Simultaneous sEMG recognition of gestures and force levels for interaction with prosthetic hand

B Fang, C Wang, F Sun, Z Chen, J Shan… - … on Neural Systems …, 2022‏ - ieeexplore.ieee.org
The natural interaction between the prosthetic hand and the upper limb amputation patient is
important and directly affects the rehabilitation effect and operation ability. Most previous …

Multi-grip classification-based prosthesis control with two EMG-IMU sensors

A Krasoulis, S Vijayakumar… - IEEE transactions on …, 2019‏ - ieeexplore.ieee.org
In the field of upper-limb myoelectric prosthesis control, the use of statistical and machine
learning methods has been long proposed as a means of enabling intuitive grip selection …

sEMG-based hand gesture recognition using binarized neural network

S Kang, H Kim, C Park, Y Sim, S Lee, Y Jung - Sensors, 2023‏ - mdpi.com
Recently, human–machine interfaces (HMI) that make life convenient have been studied in
many fields. In particular, a hand gesture recognition (HGR) system, which can be …

BioPoint: Enhancing Human-Computer Interaction through Single-Site, Multi-Sensor Gesture Recognition

X Isabel, E Campbell, L Olivier, G Gagné… - 2024 46th Annual …, 2024‏ - ieeexplore.ieee.org
Advancements in human-computer interaction (HCI) and machine learning are seen as key
avenues to help individuals living with upper limb disabilities in accomplishing their activities …

Human hand movement recognition based on HMM with hyperparameters optimized by maximum mutual information

R Wen, Q Wang, X Ma, Z Li - 2020 Asia-Pacific Signal and …, 2020‏ - ieeexplore.ieee.org
Performing dexterous and versatile movements is essential for multi-finger manipulators for
human-robot collaboration, and designing effective control methods for the robotic …

[HTML][HTML] Selection of EMG sensors based on motion coordinated analysis

L Chen, X Liu, B Xuan, J Zhang, Z Liu, Y Zhang - Sensors, 2021‏ - mdpi.com
The intelligent prosthesis driven by electromyography (EMG) signal provides a solution for
the movement of the disabled. The proper position of EMG sensors can improve the …

Securing embedded medical devices using dual-factor authentication

S Maji, U Banerjee, SH Fuller… - 2021 IEEE 34th …, 2021‏ - ieeexplore.ieee.org
This work provides an analysis of dual-factor authentication protocol for securing low-power
medical devices. The dual-factor protocol incorporates voluntary physical action-based …

The effects of channel number on classification performance for sEMG-based speech recognition

X Wang, M Zhu, H Cui, Z Yang, X Wang… - 2020 42nd Annual …, 2020‏ - ieeexplore.ieee.org
Speech recognition based on surface electromyography (sEMG) signals is an important
research direction with potential applications in life, work and clinical. The number and …

Анализ эффективности методов машинного обучения в задаче распознавания жестов на основе данных электромиографических сигналов

ПС Козырь, АИ Савельев - Компьютерные исследования и …, 2021‏ - mathnet.ru
При разработке систем человеко-машинных интерфейсов актуальной является задача
распознавания жестов. Для выявления наиболее эффективного метода распознавания …

Hand Gesture Recognition Based on EMG Data: A Convolutional Neural Network Approach

P Tsinganos, B Cornelis, J Cornelis, B Jansen… - … , PhyCS 2016, Lisbon …, 2019‏ - Springer
Deep learning (DL) has transformed the field of data analysis by dramatically improving the
state of the art in various classification and prediction tasks. Especially in the area of …