AI Medical Compendium Topic:
Wearable Electronic Devices

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Bicycling Phase Recognition for Lower Limb Amputees Using Support Vector Machine Optimized by Particle Swarm Optimization.

Sensors (Basel, Switzerland)
A novel method for recognizing the phases in bicycling of lower limb amputees using support vector machine (SVM) optimized by particle swarm optimization (PSO) is proposed in this paper. The method is essential for enhanced prosthetic knee joint cont...

Classification and Detection of Breathing Patterns with Wearable Sensors and Deep Learning.

Sensors (Basel, Switzerland)
Rapid assessment of breathing patterns is important for several emergency medical situations. In this research, we developed a non-invasive breathing analysis system that automatically detects different types of breathing patterns of clinical signifi...

Ultra-sensitive and resilient compliant strain gauges for soft machines.

Nature
Soft machines are a promising design paradigm for human-centric devices and systems required to interact gently with their environment. To enable soft machines to respond intelligently to their surroundings, compliant sensory feedback mechanisms are ...

Classification of Aggressive Movements Using Smartwatches.

Sensors (Basel, Switzerland)
Recognizing aggressive movements is a challenging task in human activity recognition. Wearable smartwatch technology with machine learning may be a viable approach for human aggressive behavior classification. This research identified a viable classi...

Estimation of Three-Dimensional Lower Limb Kinetics Data during Walking Using Machine Learning from a Single IMU Attached to the Sacrum.

Sensors (Basel, Switzerland)
Kinetics data such as ground reaction forces (GRFs) are commonly used as indicators for rehabilitation and sports performance; however, they are difficult to measure with convenient wearable devices. Therefore, researchers have attempted to estimate ...

Deep learning with wearable based heart rate variability for prediction of mental and general health.

Journal of biomedical informatics
The ubiquity and commoditisation of wearable biosensors (fitness bands) has led to a deluge of personal healthcare data, but with limited analytics typically fed back to the user. The feasibility of feeding back more complex, seemingly unrelated meas...

Acceleration Magnitude at Impact Following Loss of Balance Can Be Estimated Using Deep Learning Model.

Sensors (Basel, Switzerland)
Pre-impact fall detection can detect a fall before a body segment hits the ground. When it is integrated with a protective system, it can directly prevent an injury due to hitting the ground. An impact acceleration peak magnitude is one of key measur...

Lower body kinematics estimation from wearable sensors for walking and running: A deep learning approach.

Gait & posture
BACKGROUND: Inertial measurement units (IMUs) are promising tools for collecting human movement data. Model-based filtering approaches (e.g. Extended Kalman Filter) have been proposed to estimate joint angles from IMUs data but little is known about ...

Combining wearable sensor signals, machine learning and biomechanics to estimate tibial bone force and damage during running.

Human movement science
There are tremendous opportunities to advance science, clinical care, sports performance, and societal health if we are able to develop tools for monitoring musculoskeletal loading (e.g., forces on bones or muscles) outside the lab. While wearable se...

Substrate-Free Multilayer Graphene Electronic Skin for Intelligent Diagnosis.

ACS applied materials & interfaces
Current wearable sensors are fabricated with substrates, which limits the comfort, flexibility, stretchability, and induces interface mismatch. In addition, the substrate prevents the evaporation of sweat and is harmful to skin health. In this work, ...