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Wearable Electronic Devices

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Future of service member monitoring: the intersection of biology, wearables and artificial intelligence.

BMJ military health
While substantial investment has been made in the early identification of mental and behavioural health disorders in service members, rates of depression, substance abuse and suicidality continue to climb. Objective and persistent measures are needed...

Inferring ECG Waveforms from PPG Signals with a Modified U-Net Neural Network.

Sensors (Basel, Switzerland)
There are two widely used methods to measure the cardiac cycle and obtain heart rate measurements: the electrocardiogram (ECG) and the photoplethysmogram (PPG). The sensors used in these methods have gained great popularity in wearable devices, which...

Improving Human Activity Recognition With Wearable Sensors Through BEE: Leveraging Early Exit and Gradient Boosting.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Early-exiting has recently provided an ideal solution for accelerating activity inference by attaching internal classifiers to deep neural networks. It allows easy activity samples to be predicted at shallower layers, without executing deeper layers,...

Development and Assessment of Artificial Intelligence-Empowered Gait Monitoring System Using Single Inertial Sensor.

Sensors (Basel, Switzerland)
Gait instability is critical in medicine and healthcare, as it has associations with balance disorder and physical impairment. With the development of sensor technology, despite the fact that numerous wearable gait detection and recognition systems h...

Deep-learning-assisted thermogalvanic hydrogel fiber sensor for self-powered in-nostril respiratory monitoring.

Journal of colloid and interface science
Direct and consistent monitoring of respiratory patterns is crucial for disease prognostication. Although the wired clinical respiratory monitoring apparatus can operate accurately, the existing defects are evident, such as the indispensability of an...

Ultrasensitive Flexible Strain Sensor Made with Carboxymethyl-Cellulose-Anchored Carbon Nanotubes/MXene for Machine-Learning-Assisted Handwriting Recognition.

ACS applied materials & interfaces
The combination of wearable sensors with machine learning enables intelligent perception in human-machine interaction and healthcare, but achieving high sensitivity and a wide working range in flexible strain sensors for signal acquisition and accura...

The Role of Deep Learning and Gait Analysis in Parkinson's Disease: A Systematic Review.

Sensors (Basel, Switzerland)
Parkinson's disease (PD) is the second most common movement disorder in the world. It is characterized by motor and non-motor symptoms that have a profound impact on the independence and quality of life of people affected by the disease, which increa...

Detection of Sleep Apnea Using Wearable AI: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Early detection of sleep apnea, the health condition where airflow either ceases or decreases episodically during sleep, is crucial to initiate timely interventions and avoid complications. Wearable artificial intelligence (AI), the integ...

A Pre-Voiding Alarm System Using Wearable Ultrasound and Machine Learning Algorithms for Children With Nocturnal Enuresis.

IEEE journal of translational engineering in health and medicine
Nocturnal enuresis is a bothersome condition that affects many children and their caregivers. Post-voiding systems is of little value in training a child into a correct voiding routing while existing pre-voiding systems suffer from several practical ...

Implementing Autonomous Control in the Digital-Twins-Based Internet of Robotic Things for Remote Patient Monitoring.

Sensors (Basel, Switzerland)
Conventional patient monitoring methods require skin-to-skin contact, continuous observation, and long working shifts, causing physical and mental stress for medical professionals. Remote patient monitoring (RPM) assists healthcare workers in monitor...