{"url":"/dataset/ui-prmd","name":"UI-PRMD","full_name":"University of Idaho – Physical Rehabilitation Movement Dataset","description_markdown":"UI-PRMD is a data set of movements related to common exercises performed by patients in physical therapy and rehabilitation programs. The data set consists of 10 rehabilitation exercises. A sample of 10 healthy individuals repeated each exercise 10 times in front of two sensory systems for motion capturing: a Vicon optical tracker, and a Kinect camera. The data is presented as positions and angles of the body joints in the skeletal models provided by the Vicon and Kinect mocap systems.","description_withheld":null,"homepage":"https://www.webpages.uidaho.edu/ui-prmd/","introduced_date":"2019-01-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-deep-learning-framework-for-assessing","title":"A Deep Learning Framework for Assessing Physical Rehabilitation Exercises","first_author":"Y. Liao","url":null},"license":null,"modalities":[{"name":"Biomedical","url":"/datasets/modality/biomedical"},{"name":"Time series","url":"/datasets/modality/time-series"},{"name":"Actions","url":"/datasets/modality/actions"}],"tasks":[{"name":"Action Quality Assessment","url":"/task/action-quality-assessment","datasets_with_task":"/datasets/task/action-quality-assessment"},{"name":"Action Assessment","url":"/task/action-assessment","datasets_with_task":"/datasets/task/action-assessment"}],"languages":[],"variants":["UI-PRMD"],"data_loaders":[],"num_papers_in_archive":10,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/action-assessment-on-ui-prmd","task":"Action Assessment","dataset_variant":"UI-PRMD","rows":1,"metrics":["Prediction Accuracy"],"first_row_in_archive_order":{"model":"EGCN","paper":"/paper/egcn-an-ensemble-based-learning-framework-for","metrics":{"Prediction Accuracy":"86.9"},"code_links":[{"title":"bruceyo/EGCN","url":"https://github.com/bruceyo/EGCN"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/action-quality-assessment-on-ui-prmd","task":"Action Quality Assessment","dataset_variant":"UI-PRMD","rows":1,"metrics":["Average mean absolute error"],"first_row_in_archive_order":{"model":"Spatio-Temporal Model","paper":"/paper/a-deep-learning-framework-for-assessing","metrics":{"Average mean absolute error":"0.0253"},"code_links":[{"title":"avakanski/A-Deep-Learning-Framework-for-Assessing-Physical-Rehabilitation-Exercises","url":"https://github.com/avakanski/A-Deep-Learning-Framework-for-Assessing-Physical-Rehabilitation-Exercises"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/egcn-an-ensemble-based-learning-framework-for","title":"EGCN: An Ensemble-based Learning Framework for Exploring Effective Skeleton-based Rehabilitation Exercise Assessment","date":"2022-07-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/a-deep-learning-framework-for-assessing","title":"A Deep Learning Framework for Assessing Physical Rehabilitation Exercises","date":"2019-01-29","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"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."}