datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Project_FatigueFatigueSense
FatigueSense Training Data
Domain-specific recordings and derived training artifacts for the FatigueSense
fatigue-detection pipeline. This dataset supports YOLO11n-pose retraining
(upper-body keypoints) and BiGRU temporal model training (1 Hz feature windows).
Contents
Path
Used by
Description
pose/
model_architecture.train_yolo_pose
YOLO-pose images + labels (5 kpts: nose, ears, shoulders). Pseudo-labeled with yolo11n-pose.pt.
pose/dataset.yaml
Ultralytics… See the full description on the dataset page: https://huggingface.co/datasets/Jlords32/FatigueSense.temporal_datasetMuscle_Fatigue_CyclingThis dataset was created with healthy participants aged between 18 and 25 years old. The participants in this dataset were not frequent athletes.
The dataset consists of 8 EMG signals recorded from the domineering foot of each participant during a cycling trial. The participants performed exercises on a conditioned cycle, alternating with short periods of high-intensity sprints. When a participant could no longer sustain the sprint intensity, this was considered the first index of fatigue and… See the full description on the dataset page: https://huggingface.co/datasets/YominE/Muscle_Fatigue_Cycling.fatigue-detection-v3fatigue-injection-pi0.5-cube-stacking
fatigue-injection-pi0.5-cube-stacking
Franka Panda cube-stacking rollouts collected while a square-wave "fatigue" perturbation was injected
into the commanded end-effector motion. Five datasets, one per perturbation magnitude, so the effect of
perturbation strength can be studied at a fixed task and policy.
Rollouts were produced by a π0.5 policy served over openpi_client; only successful episodes were kept.
Subsets
Each subfolder is a standalone LeRobot dataset… See the full description on the dataset page: https://huggingface.co/datasets/SinjaeKang/fatigue-injection-pi0.5-cube-stacking.epl-inplay-quad-fatigue-sub-error-collapse-v0.1EPL In-Play Quad Fatigue Substitution Error Collapse v0.1
What this dataset is
You test whether a model can detect late-game defensive collapse.
Each row represents a defending team state in minute 65 to 95.
Core quad coupling
Sprint intensityMinutes since last substitutionDefensive duel successError rate
The label asks
Will this team concede a goal in the next 120 seconds
Why this matters
Late goals decide matches.
Defensive collapse is usually a coupling failure between fatigue and… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/epl-inplay-quad-fatigue-sub-error-collapse-v0.1.muscle_fatigue_cycling
Muscle Fatigue Cycling EMG (TsFile)
This dataset is an Apache TsFile conversion of
YominE/Muscle_Fatigue_Cycling.
Modalities: Time-series.
Overview
Healthy participants aged 18–25 performed cycling trials with alternating high-intensity sprints.
8 EMG signals recorded from the dominant leg; Target is the fatigue label.
3 participants; each is a device identified by the patient TAG.
Converted observations: 3,002,137 rows across 1 TsFile file(s)
Source format:… See the full description on the dataset page: https://huggingface.co/datasets/THULab/muscle_fatigue_cycling.meta-fatigue-grpo-dataset
Meta Fatigue Detection GRPO Dataset
A specialized dataset for training language models using GRPO (Group Relative Policy Optimization) on Meta advertising fatigue detection with critical thinking reasoning.
Dataset Description
This dataset contains 200 high-quality prompt-response pairs focused on diagnosing, analyzing, and strategizing around creative fatigue in Meta (Facebook/Instagram) advertising campaigns.
Key Features
🧠 Critical Thinking Format:… See the full description on the dataset page: https://huggingface.co/datasets/Sri-Vigneshwar-DJ/meta-fatigue-grpo-dataset.fatigue-detectionpose_datasetpremier-league-fatigue-driven-decision-space-collapse-detection-v0.1What this dataset tests
Whether a system can detect fatigue-driven collapseof player decision-space in live match contexts.
Required outputs
decision-space collapse percent
collapse onset timestamp
collapse signature
predictability spike index
error likelihood uplift
cognitive-fatigue-repro-resultsfatigue-detection-v2huberman_lab_AMA_8_Balancing_Caffeine_Decision_Fatigue__Social_Isolationmlb-bullpen-usage-fatigue-research-sample
MLB Bullpen Usage and Fatigue Dataset for Run Prevention Research
Question this dataset helps answer:
Which MLB teams historically enter games with fresh or taxed bullpens, and how does recent reliever workload relate to late-inning run prevention before first pitch?
This dataset helps sports-betting researchers, fantasy baseball analysts, and dashboard builders compare, screen, and investigate MLB bullpen freshness using reliever reuse counts, rolling bullpen workload… See the full description on the dataset page: https://huggingface.co/datasets/Karmane/mlb-bullpen-usage-fatigue-research-sample.Yawning_due_to_fatigue_while_driving_inside_the_carfusion-pfc-erosion-fatigue-decoupling-drift-detection-v0.1Dataset goal
Detect surface–bulk decoherence in plasma-facing components.
The failure mode is not “heat flux high.”
It is:
erosion rate stops tracking crack growth
crack propagation accelerates without proportional surface signal
thermal cycling no longer predicts damage accumulation
Inputs
Per shot or short window:
edge heat flux and particle flux
surface temperature
erosion rate
crack density and crack growth rate
baseline coherence score
Required outputs
drift_gradient
decoherence_score… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/fusion-pfc-erosion-fatigue-decoupling-drift-detection-v0.1.football-latent-cross-coupling-pressing-fatigue-breakdown-v0.1
What this repo does
This dataset detects hidden instability in high-press football systems before visible breakdown occurs.
It identifies when pressing intensity and fatigue are interacting in a way that will lead to structural collapse.
Core structure
This dataset models:
latent instability under sustained pressing
fatigue accumulation
transition exposure
cross-coupled breakdown risk
Prediction target
Binary:
1 → pressing system likely to break down due to… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/football-latent-cross-coupling-pressing-fatigue-breakdown-v0.1.f1-quad-pit-duration-crew-fatigue-race-pressure-weather-variability-pit-error-v0.1What this repo does
This dataset models pit stop failure risk in Formula One. It predicts when the interaction between stop duration strain, cumulative crew fatigue, race pressure intensity, and weather variability produces elevated probability of pit execution error.
Core quad
pit_duration_s
crew_fatigue_index
race_pressure_index
weather_variability_index
Prediction target
label_pit_error
Binary forward label predicting unsafe release, delayed wheel fit, or procedural error during the pit… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/f1-quad-pit-duration-crew-fatigue-race-pressure-weather-variability-pit-error-v0.1.nba-player-load-fatigue-coherence-risk-v0.1What this repo is for
Detect fatigue risk before late-game drop.
Focus
travel and schedule density
rest days and back-to-backs
minutes trend
intensity bursts
late game efficiency
soreness markers
Why it matters
Fatigue shows up late.
Dense schedule plus rising minutes is the warning.
clinical-quad-epro-compliance-diary-fatigue-backfill-endpoint-reliability-loss-v0.1Clinical Quad ePRO Compliance Diary Fatigue Backfill Endpoint Reliability Loss v0.1
Each row is a site monthly snapshot.
Core quad
ePRO complianceDiary fatigueBackfill entriesEndpoint reliability loss
Target
label_primary_fail_next_90d
Files
data/train.csvdata/tester.csvscorer.py
Evaluation
Run model on data/tester.csvReturn predictions row alignedScore with scorer.py
License
MIT
This dataset identifies a measurable coupling pattern associated with systemic instability.
The sample demonstrates… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-epro-compliance-diary-fatigue-backfill-endpoint-reliability-loss-v0.1.Muscle_Fatigue_CyclingThis dataset was created with healthy participants aged between 18 and 25 years old. The participants in this dataset were not frequent athletes.
The dataset consists of 8 EMG signals recorded from the domineering foot of each participant during a cycling trial. The participants performed exercises on a conditioned cycle, alternating with short periods of high-intensity sprints. When a participant could no longer sustain the sprint intensity, this was considered the first index of fatigue and… See the full description on the dataset page: https://huggingface.co/datasets/tpzjade999/Muscle_Fatigue_Cycling.PMData-fatigue-rawsmart-material-coherence-drift-functional-fatigue-detection-v0.1Goal
Detect when a smart material starts losing function.
Core idea
Smart materials fail when stimulus and response stop coupling.
This dataset tests whether a model can detect that drift early.
Domains
shape memory alloys
self-healing polymers
electrochromic materials
Inputs
Healthy baseline signals plus evolving drift signals.
Required outputs
coherence_drift_rate
fatigue_onset_cycle
decoherence_type
functional_variance_growth
failure_probability
recommended_monitoring_action
Decoherence… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/smart-material-coherence-drift-functional-fatigue-detection-v0.1.Muscle_Fatigue_CyclingThis dataset was created with healthy participants aged between 18 and 25 years old. The participants in this dataset were not frequent athletes.
The dataset consists of 8 EMG signals recorded from the domineering foot of each participant during a cycling trial. The participants performed exercises on a conditioned cycle, alternating with short periods of high-intensity sprints. When a participant could no longer sustain the sprint intensity, this was considered the first index of fatigue and… See the full description on the dataset page: https://huggingface.co/datasets/Sams1357/Muscle_Fatigue_Cycling.mlb-bullpen-usage-fatigue-research
MLB Bullpen Usage and Fatigue Dataset for Run Prevention Research
Question this dataset helps answer:
Which MLB teams historically enter games with fresh or taxed bullpens, and how does recent reliever workload relate to late-inning run prevention before first pitch?
This dataset helps sports-betting researchers, fantasy baseball analysts, and dashboard builders compare, screen, and investigate MLB bullpen freshness using reliever reuse counts, rolling bullpen workload… See the full description on the dataset page: https://huggingface.co/datasets/Karmane/mlb-bullpen-usage-fatigue-research.FatigueNetatc-fatiguePMData-fatigue-raw-update