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sEMG pattern recognition algorithms have been explored extensively in decoding movement intent, yet are known to be vulnerable to changing recording conditions, exhibiting significant drops in performance across subjects, and even across…

Machine Learning · Computer Science 2024-01-08 Joao Pereira , Dimitrios Chalatsis , Balint Hodossy , Dario Farina

How to design an optimal wearable device for human movement recognition is vital to reliable and accurate human-machine collaboration. Previous works mainly fabricate wearable devices heuristically. Instead, this paper raises an academic…

Computer Vision and Pattern Recognition · Computer Science 2022-07-25 Xiaohao Xu , Zihao Du , Huaxin Zhang , Ruichao Zhang , Zihan Hong , Qin Huang , Bin Han

Hand gesture recognition based on surface electromyographic (sEMG) signals is a promising approach for developing Human-Machine Interfaces (HMIs) with a natural control, such as intuitive robot interfaces or poly-articulated prostheses.…

Signal Processing · Electrical Eng. & Systems 2023-06-21 Marcello Zanghieri

In sensitive scenarios, such as meetings, negotiations, and team sports, messages must be conveyed without detection by non-collaborators. Previous methods, such as encrypting messages, eye contact, and micro-gestures, had problems with…

Human-Computer Interaction · Computer Science 2024-11-22 Hongxin Li , Jingsheng Tang , Xuechao Xu , Wei Dai , Yaru Liu , Junhao Xiao , Huimin Lu , Zongtan Zhou

Regressively-based surface electromyography (sEMG) prosthetics are widely used for their ability to continuously convert muscle activity into finger force and motion. However, they typically require additional kinematic or dynamic sensors,…

Robotics · Computer Science 2025-11-21 Gang Liu , Ye Sun , Zhenxiang Wang , Chuanmei Xi , Ziyang He , Shanshan Guo , Rui Zhang , Dezhong Yao

The main purpose of this research is to move the robotic arm (5DoF) in real-time, based on the surface Electromyography (sEMG) signals, as obtained from the wireless Myo gesture armband to distinguish seven hand movements. The sEMG signals…

Signal Processing · Electrical Eng. & Systems 2018-10-24 Hussein F. Hassan , Sadiq J. Abou-Loukh , Ibraheem Kasim Ibraheem

Surface electromyography (sEMG) signals exhibit substantial inter-subject variability and are highly susceptible to noise, posing challenges for robust and interpretable decoding. To address these limitations, we propose a discrete…

Signal Processing · Electrical Eng. & Systems 2026-03-02 Yuepeng Chen , Kaili Zheng , Ji Wu , Zhuangzhuang Li , Ye Ma , Dongwei Liu , Chenyi Guo , Xiangling Fu

Recently, surface electromyogram (EMG) has been proposed as a novel biometric trait for addressing some key limitations of current biometrics, such as spoofing and liveness. The EMG signals possess a unique characteristic: they are…

Cryptography and Security · Computer Science 2022-12-02 Ashirbad Pradhan , Jiayuan He , Ning Jiang

Surface electromyography (sEMG) is a widely used muscle activity monitoring technique. sEMG measures muscle activity through monopolar and bipolar, multi-electrode electrodes. The surface electrodes are placed on the surface of the skin…

Signal Processing · Electrical Eng. & Systems 2023-12-25 Kukhokuhle Tsengwa , Stephen Paine , Fred Nicolls , Yumna Albertus , Amir Patel

Surface electromyography (sEMG) has gained significant importance during recent advancements in consumer electronics for healthcare systems, gesture analysis and recognition and sign language communication. For such a system, it is…

Signal Processing · Electrical Eng. & Systems 2020-05-04 Rinki Gupta , Karush Suri

Electromyography (EMG) signal analysis is a popular method for controlling prosthetic and gesture control equipment. For portable systems, such as prosthetic limbs, real-time low-power operation on embedded processors is critical, but to…

Signal Processing · Electrical Eng. & Systems 2019-05-10 Sumit Raurale , John McAllister , Jesus Martinez del Rincon

Hand gesture recognition using multichannel surface electromyography (sEMG) is challenging due to unstable predictions and inefficient time-varying feature enhancement. To overcome the lack of signal based time-varying feature problems, we…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Jungpil Shin , Abu Saleh Musa Miah , Sota Konnai , Shu Hoshitaka , Pankoo Kim

Objective: Multimodal hand gesture recognition (HGR) systems can achieve higher recognition accuracy compared to unimodal HGR systems. However, acquiring multimodal gesture recognition data typically requires users to wear additional…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Wentao Wei , Linyan Ren

Wearable robotic hand rehabilitation devices can allow greater freedom and flexibility than their workstation-like counterparts. However, the field is generally lacking effective methods by which the user can operate the device: such…

Robotics · Computer Science 2019-01-14 Sangwoo Park , Cassie Meeker , Lynne M. Weber , Lauri Bishop , Joel Stein , Matei Ciocarlie

Accurate human pose estimation is essential for effective Human-Robot Interaction (HRI). By observing a user's arm movements, robots can respond appropriately, whether it's providing assistance or avoiding collisions. While visual…

Robotics · Computer Science 2025-02-11 Rotem Atari , Eran Bamani , Avishai Sintov

Hands are the primary means through which humans interact with the world. Reliable and always-available hand pose inference could yield new and intuitive control schemes for human-computer interactions, particularly in virtual and augmented…

Electromyography (EMG) signals have been successfully employed for driving prosthetic limbs of a single or double degree of freedom. This principle works by using the amplitude of the EMG signals to decide between one or two simpler…

Computer Vision and Pattern Recognition · Computer Science 2020-08-13 Asad Ullah , Sarwan Ali , Imdadullah Khan , Muhammad Asad Khan , Safiullah Faizullah

This study investigates the impact of electrode shift and sensor reapplication on common surface electromyography (sEMG) features in lower limb muscles, factors which have, thus far, precluded clinicians from being able to attribute…

Signal Processing · Electrical Eng. & Systems 2025-09-19 Fraser Douglas , Mona Pei , Calvin Kuo

Electromyography (EMG) is a way of measuring the bioelectric activities that take place inside the muscles. EMG is usually performed to detect abnormalities within the nerves or muscles of a target area. The recent developments in the field…

Computer Vision and Pattern Recognition · Computer Science 2021-01-19 Niloy Sikder , Abu Shamim Mohammad Arif , Abdullah-Al Nahid

Surface electromyogram (EMG) can be employed as an interface signal for various devices and software via pattern recognition. In EMG-based pattern recognition, the classifier should not only be accurate, but also output an appropriate…

Signal Processing · Electrical Eng. & Systems 2024-06-28 Akira Furui