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Artificial Limbs

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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...

CyberLimb: a novel robotic prosthesis concept with shared and intuitive control.

Journal of neuroengineering and rehabilitation
BACKGROUND: Existing assistive technologies attempt to mimic biological functions through advanced mechatronic designs. In some occasions, the information processing demands for such systems require substantial information bandwidth and convoluted co...

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...

Noncontact Electromagnetic Wireless Recognition for Prosthesis Based on Intelligent Metasurface.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
With the development of artificial intelligence and Internet of Things, hand gesture recognition techniques have attracted great attention owing to their excellent applications in developing human-machine interaction (HMI). Here, the authors propose ...

Effect of variable transmission on body-powered prosthetic grasping.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Body-powered upper-limb prostheses remain a popular option for those with limb absence due to their passive nature. These devices typically feature a constant transmission ratio between the forces input by the user and the grasp forces output by the ...

The Effectiveness of Narrowing the Window size for LD & HD EMG Channels based on Novel Deep Learning Wavelet Scattering Transform Feature Extraction Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The use of the Electromyogram (EMG) signals as a source of control to command externally powered prostheses is often challenged by the signal complexity and non-stationary behavior. Mainly, two factors affect classification accuracy: selecting the op...

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 ...

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...

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...

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...