause stroke,
cognitive decline, cardiovascular disease, or even death. The SA symptoms often manifest …
cognitive decline, cardiovascular disease, or even death. The SA symptoms often manifest …
Wearables-assisted smart health monitoring for sleep quality prediction using optimal deep learning
Wearable devices such as smartwatches, wristbands, and GPS shoes are commonly
employed for fitness and wellness as they enable people to observe their day-to-day health …
employed for fitness and wellness as they enable people to observe their day-to-day health …
Multimodal multiresolution data fusion using convolutional neural networks for IoT wearable sensing
With advances in circuit design and sensing technology, the acquisition of data from a large
number of Internet of Things (IoT) sensors simultaneously to enable more accurate …
number of Internet of Things (IoT) sensors simultaneously to enable more accurate …
SomnNET: An SpO2 based deep learning network for sleep apnea detection in smartwatches
The abnormal pause or rate reduction in breathing is known as the sleep-apnea hypopnea
syndrome and affects the quality of sleep of an individual. A novel method for the detection …
syndrome and affects the quality of sleep of an individual. A novel method for the detection …
ViTDFNN: A Vision Transformer Enabled Deep Fuzzy Neural Network for Detecting Sleep Apnea-Hypopnea Syndrome in the Internet of Medical Things
N Ying, H Li, Z Zhang, Y Zhou, H Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Sleep apnea-hypopnea syndrome (SAHS) seriously affects human sleep, so it is necessary
to find the disease as early as possible. However, most of traditional models use …
to find the disease as early as possible. However, most of traditional models use …