EMG-centered multisensory based technologies for pattern recognition in rehabilitation: state of the art and challenges
In the field of rehabilitation, the electromyography (EMG) signal plays an important role in
interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the …
interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the …
EMG-driven control in lower limb prostheses: A topic-based systematic review
Background The inability of users to directly and intuitively control their state-of-the-art
commercial prosthesis contributes to a low device acceptance rate. Since Electromyography …
commercial prosthesis contributes to a low device acceptance rate. Since Electromyography …
Prediction of muscular paralysis disease based on hybrid feature extraction with machine learning technique for COVID-19 and post-COVID-19 patients
P Subramani, SK, P BD - Personal and ubiquitous computing, 2023 - Springer
Abstract Many Coronavirus disease 2019 (COVID-19) and post-COVID-19 patients
experience muscle fatigues. Early detection of muscle fatigue and muscular paralysis helps …
experience muscle fatigues. Early detection of muscle fatigue and muscular paralysis helps …
[HTML][HTML] Wearable sensors for activity monitoring and motion control: A review
Wearable sensors for activity monitoring currently are being designed and developed,
driven by an increasing demand in health care for noninvasive patient monitoring and …
driven by an increasing demand in health care for noninvasive patient monitoring and …
Lower limb motion intention recognition based on sEMG fusion features
P Zhang, J Zhang, A Elsabbagh - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Surface Electromyography (sEMG) has been extensively used for gait analysis and robotic
control. Since the low accuracy of intention recognition limits the development of …
control. Since the low accuracy of intention recognition limits the development of …
Hand gesture classification framework leveraging the entropy features from sEMG signals and VMD augmented multi-class SVM
T Prabhavathy, VK Elumalai, E Balaji - Expert Systems with Applications, 2024 - Elsevier
To improve the classification accuracy of hand movements from sEMG signals, this paper
puts forward a unified hand gesture classification framework which exploits the potentials of …
puts forward a unified hand gesture classification framework which exploits the potentials of …
Advancements, trends and future prospects of lower limb prosthesis
Amputees with lower limb loss need special care during daily life activities to make the
movement natural as before amputation. No such work exists covering the main aspects …
movement natural as before amputation. No such work exists covering the main aspects …
A novel methodology for classifying EMG movements based on SVM and genetic algorithms
Electromyography (EMG) processing is a fundamental part of medical research. It offers the
possibility of developing new devices and techniques for the diagnosis, treatment, care, and …
possibility of developing new devices and techniques for the diagnosis, treatment, care, and …
A review of terrain detection systems for applications in locomotion assistance
AHA Al-dabbagh, R Ronsse - Robotics and Autonomous Systems, 2020 - Elsevier
Terrain detection systems have been developed for a large body of applications. For
instance, a bionic leg prosthesis would have to adapt its behavior as a function of the terrain …
instance, a bionic leg prosthesis would have to adapt its behavior as a function of the terrain …
Flexible and wearable EMG and PSD sensors enabled locomotion mode recognition for IoHT-based in-home rehabilitation
Y Zhao, J Wang, Y Zhang, H Liu, Z Chen… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Benefiting from the development of the Internet of Healthcare Things (IoHT) in recent years,
locomotion mode recognition using wearable sensors plays a more and more important role …
locomotion mode recognition using wearable sensors plays a more and more important role …