AI Medical Compendium Topic

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Movement

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In-Sensor Computing Realization Using Fully CMOS-Compatible TiN/HfO-Based Neuristor Array.

ACS sensors
With the evolution of artificial intelligence, the explosive growth of data from sensory terminals gives rise to severe energy-efficiency bottleneck issues due to cumbersome data interactions among sensory, memory, and computing modules. Heterogeneou...

Direction-dependent differences in the quality and quantity of horizontal reaching in people after stroke.

Journal of neurophysiology
Arm reaching is often impaired in individuals with stroke. Nonetheless, how aiming directions influence reaching performance and how such differences change with motor recovery over time remain unclear. Here, we elucidated kinematic parameters of rea...

Portable Device to Assist With Force Control in Ultrasound Acquisition.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
This study presents a portable device that ensures precise contact force between a subject and a probe to improve the stability and reproducibility of ultrasound (US) acquisition. The mechanical portion of the device includes a servo motor, gears, an...

Deep Learning in the Recognition of Activities of Daily Living Using Smartwatch Data.

Sensors (Basel, Switzerland)
The recognition of human activities (HAR) using wearable device data, such as smartwatches, has gained significant attention in the field of computer science due to its potential to provide insights into individuals' daily activities. This article ai...

Decoding movement kinematics from EEG using an interpretable convolutional neural network.

Computers in biology and medicine
Continuous decoding of hand kinematics has been recently explored for the intuitive control of electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs). Deep neural networks (DNNs) are emerging as powerful decoders, for their ability to au...

Customized Trajectory Optimization and Compliant Tracking Control for Passive Upper Limb Rehabilitation.

Sensors (Basel, Switzerland)
Passive rehabilitation training in the early poststroke period can promote the reshaping of the nervous system. The trajectory should integrate the physicians' experience and the patient's characteristics. And the training should have high accuracy o...

Hybrid convolution neural network with channel attention mechanism for sensor-based human activity recognition.

Scientific reports
In the field of machine intelligence and ubiquitous computing, there has been a growing interest in human activity recognition using wearable sensors. Over the past few decades, researchers have extensively explored learning-based methods to develop ...

Smart self-propelled particles: a framework to investigate the cognitive bases of movement.

Journal of the Royal Society, Interface
Decision-making and movement of single animals or group of animals are often treated and investigated as separate processes. However, many decisions are taken while moving in a given space. In other words, both processes are optimized at the same tim...

Coherent movement of error-prone individuals through mechanical coupling.

Nature communications
We investigate how reliable movement can emerge in aggregates of highly error-prone individuals. The individuals-robotic modules-move stochastically using vibration motors. By coupling them via elastic links, soft-bodied aggregates can be created. We...

Eye-Gaze Controlled Wheelchair Based on Deep Learning.

Sensors (Basel, Switzerland)
In this paper, we design a technologically intelligent wheelchair with eye-movement control for patients with ALS in a natural environment. The system consists of an electric wheelchair, a vision system, a two-dimensional robotic arm, and a main cont...