Toward higher-performance bionic limbs for wider clinical use
Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by
the user as belonging to their own body. Robotic limbs can convey information about the …
the user as belonging to their own body. Robotic limbs can convey information about the …
Gesture recognition using surface electromyography and deep learning for prostheses hand: state-of-the-art, challenges, and future
W Li, P Shi, H Yu - Frontiers in neuroscience, 2021 - frontiersin.org
Amputation of the upper limb brings heavy burden to amputees, reduces their quality of life,
and limits their performance in activities of daily life. The realization of natural control for …
and limits their performance in activities of daily life. The realization of natural control for …
Deep learning for processing electromyographic signals: A taxonomy-based survey
Deep Learning (DL) has been recently employed to build smart systems that perform
incredibly well in a wide range of tasks, such as image recognition, machine translation, and …
incredibly well in a wide range of tasks, such as image recognition, machine translation, and …
Predicting wrist kinematics from motor unit discharge timings for the control of active prostheses
Background Current myoelectric control algorithms for active prostheses map time-and
frequency-domain features of the interference EMG signal into prosthesis commands. With …
frequency-domain features of the interference EMG signal into prosthesis commands. With …
Leveraging deep feature learning for wearable sensors based handwritten character recognition
SK Singh, A Chaturvedi - Biomedical Signal Processing and Control, 2023 - Elsevier
Despite rapid advancements in technology, handwritten characters still hold significant roles
in various fields, including education, communication, biometric signature verification, and …
in various fields, including education, communication, biometric signature verification, and …
Stacked sparse autoencoders for EMG-based classification of hand motions: A comparative multi day analyses between surface and intramuscular EMG
Advances in myoelectric interfaces have increased the use of wearable prosthetics including
robotic arms. Although promising results have been achieved with pattern recognition-based …
robotic arms. Although promising results have been achieved with pattern recognition-based …
Wearable MMG-plus-one armband: Evaluation of normal force on mechanomyography (MMG) to enhance human-machine interfacing
In this paper, we introduce a new mode of mechanomyography (MMG) signal capture for
enhancing the performance of human-machine interfaces (HMIs) through modulation of …
enhancing the performance of human-machine interfaces (HMIs) through modulation of …
An intention-based online bilateral training system for upper limb motor rehabilitation
Bilateral rehabilitation training robotic systems have potential to promote the upper limb
motor recovery of post-stroke hemiparesis patients through providing the synchronization …
motor recovery of post-stroke hemiparesis patients through providing the synchronization …
Co-adaptive control of bionic limbs via unsupervised adaptation of muscle synergies
Objective: In this work, we present a myoelectric interface that extracts natural motor
synergies from multi-muscle signals and adapts in real-time with new user inputs. With this …
synergies from multi-muscle signals and adapts in real-time with new user inputs. With this …
Evaluation of methods for the extraction of spatial muscle synergies
Muscle synergies have been largely used in many application fields, including motor control
studies, prosthesis control, movement classification, rehabilitation, and clinical studies. Due …
studies, prosthesis control, movement classification, rehabilitation, and clinical studies. Due …