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Simultaneous electrocardiography (ECG) and phonocardiogram (PCG) provide a comprehensive, multimodal perspective on cardiac function by capturing the heart's electrical and mechanical activities, respectively. However, the distinct and…

Machine Learning · Computer Science 2025-06-13 Sajjad Karimi , Amit J. Shah , Gari D. Clifford , Reza Sameni

Kinematics decoding from brain activity helps in developing rehabilitation or power-augmenting brain-computer interface devices. Low-frequency signals recorded from non-invasive electroencephalography (EEG) are associated with the neural…

Signal Processing · Electrical Eng. & Systems 2022-08-30 Anant Jain , Lalan Kumar

Recently, practical brain-computer interface is actively carried out, especially, in an ambulatory environment. However, the electroencephalography (EEG) signals are distorted by movement artifacts and electromyography signals when users…

Human-Computer Interaction · Computer Science 2021-03-04 Young-Eun Lee , Seong-Whan Lee

Efficient control of prosthetic limbs via non-invasive brain-computer interfaces (BCIs) requires advanced EEG processing, including pre-filtering, feature extraction, and action prediction, performed in real time on edge AI hardware.…

Human-Computer Interaction · Computer Science 2025-09-22 Abdul Basit , Maha Nawaz , Saim Rehman , Muhammad Shafique

Brain-Computer Interfaces (BCIs) enable converting the brain electrical activity of an interface user to the user commands. BCI research studies demonstrated encouraging results in different areas such as neurorehabilitation, control of…

Signal Processing · Electrical Eng. & Systems 2021-10-07 Alexandra Samsonova , Barry J. Devereux , Georgios Karakonstantis , Lev Mukhanov

Motor pattern recognition paradigms are the main forms of Brain-Computer Interfaces(BCI) aimed at motor function rehabilitation and are the most easily promoted applications. In recent years, many researchers have suggested encouraging…

Signal Processing · Electrical Eng. & Systems 2024-10-01 ZhengXiao He , Minghong Cai , Letian Li , Siyuan Tian , Ren-Jie Dai

The aim of this study is to investigate bursts- related EEG signals in a focal hand dystonia patient. Despite of considering time domain and frequency domain techniques as mutually exclusive analysis, in this contribution we have taken…

Medical Physics · Physics 2018-02-08 Giulia Cisotto , Umberto Michieli , Leonardo Badia

Robotic arms are increasingly being used in collaborative environments, requiring an accurate understanding of human intentions to ensure both effectiveness and safety. Electroencephalogram (EEG) signals, which measure brain activity,…

Signal Processing · Electrical Eng. & Systems 2024-11-20 Byeong-Hoo Lee , Kang Yin

$\textit{Objective.}$ In this article, we present data and methods for decoding hand gestures using surface electromyogram (EMG) signals. EMG-based upper limb interfaces are valuable for amputee rehabilitation, artificial supernumerary limb…

Signal Processing · Electrical Eng. & Systems 2025-04-04 Harshavardhana T. Gowda , Lee M. Miller

Motor kinematics decoding (MKD) using brain signal is essential to develop Brain-computer interface (BCI) system for rehabilitation or prosthesis devices. Surface electroencephalogram (EEG) signal has been widely utilized for MKD. However,…

Signal Processing · Electrical Eng. & Systems 2023-12-27 Anant Jain , Lalan Kumar

Brain-computer interfaces (BCIs) often suffer from limited robustness and poor long-term adaptability. Model performance rapidly degrades when user attention fluctuates, brain states shift over time, or irregular artifacts appear during…

Signal Processing · Electrical Eng. & Systems 2025-11-12 Yeon-Woo Choi , Hye-Bin Shin , Dan Li

Wearable orthoses can function both as assistive devices, which allow the user to live independently, and as rehabilitation devices, which allow the user to regain use of an impaired limb. To be fully wearable, such devices must have…

Robotics · Computer Science 2018-02-02 Cassie Meeker , Sangwoo Park , Lauri Bishop , Joel Stein , Matei Ciocarlie

$\textit{Objective.}$ Accurate neural decoding of locomotion holds promise for advancing rehabilitation, prosthetic control, and understanding neural correlates of action. Recent studies have demonstrated decoding of locomotion kinematics…

Machine Learning · Computer Science 2026-02-24 Alejandro de Miguel , Nelson Totah , Uri Maoz

Non-invasive electroencephalography (EEG)-based brain-computer interfaces (BCIs) offer an intuitive means for individuals with severe motor impairments to independently operate assistive robotic wheelchairs and navigate built environments.…

Robotics · Computer Science 2025-11-24 Xiaoshan Zhou , Carol C. Menassa , Vineet R. Kamat

(Abridged) Stroke and SCI are conditions that can significantly impact the QoL of survivors in both the physical and psychosocial domains. Both diseases often result in significant motor and sensory impairments that are not fully reversible…

Human-Computer Interaction · Computer Science 2025-07-17 Derrick Lin , Tracie Tran , Shravan Thaploo , Jose Gabrielle E. Matias , Joy E. Pixley , Zoran Nenadic , An H. Do

Electroencephalography (EEG) is a widely used non-invasive technique for measuring brain activity in brain-computer interface (BCI) applications. Supervised EEG decoding models often struggle to generalize across tasks, subjects, and…

Artificial Intelligence · Computer Science 2026-05-29 Ayse Betul Yuce , Sebastian Stober

This article examined brain signals of people with disabilities using various signal processing methods to achieve the desired accuracy for utilizing brain-computer interfaces (BCI). EEG signals resulted from 5 mental tasks of word…

Human-Computer Interaction · Computer Science 2021-11-02 Fateme Dehrouye-Semnani , Nasrollah Moghada Charkari , Seyed Mohammad Mehdi Mirbagheri

Electroencephalography (EEG) is a neuroimaging technique that records brain neural activity with high temporal resolution. Unlike other methods, EEG does not require prohibitively expensive equipment and can be easily set up using…

Human-Computer Interaction · Computer Science 2024-10-01 Arash Akbarinia

Brain-computer interfaces (BCIs) offer transformative potential, but decoding neural signals presents significant challenges. The core premise of this paper is built around demonstrating methods to elucidate the underlying low-dimensional…

Machine Learning · Computer Science 2025-02-28 Benjamin J. Choi

A brain-computer interface (BCI) enables direct communication between the human brain and external devices. Electroencephalography (EEG) based BCIs are currently the most popular for able-bodied users. To increase user-friendliness, usually…

Human-Computer Interaction · Computer Science 2024-12-05 Ziwei Wang , Siyang Li , Jingwei Luo , Jiajing Liu , Dongrui Wu
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