AIMC Topic: Artificial Limbs

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Improving Automatic Control of Upper-Limb Prosthesis Wrists Using Gaze-Centered Eye Tracking and Deep Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Feb 16, 2022
Many upper-limb prostheses lack proper wrist rotation functionality, leading to users performing poor compensatory strategies, leading to overuse or abandonment. In this study, we investigate the validity of creating and implementing a data-driven pr...
Wrist Artificial Limbs Wrist Joint Humans Eye-Tracking Technology Deep Learning
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Research on the Improved CNN Deep Learning Method for Motion Intention Recognition of Dynamic Lower Limb Prosthesis.

Journal of healthcare engineering Dec 6, 2021
OBJECTIVE: In order to study the motion recognition intention of lower limb prosthesis based on the CNN deep learning algorithm.
Intention Deep Learning Artificial Limbs Motion Humans Neural Networks, Computer
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Spatio-temporal warping for myoelectric control: an offline, feasibility study.

Journal of neural engineering Dec 1, 2021
The efficacy of an adopted feature extraction method directly affects the classification of the electromyographic (EMG) signals in myoelectric control applications. Most methods attempt to extract the dynamics of the multi-channel EMG signals in the ...
Electromyography Artificial Limbs Feasibility Studies Neural Networks, Computer
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Emerging of new bioartificial corticospinal motor synergies using a robotic additional thumb.

Scientific reports Sep 16, 2021
It is likely that when using an artificially augmented hand with six fingers, the natural five plus a robotic one, corticospinal motor synergies controlling grasping actions might be different. However, no direct neurophysiological evidence for this ...
Motor Neurons Pyramidal Tracts Robotics Artificial Limbs Motor Skills Evoked Potentials, Motor Motor Cortex Thumb Humans Adult Female Male Magnetic Resonance Imaging
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Cutaneous Ionogel Mechanoreceptors for Soft Machines, Physiological Sensing, and Amputee Prostheses.

Advanced materials (Deerfield Beach, Fla.) Aug 1, 2021
Touch sensing has a central role in robotic grasping and emerging human-machine interfaces for robot-assisted prosthetics. Although advancements in soft conductive polymers have promoted the creation of diverse pressure sensors, these sensors are dif...
Humans Wearable Electronic Devices Robotics Prosthesis Design Hydrogels Touch Skin Amputees Artificial Limbs Mechanoreceptors
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A Subvision System for Enhancing the Environmental Adaptability of the Powered Transfemoral Prosthesis.

IEEE transactions on cybernetics May 18, 2021
Visual information is indispensable to human locomotion in complex environments. Although amputees can perceive the environmental information by eyes, they cannot transmit the neural signals to prostheses directly. To augment human-prosthesis interac...
Walking Artificial Limbs Environment Adult Male Deep Learning Image Processing, Computer-Assisted Robotics Signal Processing, Computer-Assisted Humans Decision Support Techniques Female
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Optimal strategy of sEMG feature and measurement position for grasp force estimation.

PloS one Mar 30, 2021
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...
Forearm Hand Strength Humans Electromyography Neural Networks, Computer Artificial Limbs
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Activities of daily living with bionic arm improved by combination training and latching filter in prosthesis control comparison.

Journal of neuroengineering and rehabilitation Feb 25, 2021
BACKGROUND: Advanced prostheses can restore function and improve quality of life for individuals with amputations. Unfortunately, most commercial control strategies do not fully utilize the rich control information from residual nerves and musculatur...
Male Quality of Life Signal Processing, Computer-Assisted Electromyography Artificial Limbs Activities of Daily Living Humans Machine Learning Young Adult Arm Movement Bionics
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User training for machine learning controlled upper limb prostheses: a serious game approach.

Journal of neuroengineering and rehabilitation Feb 12, 2021
BACKGROUND: Upper limb prosthetics with multiple degrees of freedom (DoFs) are still mostly operated through the clinical standard Direct Control scheme. Machine learning control, on the other hand, allows controlling multiple DoFs although it requir...
Exercise Therapy Adult Video Games Humans Male Machine Learning Hand Strength Female Hand Electromyography Artificial Limbs
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Application of machine learning to the identification of joint degrees of freedom involved in abnormal movement during upper limb prosthesis use.

PloS one Feb 11, 2021
To evaluate movement quality of upper limb (UL) prosthesis users, performance-based outcome measures have been developed that examine the normalcy of movement as compared to a person with a sound, intact hand. However, the broad definition of "normal...
Female Young Adult Adult Upper Extremity Dyskinesias Humans Machine Learning Artificial Limbs Biomechanical Phenomena Range of Motion, Articular Male Movement Adolescent
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