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Surface electromyography (sEMG) is a technology to assess muscle activation, which is an important component in applications related to diagnosis, treatment, progression assessment, and rehabilitation of specific individuals' conditions.…

Early identification of individuals at risk of stroke remains a major clinical challenge, as prodromal motor im- pairments are often subtle and transient. In this pilot study, a wearable sensor-based framework is proposed for early pre-…

Neurons and Cognition · Quantitative Biology 2026-03-18 Chanakan Chaipan , Aueaphum Aueawatthanaphisut

We developed a new grip force measurement concept that allows for embedding tactile stimulation mechanisms in a gripper. This concept is based on a single force sensor to measure the force applied on each side of the gripper, and it…

Robotics · Computer Science 2020-06-09 Guy Bitton , Ilana Nisky , David Zarrouk

Musculoskeletal diseases such as sarcopenia and osteoporosis are major obstacles to health during aging. Although dual-energy X-ray absorptiometry (DXA) and computed tomography (CT) can be used to evaluate musculoskeletal conditions,…

Computer Vision and Pattern Recognition · Computer Science 2023-07-24 Yi Gu , Yoshito Otake , Keisuke Uemura , Masaki Takao , Mazen Soufi , Yuta Hiasa , Hugues Talbot , Seiji Okata , Nobuhiko Sugano , Yoshinobu Sato

In this study, we developed a method to estimate the relationship between stimulation current and volatility during isometric contraction. In functional electrical stimulation (FES), joints are driven by applying voltage to muscles. This…

Human-Computer Interaction · Computer Science 2021-01-21 Tomoya Kitamura , Yuu Hasegawa , Sho Sakaino , Toshiaki Tsuji

Surface Electromyography (sEMG) is a technology to measure the bio-potentials across the muscles. The true prospective of this technology is yet to be explored. In this paper, a simple and economic construction of a sEMG sensor is proposed.…

Medical Physics · Physics 2015-10-15 Abhishek Jha , Mrinal Sen

Intuitive control of prostheses relies on training algorithms to correlate biological recordings to motor intent. The quality of the training dataset is critical to run-time performance, but it is difficult to label hand kinematics…

Robotics · Computer Science 2020-01-27 Jacob A. George , Troy N. Tully , Paul C. Colgan , Gregory A. Clark

Objective: Fast neural Electrical Impedance Tomography (EIT) is a method which permits imaging of neuronal activity in nerves by measuring the associated impedance changes (dZ). Due to the small magnitudes of dZ signals, EIT parameters…

Medical Physics · Physics 2019-10-17 Ilya Tarotin , Kirill Aristovich , David Holder

During morphogenesis, the shape of a tissue emerges from collective cellular behaviors, which are in part regulated by mechanical and biochemical interactions between cells. Quantification of force and stress is therefore necessary to…

Tissues and Organs · Quantitative Biology 2014-02-19 K. Sugimura , Y. Bellaïche , F. Graner , P. Marcq , S. Ishihara

Mammography is currently the primary imaging modality for breast cancer screening and plays an important role in cancer diagnostics. A standard mammographic image acquisition always includes the compression of the breast prior x-ray…

Measuring the forces of individual muscles in a muscle group around a joint is non-trivial, and researchers have suggested using surrogates for individual muscle forces instead. Traditionally, experimentalists have shown that the force…

Tissues and Organs · Quantitative Biology 2025-08-26 Karan Taneja , Xiaolong He , Chung-Hao Lee , John Hodgson , Usha Sinha , Shantanu Sinha , J. S. Chen

In this paper, our goal is to enable quantitative feedback on muscle fatigue during exercise to optimize exercise effectiveness while minimizing injury risk. We seek to capture fatigue by monitoring surface vibrations that muscle exertion…

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

Electrodermal activity (EDA) reflects changes in skin conductance, which are closely tied to human psychophysiological states. For example, EDA sensors can assess stress, cognitive workload, arousal, or other measures tied to the…

Human-Computer Interaction · Computer Science 2024-03-25 Martin Schmitz , Dominik Schön , Henning Klagemann , Thomas Kosch

Objective: For transradial amputees, robotic prosthetic hands promise to regain the capability to perform daily living activities. Current control methods based on physiological signals such as electromyography (EMG) are prone to yielding…

Many physical tasks such as pulling out a drawer or wiping a table can be modeled with geometric constraints. These geometric constraints are characterized by restrictions on kinematic trajectories and reaction wrenches (forces and moments)…

Robotics · Computer Science 2020-11-02 Guru Subramani , Michael Hagenow , Michael Gleicher , Michael Zinn

The muscle synergy concept provides the best framework to understand motor control and it has been recently utilised in many applications such as prosthesis control. The current muscle synergy model relies on decomposing multi-channel…

Signal Processing · Electrical Eng. & Systems 2020-07-07 Ahmed Ebied , Loukianos Spyrou , Eli Kinney-Lang , Javier Escudero

Impedance Spectroscopy resolves electrical properties into uncorrelated variables, as a function of frequency, with exquisite resolution. Separation is robust and most useful when the system is linear. Impedance spectroscopy combined with…

Quantitative Methods · Quantitative Biology 2015-11-05 Robert Eisenberg

Motor control is a set of time-varying muscle excitations which generate desired motions for a biomechanical system. Muscle excitations cannot be directly measured from live subjects. An alternative approach is to estimate muscle…

Machine Learning · Computer Science 2019-10-29 Amir H. Abdi , Pramit Saha , Praneeth Srungarapu , Sidney Fels

We study the task of gesture recognition from electromyography (EMG), with the goal of enabling expressive human-computer interaction at high accuracy, while minimizing the time required for new subjects to provide calibration data. To…

Human-Computer Interaction · Computer Science 2023-11-30 Niklas Smedemark-Margulies , Yunus Bicer , Elifnur Sunger , Tales Imbiriba , Eugene Tunik , Deniz Erdogmus , Mathew Yarossi , Robin Walters
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