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Forearm

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Integration of Forearm sEMG Signals with IMU Sensors for Trajectory Planning and Control of Assistive Robotic Arm.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Patients with issues such as cerebral palsy, spinal cord injury, and multiple sclerosis have difficulties with activities of daily living (ADL). Their abilities to perform tasks can be improved through vigorous physical therapy. When that therapy is ...

Reconstructing Degree of Forearm Rotation from Imagined movements for BCI-based Robot Hand Control.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Brain-computer interface (BCI) is an important tool for rehabilitation and control of an external device (e.g., robot arm or home appliances). Fully reconstruction of upper limb movement from brain signals is one of the critical issues for intuitive ...

Visualized Evidences for Detecting Novelty in Myoelectric Pattern Recognition using 3D Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Although myoelectric pattern recognition (MPR) has been considered as a milestone technique to enable dexterous control of multiple degrees of freedom, outlier data interference (i.e., novelty) is a big issue affecting stability of conventional MPR c...

Development of a Wearable Electrical Impedance Tomographic Sensor for Gesture Recognition With Machine Learning.

IEEE journal of biomedical and health informatics
A wearable electrical impedance tomographic (wEIT) sensor with 8 electrodes is developed to realize gesture recognition with machine learning algorithms. To optimize the wEIT sensor, gesture recognition rates are compared by using a series of electro...

A Fully Embedded Adaptive Real-Time Hand Gesture Classifier Leveraging HD-sEMG and Deep Learning.

IEEE transactions on biomedical circuits and systems
This paper presents a real-time fine gesture recognition system for multi-articulating hand prosthesis control, using an embedded convolutional neural network (CNN) to classify hand-muscle contractions sensed at the forearm. The sensor consists in a ...

Basketball Activity Classification Based on Upper Body Kinematics and Dynamic Time Warping.

International journal of sports medicine
Basketball activity classification can help document players' statistics, allow coaches, trainers and the medical team to quantitatively supervise players' physical exertion and optimize training strategy, and further help prevent potential injuries....

Characterizing forearm muscle activity in young adults during dynamic wrist flexion-extension movement using a wrist robot.

Journal of biomechanics
Current research suggests that the wrist extensor muscles function as the primary stabilizers of the wrist-joint complex. However, most investigations have utilized isometric study designs, with little consideration for wrist dynamics or changes in p...

Characterizing forearm muscle activity in university-aged males during dynamic radial-ulnar deviation of the wrist using a wrist robot.

Journal of biomechanics
Functioning as wrist stabilizers, the wrist extensor muscles exhibit higher levels of muscle activity than the flexors in most distal upper-limb tasks. However, this finding has been derived mostly from isometric or wrist flexion-extension protocols,...

Optimal strategy of sEMG feature and measurement position for grasp force estimation.

PloS one
Grasp force estimation based on surface electromyography (sEMG) is essential for the dexterous control of a prosthetic hand. Nowadays, although increasing the number of sEMG measurement positions and extracting more features are common methods to inc...