| { |
| "@context": { |
| "@language": "en", |
| "@vocab": "https://schema.org/", |
| "citeAs": "cr:citeAs", |
| "column": "cr:column", |
| "conformsTo": "dct:conformsTo", |
| "containedIn": "cr:containedIn", |
| "cr": "http://mlcommons.org/croissant/", |
| "rai": "http://mlcommons.org/croissant/RAI/", |
| "data": { |
| "@id": "cr:data", |
| "@type": "@json" |
| }, |
| "dataType": { |
| "@id": "cr:dataType", |
| "@type": "@vocab" |
| }, |
| "dct": "http://purl.org/dc/terms/", |
| "equivalentProperty": "cr:equivalentProperty", |
| "examples": { |
| "@id": "cr:examples", |
| "@type": "@json" |
| }, |
| "extract": "cr:extract", |
| "field": "cr:field", |
| "fileProperty": "cr:fileProperty", |
| "fileObject": "cr:fileObject", |
| "fileSet": "cr:fileSet", |
| "format": "cr:format", |
| "includes": "cr:includes", |
| "isLiveDataset": "cr:isLiveDataset", |
| "jsonPath": "cr:jsonPath", |
| "key": "cr:key", |
| "md5": "cr:md5", |
| "parentField": "cr:parentField", |
| "path": "cr:path", |
| "prov": "http://www.w3.org/ns/prov#", |
| "recordSet": "cr:recordSet", |
| "references": "cr:references", |
| "regex": "cr:regex", |
| "repeated": "cr:repeated", |
| "replace": "cr:replace", |
| "samplingRate": "cr:samplingRate", |
| "sc": "https://schema.org/", |
| "separator": "cr:separator", |
| "source": "cr:source", |
| "subField": "cr:subField", |
| "transform": "cr:transform" |
| }, |
| "@type": "sc:Dataset", |
| "name": "ForceBody", |
| "description": "ForceBody pairs the SKEL parametric body model with measured ground reaction forces and inverse-dynamics joint torques across 10,386 motion trials (9,689,808 frames, 26.9 hours) from 140 subjects in 10 source studies aggregated by AddBiomechanics. Each torque label comes with a per-frame, per-DOF Monte Carlo uncertainty sigma_tau, computed for 10,382 of the 10,386 trials. Release 1.3.0.", |
| "conformsTo": [ |
| "http://mlcommons.org/croissant/1.1", |
| "http://mlcommons.org/croissant/RAI/1.0" |
| ], |
| "url": "https://huggingface.co/datasets/kwonjoon/ForceBody", |
| "sameAs": "https://github.com/DominoAI-Lab/ForceBody-NeurIPS-ED-2026", |
| "license": "https://creativecommons.org/licenses/by-nc/4.0/", |
| "version": "1.3.0", |
| "datePublished": "2026-10-29", |
| "dateModified": "2026-11-02", |
| "keywords": [ |
| "3D human body models", |
| "SKEL", |
| "biomechanics", |
| "ground reaction force", |
| "joint torque", |
| "uncertainty annotations", |
| "human motion" |
| ], |
| "creator": [ |
| { |
| "@type": "sc:Person", |
| "name": "Joonwoo Kwon", |
| "email": "kwonjoon@msu.edu", |
| "affiliation": { |
| "@type": "sc:Organization", |
| "name": "Michigan State University" |
| } |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Yufei Zhang", |
| "email": "yufeizhang96@outlook.com", |
| "affiliation": { |
| "@type": "sc:Organization", |
| "name": "Independent Researcher" |
| } |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Xiaoming Liu", |
| "email": "liuxm@cs.unc.edu", |
| "affiliation": { |
| "@type": "sc:Organization", |
| "name": "University of North Carolina at Chapel Hill" |
| } |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Zijun Cui", |
| "email": "cuizijun@msu.edu", |
| "affiliation": { |
| "@type": "sc:Organization", |
| "name": "Michigan State University" |
| } |
| } |
| ], |
| "publisher": { |
| "@type": "sc:Organization", |
| "name": "Michigan State University" |
| }, |
| "citeAs": "@inproceedings{kwon2026forcebody, title={ForceBody: Force-Paired Parametric Body Motion with Torque Uncertainty}, author={Kwon, Joonwoo and Zhang, Yufei and Liu, Xiaoming and Cui, Zijun}, booktitle={Advances in Neural Information Processing Systems (NeurIPS), Evaluations and Datasets Track}, year={2026}}", |
| "rai:dataLimitations": "ForceBody is limited to the 140 subjects and 10 source studies it takes from AddBiomechanics. Walking and running make up 93.5% of trials (running 5,547, walking 4,167). Rare classes have few trials (activity_recovered standing 272, jumping 75, sit_stand 71, squat 24, stairs 22, and a mixed group of 208 trials in the classes yoga 86, gait_transition 64, sport 24, dance 21, taichi 9, stretch 2 and leg_exercise 2). Carter2023 contributes 7,006 trials (67.5%). SKEL parameters are numerical fits with mean per-joint error 21.6 mm against the AddBiomechanics joint centers. sigma_tau models joint-angle noise only and does not cover GRF and CoP error, segment inertia, or the axis mismatch between SKEL and the Rajagopal model. Torques inherit any error of the AddBiomechanics kinematics, skeleton and force data they are computed from.", |
| "rai:dataBiases": "Subjects are 75 male, 55 female and 10 unreported (vanderZee2022). Height 1.73 +/- 0.09 m, mass 68.8 +/- 11.5 kg, BMI 22.8 +/- 2.8. Mostly healthy adults. Non-healthy subjects are 1 post-stroke subject (Li2021, 65 trials) and 4 total knee arthroplasty subjects (Fregly2012, 78 trials). Activity and source imbalance as in dataLimitations. The 10 unreported-sex subjects are fitted with a SKEL sex model chosen by height (female below 1.683 m). sigma_q = 1.6 deg is applied isotropically to all 20 direct DOFs because AddBiomechanics reports only an aggregate angle error.", |
| "rai:personalSensitiveInformation": "No full names or contact details appear in any field. Subjects appear only as generic labels of the form study_S<NN> (for example Carter2023_S45). The AddBiomechanics subject labels are kept in name_map.csv (addb_subject). trial_name keeps the AddBiomechanics source trial names. All 240 Han2023 names contain a capture date, and the 78 Fregly2012 names contain subject initials. Height, mass, BMI, sex and age (18 to 86 years, unknown in 200 trials) come from the source studies. AddBiomechanics requires de-identified uploads. The data include health information. health_status is healthy (135 subjects, 10,243 trials), TKA (total knee arthroplasty, 4 subjects, 78 trials) or stroke (1 subject, 65 trials). health_detail gives TKA left knee (40 trials), TKA right knee (38 trials) or stroke, right-sided hemiparesis (65 trials). Gait and body-size data can help to re-identify a person. Do not attempt to re-identify subjects.", |
| "rai:dataUseCases": "Intended for non-commercial scientific research. Use cases are (i) supervised joint torque prediction from kinematics, (ii) uncertainty-aware regression that uses sigma_tau as a per-sample loss weight, (iii) ground reaction force prediction from kinematics, (iv) marker-based pose fitting and SKEL-fit benchmarks, and (v) physics-aware human motion modeling that requires force grounding rather than purely kinematic supervision. Not intended for clinical decision making, identification of persons, or commercial use. Construct and validity. The data measure per-frame joint torques and ground reaction forces paired with SKEL body motion. The GRF are force-plate measurements. The torques come from inverse dynamics with the cleaned measured GRF on the AddBiomechanics pass-2 skeleton. The SKEL fits have a mean per-joint error of 21.6 mm against the AddBiomechanics joint centers (qc_skel_fit_err_mm). The paper shows use case (i) with the torque benchmark baselines (Table 4), use case (iii) with the GRF baselines (Table 3) and use case (ii) with an uncertainty-weighted fine-tune (Table 5). Use cases (iv) and (v) are not evaluated in the paper.", |
| "rai:dataSocialImpact": "ForceBody is meant for physically grounded human motion modeling. Applications include biomechanical assessment, exoskeleton and prosthetic design, sports analytics, and physics-aware animation. sigma_tau gives the sensitivity of each torque label to joint-angle noise, which a model can use as a weight during training. The data are de-identified and released under CC BY-NC 4.0. SKEL-derived fields also follow the SKEL non-commercial license. The data include health labels for 5 subjects, and gait and body-size data can help to re-identify a person. Re-identification of subjects and clinical decisions are out of scope.", |
| "rai:hasSyntheticData": false, |
| "rai:dataCollection": "ForceBody does not collect new motion-capture data. Motion, force and torque records come from the public AddBiomechanics dataset (CC BY 4.0), which aggregates optical motion capture with synchronized force-plate ground reaction forces from 10 source studies. The source studies are responsible for the ethics approval of their data collection. Subject identities are replaced by generic labels.", |
| "rai:dataCollectionType": [ |
| "Secondary Data Analysis", |
| "Software Collection" |
| ], |
| "rai:dataCollectionRawData": "Source records are 378 AddBiomechanics .b3d files. Each file holds marker trajectories, inverse-kinematics joint angles, force-plate GRF and CoP, and inverse-dynamics torques on the OpenSim Rajagopal full-body model. The 10 source studies are Carter2023, Moore2015, Hamner2013, Falisse2017, Fregly2012, Han2023, Li2021, Tiziana2019, Uhlrich2023 and vanderZee2022.", |
| "rai:dataCollectionMissingData": "sigma_tau is computed for 10,382 of the 10,386 released trials. The other 4 trials are shorter than one period of the 6 Hz noise band, so their sigma_tau is 0 and has_uncertainty is False (mc_missing_reason). The sigma_tau statistics of the paper use the 8,732 trials with has_uncertainty True and GRF valid on at least 50% of frames (grf_valid_frac >= 0.5). Missing markers are NaN in markers fields. Frames with invalid force, CoP, torque or kinematics are flagged by the per-frame masks (grf_frame_ok, cop_frame_ok, tau_frame_ok, mc_frame_ok, kin_frame_ok) and are not imputed. In 14 trials force and motion capture are out of sync and could not be re-timed, so force_label_usable is False.", |
| "rai:dataPreprocessingProtocol": [ |
| "The default SKEL pose set (poses) is fitted to the AddBiomechanics inverse-kinematics pass (pass 0) to keep force labels out of kinematic inputs. A second pose set fitted to the dynamics pass (poses_dyn) is also released. The torque labels and sigma_tau are computed on the dynamics-pass joint angles (q_gt, or q_kin on the 27 re-timed trials).", |
| "The kinematics-pass target q_kin is AddBiomechanics pass 0 filtered with the same 2nd-order 30 Hz zero-lag Butterworth filter that AddBiomechanics applies for pass 1. q_kin reproduces the stored AddBiomechanics pass 1 in 8,218 trials (q_kin_pass1_match). q_kin_pass1_mismatch_reason gives the reason for the other 2,168 trials. 10,186 of the 10,386 trials (98.1%) are on a grid of 99 to 101 Hz. 8,848 of them were resampled from a capture rate of 120 to 251 Hz (field fps_native_capture), and 1,338 were captured at 100 or 101 Hz. The other 200 trials keep their native grid of 61 Hz (64 trials), 201 Hz (111 trials) or 250 Hz (25 trials). fps is the nominal rate. Time stamps use fps_true_grid.", |
| "Trials are quality-filtered at the 80th percentile of the unfiltered fitting error. 10,386 of 12,986 source trials (80.0%) are released.", |
| "Ground reaction force, CoP and free moment are cleaned (contact rule, plate re-zero, crossover, free-moment bound, raw-plate CoP, frame tilt and tail blanking). contact_status gives the result per frame and contact. The cleaned forces are released in the AddBiomechanics lab frame (grf, cop, contact_torque) and in the SKEL world frame (grf_aligned, cop_aligned_foot, contact_torque_aligned). Joint torques tau_selfconsistent are recomputed with the cleaned forces." |
| ], |
| "rai:dataManipulationProtocol": "Each manipulation below is recorded in the named field. (i) SKEL fit. AddBiomechanics motion is re-expressed in SKEL by the fitting described in dataAnnotationProtocol, once for each pose set (poses, poses_dyn). (ii) Resampling. 8,848 trials captured at 120 to 251 Hz are released on a resampled grid of 99 to 101 Hz, with kinematics, forces and markers on one grid per trial (fps_native_capture, fps_true_grid). (iii) Force cleaning. GRF, CoP and free moment are cleaned as described in dataPreprocessingProtocol (contact_status). In 270 trials the raw plate CoP is unusable and the CoP is a near-fixed lab point (qc_cop_fixed_point). (iv) Force re-timing. In 27 trials the force stream and grf_valid_mask are shifted in time to match the motion capture (skel_fit_target_dyn == kin_retimed, per-frame shift in grf_retimed_ms, median 277 ms, range -85 to 320 ms). In 14 trials that could not be re-timed, force_label_usable is False, and 1 trial has force invalid from force_invalid_from_frame. (v) Dynamics mass. In 491 trials (14 source files) the AddBiomechanics link masses are rescaled to agree with the measured GRF (mass_dyn_scale, already applied in mass_kg_dynamics). (vi) Torque label. tau_selfconsistent is recomputed from the released kinematics (q_gt, or q_kin on the 27 re-timed trials, field tau_sc_kinematics) and the cleaned forces, on the AddBiomechanics pass-2 skeleton, with an inverse-dynamics routine built on nimblephysics that re-implements the AddBiomechanics inverse dynamics (mc_engine). (vii) Arm re-solve. In 875 trials the AddBiomechanics pass-0 arm that parks on a joint limit or hops is re-solved by inverse kinematics to the markers before the 30 Hz filter (q_kin_source == addb_pass0_armfix_lp30). (viii) Pass-2 target repair. In 1,420 trials the poses_dyn fit target is a repaired pass-2 target (skel_fit_target_dyn addb_pass2_armsplice 9, addb_pass2_repaired_v3a 791, addb_pass2_repaired_v4s 620). 1,392 of them have modified frames, marked per frame and DOF in dyn_target_source (dyn_target_modified_frac). q_gt itself is unchanged. (ix) Head post-fit. In 1,948 trials with at least 2 head markers the head DOFs are fitted after the main fit (head_postfit). In the other 8,438 trials the head DOFs stay 0 (qc_head_untracked). (x) Study rename. Release 1.3.0 renames Hammer2013 to Hamner2013 in 40 trial keys (trial_uid_v12, uid_map_v12_to_v13.csv). The AddBiomechanics dynamics-pass angles (q_gt) and torques (tau_gt_det) are also released for reference, on the release grid. They are not usable on the 27 re-timed trials (q_gt_usable, tau_gt_det_usable).", |
| "rai:dataImputationProtocol": "Masked frames are not imputed and not set to NaN. Outside a mask the arrays keep their raw values, and a 0 there is not a measurement. Missing markers are NaN. During force cleaning some CoP values were filled, and contact_status 2 marks them. Frames with missing or invalid GRF, CoP, torque or kinematics are flagged by per-frame masks (grf_valid_mask, grf_frame_ok, cop_frame_ok, tau_frame_ok, mc_frame_ok, kin_frame_ok). Apply these masks before use.", |
| "rai:dataAnnotationProtocol": "Annotation is automated in two layers. (i) SKEL fit. Stage 1 estimates one 10-dimensional shape per subject by matching eight bilateral bone lengths (pelvis to hip, thigh, shank, forearm), with terms for the recorded height and a subject mass target. Stage 2 fixes the shape and fits per-frame pose (46 DOFs) and translation with a joint-position loss on the 15 directly matched joints, a marker loss, anatomical regularizers on the spine, scapula and humerus, and temporal smoothness. Stage 2 runs once on the kinematics-pass target (poses) and once on the dynamics-pass target (poses_dyn). (ii) Torque uncertainty. The AddBiomechanics dynamics-pass joint angles (q_gt, or q_kin on the 27 re-timed trials) at the 20 direct DOFs of 14 joints are perturbed with band-limited Gaussian noise (sigma_q = 1.6 deg, 6 Hz), each sample is passed through the inverse-dynamics routine that computes tau_selfconsistent with the cleaned measured GRF held fixed, and the per-DOF mean and standard deviation over N = 1000 samples are stored. sigma_q = 1.6 deg is the joint-angle RMSE that AddBiomechanics reports for its inverse kinematics on synthetic walking data. No human annotators are involved.", |
| "rai:dataAnnotationPlatform": "No annotation platform or labeling service. SKEL fitting and Monte Carlo sampling run as Python scripts on research servers.", |
| "rai:dataAnnotationAnalysis": "Each trial stores mu_tau and sigma_tau per frame and DOF. The Monte Carlo percentiles are not part of the public release. The standard error of sigma_tau is 7.1% at N = 100, 3.2% at N = 500 and 2.2% at N = 1000.", |
| "rai:annotationsPerItem": "Each trial carries one SKEL shape per subject and two SKEL pose sets with root translation per frame (poses and trans fitted to the kinematics pass, poses_dyn and trans_dyn fitted to the dynamics pass), the cleaned AddBiomechanics GRF, CoP and free moment, one torque label tau_selfconsistent per frame and DOF, and the Monte Carlo mean mu_tau and standard deviation sigma_tau from N = 1000 samples per frame. The joint torque of the paper and of the benchmark is tau_selfconsistent. The AddBiomechanics dynamics-pass torques are released as tau_gt_det for reference.", |
| "rai:annotatorDemographics": "No human annotators. All annotations were produced by the automated SKEL fitting and Monte Carlo pipeline.", |
| "rai:machineAnnotationTools": [ |
| "SKEL body model and a Python fitting pipeline (Stage 1 shape, Stage 2 pose and translation).", |
| "An inverse-dynamics routine built on nimblephysics that re-implements the AddBiomechanics inverse dynamics, used for tau_selfconsistent and the Monte Carlo samples.", |
| "scipy.signal Butterworth filters." |
| ], |
| "rai:dataReleaseMaintenancePlan": "Released as version 1.3.0 on Hugging Face (kwonjoon/ForceBody), with code at https://github.com/DominoAI-Lab/ForceBody-NeurIPS-ED-2026. Fixes are issued as semantic-versioned releases on the same repository with a CHANGELOG.md entry and MD5SUMS.txt. Data under CC BY-NC 4.0. SKEL-derived fields also follow the SKEL non-commercial license. Code under MIT.", |
| "prov:wasDerivedFrom": [ |
| { |
| "@type": "sc:Dataset", |
| "name": "AddBiomechanics dataset", |
| "description": "Werling, K., Kaneda, J., Tan, T., Agarwal, R., Skov, S., Van Wouwe, T., Uhlrich, S., Bianco, N., Ong, C., Falisse, A., et al. AddBiomechanics dataset: Capturing the physics of human motion at scale. ECCV 2024.", |
| "url": "https://addbiomechanics.org/", |
| "license": "https://spdx.org/licenses/CC-BY-4.0.html" |
| } |
| ], |
| "prov:wasGeneratedBy": "AddBiomechanics motion in the Rajagopal skeleton was re-expressed in SKEL by a two-stage fit. Stage 1 fits one shape per subject from bone lengths, height and mass. Stage 2 fits per-frame pose and translation on the 15 directly matched joints with marker, anatomical and temporal terms, once to the kinematics pass (poses) and once to the dynamics pass (poses_dyn). GRF, CoP and free moment were cleaned. The torque label tau_selfconsistent was recomputed from the released kinematics and the cleaned forces with an inverse-dynamics routine built on nimblephysics that re-implements the AddBiomechanics inverse dynamics. sigma_tau comes from 1000-sample Monte Carlo perturbation of the dynamics-pass joint angles (band-limited Gaussian, sigma_q = 1.6 deg, 6 Hz, 20 direct DOFs of 14 joints) through the same routine with the cleaned measured GRF held fixed.", |
| "distribution": [ |
| { |
| "@type": "cr:FileObject", |
| "@id": "huggingface-repo", |
| "name": "huggingface-repo", |
| "description": "Hugging Face dataset repository kwonjoon/ForceBody. The repository as a whole has no file checksum. The sha256 value points to Croissant issue 80, as in the Croissant reference examples for git repositories. MD5SUMS.txt lists the md5 of every data file.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody", |
| "encodingFormat": "git+https", |
| "sha256": "https://github.com/mlcommons/croissant/issues/80" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "manifest.csv", |
| "name": "manifest.csv", |
| "description": "Per-trial manifest, one row per trial (10,386 rows).", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/manifest.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "708f96dd0ce4c53e8fe17c0cbf71079908c0c479356978f123925a1e4dfde819" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "manifest_train.csv", |
| "name": "manifest_train.csv", |
| "description": "Train split of manifest.csv (9,472 rows, 121 subjects). It holds the 12 validation subjects (1,098 trials, split_addb_val == val).", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/manifest_train.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "f5dec7406223c71cf9af84b656aa207de7098c3439c7ba3de3e49b17cc961d71" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "manifest_test.csv", |
| "name": "manifest_test.csv", |
| "description": "Test split of manifest.csv (914 rows, 19 subjects).", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/manifest_test.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "57dd8b922d76351376196c448a85c59c0a1547951e80e88b31760a862c6ec69d" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "persons.csv", |
| "name": "persons.csv", |
| "description": "One row per subject (140 rows) with the SKEL shape betas, sex, height and splits.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/persons.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "a6710619838103a2feec172fee523b561a54f6f0188c7cb5874f05128b6b78ad" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "subjects.csv", |
| "name": "subjects.csv", |
| "description": "Per-subject metadata summary (140 rows, v1.1 layout with v1.2 values). Its n_with_uncertainty column is the v1.1 count (8,652 trials in total). For release 1.3.0 use has_uncertainty in manifest.csv (10,382 trials).", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/subjects.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "f8072afaf863474a4b151575d5e6b28d50c74ebdd2004ada67ca0582658a4c84" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "SCHEMA_v1.3.csv", |
| "name": "SCHEMA_v1.3.csv", |
| "description": "Dtype, shape, unit, frame and description of every field.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/SCHEMA_v1.3.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "9c2e97d950684ea61006d47e9ca12041f669a1238f90004d63a10fbdb5abfcfc" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "gait_events.csv", |
| "name": "gait_events.csv", |
| "description": "GRF heel strikes and toe-offs of each foot on walking and running trials with usable force labels (343,553 rows, 8,940 trials), frame on the release grid. The other 760 of the 9,700 walking or running trials with usable force labels have no rows. 732 of them have no heel strike or toe-off in grf_contact_state, and 28 fail the cadence consistency gate (qc_gait_event_inconsistent).", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/gait_events.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "b881938d4de958cdd0ca1f5dc9b93024abe60e3977b24a04123d71f166f37843" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "name_map.csv", |
| "name": "name_map.csv", |
| "description": "trial_uid to AddBiomechanics source file and trial (10,386 rows). The split column is the AddBiomechanics source split, not split_addb.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/name_map.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "fb36b21172281cb04a4b2da9435c370b7e258a29c4ded6a9a2898a380683516a" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "name_map.json", |
| "name": "name_map.json", |
| "description": "Same content as name_map.csv as a JSON list.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/name_map.json", |
| "encodingFormat": "application/json", |
| "sha256": "6c941dcab0863a075bbc54d3cb4c3724ed1e020bc28e44dbb7068902896f176a" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "uid_map_v12_to_v13.csv", |
| "name": "uid_map_v12_to_v13.csv", |
| "description": "The 40 trial keys and paths renamed in 1.3.0 (Hammer2013 to Hamner2013).", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/uid_map_v12_to_v13.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "b8426a679c0413c6489f3b31cc315a64f7fd3604c86f4029d4a9c1a930359c02" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "marker_vertex_map.json", |
| "name": "marker_vertex_map.json", |
| "description": "Motion-capture marker name to SKEL skin vertex index used by the fit.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/marker_vertex_map.json", |
| "encodingFormat": "application/json", |
| "sha256": "7eff6ed14682f68c613b1c29b4f1ccd82d552080e277cbc5fef784eadaeb9b65" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "models/models_index.csv", |
| "name": "models/models_index.csv", |
| "description": "Index of the 756 OpenSim model files (source b3d file, processing pass and path).", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/models/models_index.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "69fdc999d627fb19d23c69ea9d0674f01d6942ec862a489f224f0a6282ba31ca" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "models/body_segments.csv", |
| "name": "models/body_segments.csv", |
| "description": "Segment masses and local centre-of-mass positions of every body of the 756 OpenSim models.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/models/body_segments.csv", |
| "encodingFormat": "text/csv", |
| "sha256": "1c6b55efd914f4b14061153ee63e2a6edbd4b0a5d0a7847c98b750b065317d30" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "README.md", |
| "name": "README.md", |
| "description": "Dataset card.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/README.md", |
| "encodingFormat": "text/markdown", |
| "sha256": "b277a3e5e5b47eae3f33edb7400f882658b28b48cd6a28071453f71e58f90f54" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "DETAILS.md", |
| "name": "DETAILS.md", |
| "description": "Full documentation of masks, conventions and known issues.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/DETAILS.md", |
| "encodingFormat": "text/markdown", |
| "sha256": "7bbc52a7990dccc599e247e756aef4e3258ddc766ce65b2c6406d538cc5163e0" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "CHANGELOG.md", |
| "name": "CHANGELOG.md", |
| "description": "Release history.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/CHANGELOG.md", |
| "encodingFormat": "text/markdown", |
| "sha256": "1345574eef9fe70e6c1b4c560e84d84441bc4b8bdff0491be3c8cc1492fe9e31" |
| }, |
| { |
| "@type": "cr:FileObject", |
| "@id": "MD5SUMS.txt", |
| "name": "MD5SUMS.txt", |
| "description": "MD5 of every data file and of README.md, DETAILS.md and CHANGELOG.md. croissant.json, LICENSE.md and the card images in assets/ are not listed.", |
| "contentUrl": "https://huggingface.co/datasets/kwonjoon/ForceBody/resolve/main/MD5SUMS.txt", |
| "encodingFormat": "text/plain", |
| "sha256": "74f431090ab5453676174d9a8c7f5318f1acdba9aa447557af75e206824db2ac" |
| }, |
| { |
| "@type": "cr:FileSet", |
| "@id": "trial-npz", |
| "name": "trial-npz", |
| "containedIn": { |
| "@id": "huggingface-repo" |
| }, |
| "description": "One NumPy .npz per trial at trials/<study>/S<NN>/<trial_uid>.npz (10,386 files, 547 core fields each). Fields are listed in SCHEMA_v1.3.csv.", |
| "encodingFormat": "application/x-npz", |
| "includes": "trials/*/*/*.npz" |
| }, |
| { |
| "@type": "cr:FileSet", |
| "@id": "opensim-models", |
| "name": "opensim-models", |
| "containedIn": { |
| "@id": "huggingface-repo" |
| }, |
| "description": "AddBiomechanics scaled OpenSim models, one per source b3d file and processing pass (passes 0 and 2), 756 files for 378 b3d files. The pass-2 model is the skeleton of the torque labels. models/models_index.csv maps each file to its b3d file and pass.", |
| "encodingFormat": "application/gzip", |
| "includes": "models/*/*.osim.gz" |
| } |
| ], |
| "recordSet": [ |
| { |
| "@type": "cr:RecordSet", |
| "@id": "trials", |
| "name": "trials", |
| "key": { |
| "@id": "trials/trial_uid" |
| }, |
| "description": "One record per trial, from manifest.csv. Arrays (poses, poses_dyn, betas, trans, grf_aligned, tau_selfconsistent, sigma_tau, frame masks) are in the trial npz at npz_path.", |
| "field": [ |
| { |
| "@type": "cr:Field", |
| "@id": "trials/trial_uid", |
| "name": "trial_uid", |
| "description": "Unique trial id, also the npz file name.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "trial_uid" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/person_id", |
| "name": "person_id", |
| "description": "Subject id (140 values).", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "person_id" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/study", |
| "name": "study", |
| "description": "Source study.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "study" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/split_addb", |
| "name": "split_addb", |
| "description": "Benchmark split (train or test), subject level.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "split_addb" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/split_addb_val", |
| "name": "split_addb_val", |
| "description": "Benchmark split with the validation subjects (train, val, test). val holds 12 subjects of the split_addb train set.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "split_addb_val" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/activity_name", |
| "name": "activity_name", |
| "description": "Activity name.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "activity_name" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/activity_recovered", |
| "name": "activity_recovered", |
| "description": "Activity class.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "activity_recovered" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/sex", |
| "name": "sex", |
| "description": "Subject sex (male, female, unknown).", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "sex" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/age", |
| "name": "age", |
| "description": "Subject age in years if reported.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "age" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/height_m", |
| "name": "height_m", |
| "description": "Subject height (m).", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "height_m" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/mass_kg", |
| "name": "mass_kg", |
| "description": "Recorded subject mass (kg).", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "mass_kg" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/mass_kg_dynamics", |
| "name": "mass_kg_dynamics", |
| "description": "Mass used for the inverse dynamics (kg). Divide torques by it to get Nm/kg.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "mass_kg_dynamics" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/bmi", |
| "name": "bmi", |
| "description": "Body mass index.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "bmi" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/health_status", |
| "name": "health_status", |
| "description": "Health status of the subject (healthy, TKA for total knee arthroplasty, or stroke). Health information.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "health_status" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/health_detail", |
| "name": "health_detail", |
| "description": "Health detail of the subject (healthy, TKA left knee, TKA right knee, or stroke, right-sided hemiparesis). Health information.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "health_detail" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/num_frames", |
| "name": "num_frames", |
| "description": "Number of frames.", |
| "dataType": "sc:Integer", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "num_frames" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/fps", |
| "name": "fps", |
| "description": "Nominal release frame rate (Hz). Use fps_true_grid for time stamps.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "fps" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/fps_native_capture", |
| "name": "fps_native_capture", |
| "description": "Capture rate of the source trial (Hz). It differs from fps in the 8,848 resampled trials.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "fps_native_capture" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/fps_true_grid", |
| "name": "fps_true_grid", |
| "description": "True rate of the release grid (Hz). Frame i is at time i / fps_true_grid.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "fps_true_grid" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/duration_s", |
| "name": "duration_s", |
| "description": "Trial duration (s).", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "duration_s" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/has_uncertainty", |
| "name": "has_uncertainty", |
| "description": "True if Monte Carlo sigma_tau was computed. False for 4 trials shorter than one 6 Hz period, where sigma_tau is 0.", |
| "dataType": "sc:Boolean", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "has_uncertainty" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/grf_valid_frac", |
| "name": "grf_valid_frac", |
| "description": "Fraction of frames with valid GRF.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "grf_valid_frac" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/force_label_usable", |
| "name": "force_label_usable", |
| "description": "Trial-level flag for force labels.", |
| "dataType": "sc:Boolean", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "force_label_usable" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/torque_label_usable", |
| "name": "torque_label_usable", |
| "description": "Trial-level flag for torque labels.", |
| "dataType": "sc:Boolean", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "torque_label_usable" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/eval_stratum", |
| "name": "eval_stratum", |
| "description": "Evaluation stratum of the benchmark (healthy, or pathological for the TKA and stroke subjects).", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "eval_stratum" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/npz_path", |
| "name": "npz_path", |
| "description": "Path of the trial file inside the repository.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "npz_path" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "trials/dataset_version", |
| "name": "dataset_version", |
| "description": "Release version.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "manifest.csv" |
| }, |
| "extract": { |
| "column": "dataset_version" |
| } |
| } |
| } |
| ] |
| }, |
| { |
| "@type": "cr:RecordSet", |
| "@id": "persons", |
| "name": "persons", |
| "key": { |
| "@id": "persons/person_id" |
| }, |
| "description": "One record per subject, from persons.csv.", |
| "field": [ |
| { |
| "@type": "cr:Field", |
| "@id": "persons/person_id", |
| "name": "person_id", |
| "description": "Subject id.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "person_id" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/study", |
| "name": "study", |
| "description": "Source study.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "study" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/sex", |
| "name": "sex", |
| "description": "Subject sex.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "sex" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/height_m", |
| "name": "height_m", |
| "description": "Subject height (m).", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "height_m" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/beta_0", |
| "name": "beta_0", |
| "description": "SKEL shape coefficient beta_0.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "beta_0" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/beta_1", |
| "name": "beta_1", |
| "description": "SKEL shape coefficient beta_1.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "beta_1" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/beta_2", |
| "name": "beta_2", |
| "description": "SKEL shape coefficient beta_2.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "beta_2" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/beta_3", |
| "name": "beta_3", |
| "description": "SKEL shape coefficient beta_3.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "beta_3" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/beta_4", |
| "name": "beta_4", |
| "description": "SKEL shape coefficient beta_4.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "beta_4" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/beta_5", |
| "name": "beta_5", |
| "description": "SKEL shape coefficient beta_5.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "beta_5" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/beta_6", |
| "name": "beta_6", |
| "description": "SKEL shape coefficient beta_6.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "beta_6" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/beta_7", |
| "name": "beta_7", |
| "description": "SKEL shape coefficient beta_7.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "beta_7" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/beta_8", |
| "name": "beta_8", |
| "description": "SKEL shape coefficient beta_8.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "beta_8" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/beta_9", |
| "name": "beta_9", |
| "description": "SKEL shape coefficient beta_9.", |
| "dataType": "sc:Float", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "beta_9" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/split_addb", |
| "name": "split_addb", |
| "description": "Benchmark split.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "split_addb" |
| } |
| } |
| }, |
| { |
| "@type": "cr:Field", |
| "@id": "persons/skel_gender", |
| "name": "skel_gender", |
| "description": "SKEL sex model used for fitting.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileObject": { |
| "@id": "persons.csv" |
| }, |
| "extract": { |
| "column": "skel_gender" |
| } |
| } |
| } |
| ] |
| } |
| ] |
| } |
