AIMC Topic: Artificial Limbs

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A Novel Event-Driven Spiking Convolutional Neural Network for Electromyography Pattern Recognition.

IEEE transactions on bio-medical engineering
Electromyography (EMG) pattern recognition is an important technology for prosthesis control and human-computer interaction etc. However, the practical application of EMG pattern recognition is hampered by poor accuracy and robustness due to electrod...

3D-Printed Artificial Cilia Arrays: A Versatile Tool for Customizable Mechanosensing.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Bio-inspired cilium-based mechanosensors offer a high level of responsiveness, making them suitable for a wide range of industrial, environmental, and biomedical applications. Despite great promise, the development of sensors with multifunctionality,...

Soft Robotics Enables Neuroprosthetic Hand Design.

ACS nano
Development and implementation of neuroprosthetic hands is a multidisciplinary field at the interface between humans and artificial robotic systems, which aims at replacing the sensorimotor function of the upper-limb amputees as their own. Although p...

Simultaneous assessment and training of an upper-limb amputee using incremental machine-learning-based myocontrol: a single-case experimental design.

Journal of neuroengineering and rehabilitation
BACKGROUND: Machine-learning-based myocontrol of prosthetic devices suffers from a high rate of abandonment due to dissatisfaction with the training procedure and with the reliability of day-to-day control. Incremental myocontrol is a promising appro...

EMG-driven shared human-robot compliant control for in-hand object manipulation in hand prostheses.

Journal of neural engineering
. The limited functionality of hand prostheses remains one of the main reasons behind the lack of its wide adoption by amputees. Indeed, while commercial prostheses can perform a reasonable number of grasps, they are often inadequate for manipulating...

Toward Safe Wearer-Prosthesis Interaction: Evaluation of Gait Stability and Human Compensation Strategy Under Faults in Robotic Transfemoral Prostheses.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Although advanced wearable robots can assist human wearers, their internal faults (i.e., sensors or control errors) also pose a challenge. To ensure safe wearer-robot interactions, how internal errors by the prosthesis limb affect the stability of th...

Toward Robust, Adaptiveand Reliable Upper-Limb Motion Estimation Using Machine Learning and Deep Learning-A Survey in Myoelectric Control.

IEEE journal of biomedical and health informatics
To develop multi-functionalhuman-machine interfaces that can help disabled people reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) techniques have been widely implemented to decode human movement intentions from...

A novel sEMG data augmentation based on WGAN-GP.

Computer methods in biomechanics and biomedical engineering
The classification of sEMG signals is fundamental in applications that use mechanical prostheses, making it necessary to work with generalist databases that improve the accuracy of those classifications. Therefore, synthetic signal generation can be ...

Analysis of Neural Network Based Proportional Myoelectric Hand Prosthesis Control.

IEEE transactions on bio-medical engineering
OBJECTIVE: We show that state-of-the-art deep neural networks achieve superior results in regression-based multi-class proportional myoelectric hand prosthesis control than two common baseline approaches, and we analyze the neural network mapping to ...

A Systematic Study on Electromyography-Based Hand Gesture Recognition for Assistive Robots Using Deep Learning and Machine Learning Models.

Sensors (Basel, Switzerland)
Upper limb amputation severely affects the quality of life and the activities of daily living of a person. In the last decade, many robotic hand prostheses have been developed which are controlled by using various sensing technologies such as artific...