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Full-Text Articles in Musculoskeletal, Neural, and Ocular Physiology
Dimensionality Reduction For Classification Of Object Weight From Electromyography, Elnaz Lashgari, Uri Maoz
Dimensionality Reduction For Classification Of Object Weight From Electromyography, Elnaz Lashgari, Uri Maoz
Psychology Faculty Articles and Research
Electromyography (EMG) is a simple, non-invasive, and cost-effective technology for measuring muscle activity. However, multi-muscle EMG is also a noisy, complex, and high-dimensional signal. It has nevertheless been widely used in a host of human-machine-interface applications (electrical wheelchairs, virtual computer mice, prosthesis, robotic fingers, etc.) and, in particular, to measure the reach-and-grasp motions of the human hand. Here, we developed an automated pipeline to predict object weight in a reach-grasp-lift task from an open dataset, relying only on EMG data. In doing so, we shifted the focus from manual feature-engineering to automated feature-extraction by using pre-processed EMG signals and thus …