{"url":"/dataset/putemg","name":"putEMG","full_name":null,"description_markdown":"putEMG and putEMG-Force datasets are databases of surface electromyographic activity recorded from forearm. Datasets allows for development of algorithms for gesture recognition and grasp force recognition. Experiment was conducted on 44 participants, with two repetitions separated by, minimum of one week. The dataset includes 7 active gestures (like hand flexion, extension, etc.) + idle and a set of trials with isometric contractions. sEMG was recorded using a 24-electrode matrix.","description_withheld":null,"homepage":"https://biolab.put.poznan.pl/putemg-dataset/","introduced_date":"2019-08-22","introduced_date_note":null,"introduced_by":{"paper":"/paper/putemg-a-surface-electromyography-hand","title":"putEMG -- a surface electromyography hand gesture recognition dataset","first_author":null,"url":null},"license":{"name":"CC BY-NC 4.0","url":"https://creativecommons.org/licenses/by-nc/4.0/"},"modalities":[],"tasks":[],"languages":[],"variants":["putEMG"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}