A review of myoelectric control for prosthetic hand manipulation
Myoelectric control for prosthetic hands is an important topic in the field of rehabilitation.
Intuitive and intelligent myoelectric control can help amputees to regain upper limb function …
Intuitive and intelligent myoelectric control can help amputees to regain upper limb function …
Use of artificial intelligence techniques to assist individuals with physical disabilities
S Pancholi, JP Wachs… - Annual Review of …, 2024 - annualreviews.org
Assistive technologies (AT) enable people with disabilities to perform activities of daily living
more independently, have greater access to community and healthcare services, and be …
more independently, have greater access to community and healthcare services, and be …
Physics-informed deep learning for musculoskeletal modeling: Predicting muscle forces and joint kinematics from surface EMG
Musculoskeletal models have been widely used for detailed biomechanical analysis to
characterise various functional impairments given their ability to estimate movement …
characterise various functional impairments given their ability to estimate movement …
EMGHandNet: A hybrid CNN and Bi-LSTM architecture for hand activity classification using surface EMG signals
NK Karnam, SR Dubey, AC Turlapaty… - Biocybernetics and …, 2022 - Elsevier
Abstract Recently, Convolutional Neural Networks (CNNs) have been used for the
classification of hand activities from surface Electromyography (sEMG) signals. However …
classification of hand activities from surface Electromyography (sEMG) signals. However …
Deep learning for predicting respiratory rate from biosignals
In the past decade, deep learning models have been applied to bio-sensors used in a body
sensor network for prediction. Given recent innovations in this field, the prediction accuracy …
sensor network for prediction. Given recent innovations in this field, the prediction accuracy …
Movenet: A deep neural network for joint profile prediction across variable walking speeds and slopes
An exoskeleton needs reference joint angle profiles at various speeds and slopes for its
application in real-world scenarios. Recording these profiles and their implementation in the …
application in real-world scenarios. Recording these profiles and their implementation in the …
Toward robust, adaptiveand reliable upper-limb motion estimation using machine learning and deep learning–A survey in myoelectric control
To develop multi-functionalhuman-machine interfaces that can help disabled people
reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) …
reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) …
Surface electromyography as a natural human–machine interface: a review
Surface electromyography (sEMG) is a non-invasive method of measuring neuromuscular
potentials generated when the brain instructs the body to perform both fine and coarse …
potentials generated when the brain instructs the body to perform both fine and coarse …
Continuous prediction of human joint mechanics using emg signals: A review of model-based and model-free approaches
SP Sitole, FC Sup - IEEE Transactions on Medical Robotics …, 2023 - ieeexplore.ieee.org
This paper reviews model-based and model-free approaches for continuous prediction of
human joint motion using surface electromyography (EMG) signals. The review focuses on …
human joint motion using surface electromyography (EMG) signals. The review focuses on …
Machine-learned wearable sensors for real-time hand-motion recognition: toward practical applications
Soft electromechanical sensors have led to a new paradigm of electronic devices for novel
motion-based wearable applications in our daily lives. However, the vast amount of random …
motion-based wearable applications in our daily lives. However, the vast amount of random …