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Movement

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Bioinspired Self-Resettable Hydrogel Actuators Powered by a Chemical Fuel.

ACS applied materials & interfaces
The movements of soft living tissues, such as muscle, have sparked a strong interest in the design of hydrogel actuators; however, so far, typical manmade examples still lag behind their biological counterparts, which usually function under nonequili...

Dance Action Recognition Model Using Deep Learning Network in Streaming Media Environment.

Journal of environmental and public health
Dance movement recognition is a video technology that has a significant impact on intelligent applications and is widely applied in many industries. In the training of intelligent dance assistants, this method can be used. Dancers' postures can be re...

Assessment of deep learning pose estimates for sports collision tracking.

Journal of sports sciences
Injury assessment during sporting collisions requires estimation of the associated kinematics. While marker-based solutions are widely accepted as providing accurate and reliable measurements, setup times are lengthy and it is not always possible to ...

Lite-3DCNN Combined with Attention Mechanism for Complex Human Movement Recognition.

Computational intelligence and neuroscience
Three-dimensional convolutional network (3DCNN) is an essential field of motion recognition research. The research work of this paper optimizes the traditional three-dimensional convolution network, introduces the self-attention mechanism, and propos...

Effect of button layout on the exploration and learning of robot operation using an unfamiliar controller.

PloS one
Robots are becoming increasingly accessible to both experts and non-experts. Therefore, establishing a method for learning robot operations that can be easily mastered by non-experts is important. With this in mind, we aimed to develop a method that ...

Orthogonal Features Based EEG Signals Denoising Using Fractional and Compressed One-Dimensional CNN Autoencoder.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper presents a fractional one-dimensional convolutional neural network (CNN) autoencoder for denoising the Electroencephalogram (EEG) signals which often get contaminated with noise during the recording process, mostly due to muscle artifacts ...

A Deep Learning Approach to Classify Sitting and Sleep History from Raw Accelerometry Data during Simulated Driving.

Sensors (Basel, Switzerland)
Prolonged sitting and inadequate sleep can impact driving performance. Therefore, objective knowledge of a driver's recent sitting and sleep history could help reduce safety risks. This study aimed to apply deep learning to raw accelerometry data col...

Residual one-dimensional convolutional neural network for neuromuscular disorder classification from needle electromyography signals with explainability.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Neuromuscular disorders are diseases that damage our ability to control body movements. Needle electromyography (nEMG) is often used to diagnose neuromuscular disorders, which is an electrophysiological test measuring electr...

Fall-from-Height Detection Using Deep Learning Based on IMU Sensor Data for Accident Prevention at Construction Sites.

Sensors (Basel, Switzerland)
Workers at construction sites are prone to fall-from-height (FFH) accidents. The severity of injury can be represented by the acceleration peak value. In the study, a risk prediction against FFH was made using IMU sensor data for accident prevention ...

Discriminating Free Hand Movements Using Support Vector Machine and Recurrent Neural Network Algorithms.

Sensors (Basel, Switzerland)
Decoding natural hand movements is of interest for human-computer interaction and may constitute a helpful tool in the diagnosis of motor diseases and rehabilitation monitoring. However, the accurate measurement of complex hand movements and the deco...