Erik Scheme

Engineering · Physical Sciences

46h-index7.2kcitations190works2.92yr avg
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Research Topics

Muscle activation and electromyography studies(125), EEG and Brain-Computer Interfaces(76), Neuroscience and Neural Engineering(68), Advanced Sensor and Energy Harvesting Materials(39), Motor Control and Adaptation(26)

Publications190 total

First International StepUP Competition for Biometric Footstep Recognition: Methods, Results and Remaining Challenges
ArXiv.org·2026Open Access
First International StepUP Competition for Biometric Footstep Recognition: Methods, Results and Remaining Challenges
arXiv (Cornell University)·2026Open Access
Investigating Feedback-Informed Screen-Guided Training to Enhance Myoelectric Control and Predictability
IEEE Transactions on Neural Systems and Rehabilitation Engineering·2025Open Access
PolarFitts: A More Intuitive Framework for Assessing Myoelectric Control Performance
2025
From zero- to few-shot: deep temporal learning of wrist EMG enables scalable cross-user gesture recognition
Journal of Neural Engineering·2025· 1 citedOpen Access
Self-supervised representation learning with continuous training data improves the feel and performance of myoelectric control
Computers in Biology and Medicine·2025· 1 citedOpen Access
A dataset of high-resolution plantar pressures for gait analysis across varying footwear and walking speeds
Scientific Data·2025Open Access
Raising the standard: an open source benchmarking platform and data repository to accelerate myoelectric control research
Machine Learning Health·2025Open Access
Variability-based assessment of assisted gait using a multi-sensor instrumented cane
Computers in Biology and Medicine·2025Open Access
Towards Next-Generation Myoelectric Prostheses: 3D-Printed Electrode Arrays for Gesture Recognition
2025
Context Informed Incremental Learning Improves Myoelectric Control Performance in Virtual Reality Object Manipulation Tasks
2025
A Qualitative Exploration of EMG Visual Feedback for Spinal Cord Injury Rehabilitation
2025
Efficient Multi-Positioned Training for Regression-Based Myoelectric Control: Exploring Transformer Models with Transfer Learning
2025· 1 cited
Context Informed Incremental Learning Improves Myoelectric Control Performance in Virtual Reality Object Manipulation Tasks
arXiv (Cornell University)·2025Open Access
A dataset of high-resolution plantar pressures for gait analysis across varying footwear and walking speeds
arXiv (Cornell University)·2025Open Access
A Framework for Interactive Sport Training Technology
Foundations and Trends® in Human–Computer Interaction·2025· 1 citedOpen Access
EMG-based wake gestures eliminate false activations during out-of-set activities of daily living: an online myoelectric control study
Journal of Neural Engineering·2025· 4 citedOpen Access
Context-Informed Incremental Learning Improves Throughput and Reduces Drift in Regression-Based Myoelectric Control
IEEE Transactions on Neural Systems and Rehabilitation Engineering·2025· 1 citedOpen Access
(Un)supervised (Co)adaptation via Incremental Learning for Myoelectric Control: Motivation, Review, and Future Directions
IEEE Transactions on Neural Systems and Rehabilitation Engineering·2025· 2 citedOpen Access
Screen Guided Training Does Not Capture Goal-Oriented Behaviors: Learning Myoelectric Control Mappings From Scratch Using Context Informed Incremental Learning
IEEE Transactions on Neural Systems and Rehabilitation Engineering·2024· 6 citedOpen Access
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Frequent Co-authors

Kevin Englehart(27), Angkoon Phinyomark(13), Ali Ameri(5), Ernest Nlandu Kamavuako(5), Evan Campbell(5), Anders Lyngvi Fougner(3), Øyvind Stavdahl(3), Rami N. Khushaba(3), Levi J. Hargrove(3), Mohammad Ali Akhaee(3), Ashkan Radmand(3), Benoit Gosselin(3), Ahmed W. Shehata(3), Adrian D. C. Chan(2), Patrick M. Pilarski(2), P.A. Parker(2), B. Hudgins(2), Pradeep Kumar(2), Partha Pratim Roy(2), Debi Prosad Dogra(2)