{"url":"/dataset/full-body-pd-dataset","name":"Full-body Parkinson’s disease dataset","full_name":null,"description_markdown":"A public data set of walking full-body kinematics and kinetics in individuals with Parkinson’s disease","description_withheld":null,"homepage":"","introduced_date":"2023-02-15","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Classification","url":"/task/classification-1","datasets_with_task":"/datasets/task/classification-1"}],"languages":[],"variants":["Full-body Parkinson’s disease dataset"],"data_loaders":[],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/classification-on-full-body-parkinsons","task":"Classification","dataset_variant":"Full-body Parkinson’s disease dataset","rows":7,"metrics":["F1-score (weighted)"],"first_row_in_archive_order":{"model":"PoseFormerV2","paper":"/paper/poseformerv2-exploring-frequency-domain-for","metrics":{"F1-score (weighted)":"0.59"},"code_links":[{"title":"zczcwh/DL-HPE","url":"https://github.com/zczcwh/DL-HPE"},{"title":"qitaozhao/poseformerv2","url":"https://github.com/qitaozhao/poseformerv2"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/motionagformer-enhancing-3d-human-pose","title":"MotionAGFormer: Enhancing 3D Human Pose Estimation with a Transformer-GCNFormer Network","date":"2023-10-25","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":16,"samples_ran":14,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/poseformerv2-exploring-frequency-domain-for","title":"PoseFormerV2: Exploring Frequency Domain for Efficient and Robust 3D Human Pose Estimation","date":"2023-03-30","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":5,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/motionbert-unified-pretraining-for-human","title":"MotionBERT: A Unified Perspective on Learning Human Motion Representations","date":"2022-10-12","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":5,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/mixste-seq2seq-mixed-spatio-temporal-encoder","title":"MixSTE: Seq2seq Mixed Spatio-Temporal Encoder for 3D Human Pose Estimation in Video","date":"2022-03-02","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":4,"samples_unverified":0,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/pose-transformers-potr-human-motion","title":"Pose Transformers (POTR): Human Motion Prediction with Non-Autoregressive Transformers","date":"2021-09-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/estimating-parkinsonism-severity-in-natural","title":"Estimating Parkinsonism Severity in Natural Gait Videos of Older Adults with Dementia","date":"2021-05-07","rows_on_this_dataset":1,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":37,"samples_ran":28,"samples_unverified":9,"pointer_only_for_licence":4,"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."}