Datasets:
Tasks:
Other
Modalities:
Text
Formats:
webdataset
Languages:
English
Size:
< 1K
Tags:
electromyography
emg
motor-unit-decomposition
blind-source-separation
dynamic-contraction
Synthetic
License:
| { | |
| "name": "muniverse-dynamic-v2", | |
| "version": "1.0", | |
| "description": "Non-stationary dynamic EMG benchmark for motor unit decomposition. 336 recordings spanning 3 pool-size tiers (26-113 MUs), 5 subjects, 7 muscle types, 8 conditions (sinusoid/triangular angle × 2 difficulties × 2 SNR).", | |
| "source_package": "muniverse", | |
| "source_repo_url": "https://github.com/dfarinagroup/muniverse", | |
| "generation_pipeline": [ | |
| "Step 1: Generate MUAP caches via NeuroMotion+BioMime container (one per subject × muscle at Flexion-Extension DOF, 130 angle steps)", | |
| "Step 2: Analyze pairwise MUAP cosine similarity, select clean MU subsets via greedy filtering at given threshold", | |
| "Step 3: Write clean caches (same format as original, fewer MUs)", | |
| "Step 4: Generate recordings by running container on clean caches with specified conditions", | |
| "Step 5: (bug fix) Regenerate triangular-angle recordings with symmetric triangle patch" | |
| ], | |
| "muap_generation": { | |
| "subjects": [ | |
| {"seed": 0, "fibre_density": 194.0, "muscle_motor_unit_counts": [206, 210, 181, 187, 141, 486, 154]}, | |
| {"seed": 1, "fibre_density": 187.0, "muscle_motor_unit_counts": [176, 176, 208, 167, 168, 340, 135]}, | |
| {"seed": 2, "fibre_density": 190.0, "muscle_motor_unit_counts": [186, 217, 164, 178, 153, 437, 192]}, | |
| {"seed": 3, "fibre_density": 174.0, "muscle_motor_unit_counts": [167, 224, 198, 186, 157, 420, 189]}, | |
| {"seed": 4, "fibre_density": 196.0, "muscle_motor_unit_counts": [194, 205, 198, 205, 187, 408, 163]} | |
| ], | |
| "muscles": ["PL", "FDSI", "EDI", "ECU", "ECRB", "ECRL", "FCU_h", "FCU_u"], | |
| "movement_dof": "Flexion-Extension", | |
| "total_caches": 40, | |
| "container_image": "pranavm19/muniverse-test:neuromotion", | |
| "muscle_label_slot_notes": { | |
| "FCU_u": "Replaces FCU slot in MuscleLabels list (custom)", | |
| "FCU_h": "Replaces FCU slot in MuscleLabels list (custom)", | |
| "standard_labels": ["ECRB", "ECRL", "ECU", "EDI", "PL", "FCU", "FDSI"] | |
| } | |
| }, | |
| "crosstalk_filtering": { | |
| "method": "greedy_henneman_order", | |
| "similarity": "cosine_similarity at mid-pose (step 65), flattened over channels × time", | |
| "description": "Starting with MU 0 (smallest), add MU i if max(sim(i, j)) < threshold for all j already selected" | |
| }, | |
| "combos": [ | |
| {"tier": "small", "subject_seed": 0, "muscle": "PL", "threshold": 0.85, "clean_N": 27}, | |
| {"tier": "small", "subject_seed": 2, "muscle": "PL", "threshold": 0.85, "clean_N": 26}, | |
| {"tier": "small", "subject_seed": 4, "muscle": "PL", "threshold": 0.85, "clean_N": 30}, | |
| {"tier": "small", "subject_seed": 4, "muscle": "FCU_h", "threshold": 0.85, "clean_N": 36}, | |
| {"tier": "small", "subject_seed": 3, "muscle": "ECRL", "threshold": 0.85, "clean_N": 39}, | |
| {"tier": "small", "subject_seed": 0, "muscle": "FDSI", "threshold": 0.85, "clean_N": 45}, | |
| {"tier": "medium", "subject_seed": 2, "muscle": "ECU", "threshold": 0.85, "clean_N": 47}, | |
| {"tier": "medium", "subject_seed": 3, "muscle": "FDSI", "threshold": 0.85, "clean_N": 49}, | |
| {"tier": "medium", "subject_seed": 2, "muscle": "FDSI", "threshold": 0.85, "clean_N": 53}, | |
| {"tier": "medium", "subject_seed": 3, "muscle": "ECU", "threshold": 0.85, "clean_N": 55}, | |
| {"tier": "medium", "subject_seed": 0, "muscle": "EDI", "threshold": 0.85, "clean_N": 56}, | |
| {"tier": "medium", "subject_seed": 3, "muscle": "EDI", "threshold": 0.85, "clean_N": 62}, | |
| {"tier": "medium", "subject_seed": 0, "muscle": "ECRB", "threshold": 0.85, "clean_N": 71}, | |
| {"tier": "medium", "subject_seed": 0, "muscle": "FCU_u", "threshold": 0.85, "clean_N": 74}, | |
| {"tier": "large", "subject_seed": 3, "muscle": "FCU_u", "threshold": 0.85, "clean_N": 77}, | |
| {"tier": "large", "subject_seed": 2, "muscle": "EDI", "threshold": 0.90, "clean_N": 80}, | |
| {"tier": "large", "subject_seed": 1, "muscle": "ECU", "threshold": 0.90, "clean_N": 84}, | |
| {"tier": "large", "subject_seed": 4, "muscle": "EDI", "threshold": 0.90, "clean_N": 93}, | |
| {"tier": "large", "subject_seed": 2, "muscle": "ECRB", "threshold": 0.90, "clean_N": 96}, | |
| {"tier": "large", "subject_seed": 3, "muscle": "FCU_u", "threshold": 0.90, "clean_N": 112}, | |
| {"tier": "large", "subject_seed": 1, "muscle": "FCU_u", "threshold": 0.90, "clean_N": 113} | |
| ], | |
| "conditions": { | |
| "SA05-hi": {"angle_profile": "Sinusoid", "af": 0.5, "sin_amplitude_deg": 32.5, "noise_level_db": 25}, | |
| "SA05-lo": {"angle_profile": "Sinusoid", "af": 0.5, "sin_amplitude_deg": 32.5, "noise_level_db": 20}, | |
| "SA10-hi": {"angle_profile": "Sinusoid", "af": 1.0, "sin_amplitude_deg": 65.0, "noise_level_db": 25}, | |
| "SA10-lo": {"angle_profile": "Sinusoid", "af": 1.0, "sin_amplitude_deg": 65.0, "noise_level_db": 20}, | |
| "TA05-hi": {"angle_profile": "Triangular", "af": 0.5, "sin_amplitude_deg": 32.5, "noise_level_db": 25}, | |
| "TA05-lo": {"angle_profile": "Triangular", "af": 0.5, "sin_amplitude_deg": 32.5, "noise_level_db": 20}, | |
| "TA10-hi": {"angle_profile": "Triangular", "af": 1.0, "sin_amplitude_deg": 65.0, "noise_level_db": 25}, | |
| "TA10-lo": {"angle_profile": "Triangular", "af": 1.0, "sin_amplitude_deg": 65.0, "noise_level_db": 20} | |
| }, | |
| "fixed_recording_parameters": { | |
| "effort_level_pct": 50, | |
| "effort_profile": "Constant", | |
| "sin_frequency_hz": 0.3, | |
| "duration_s": 10, | |
| "sampling_frequency_hz": 2048, | |
| "target_angle_deg": 0, | |
| "n_electrodes": 320, | |
| "electrode_grid": "10 rows × 32 cols", | |
| "inter_electrode_distance_mm": 8, | |
| "filter": {"type": "Butterworth", "cutoff_hz": 800, "order": 4}, | |
| "noise_model": "amplitude-based additive Gaussian, std = std(emg) * 10^(-snr_db/20)" | |
| }, | |
| "channel_configs": { | |
| "ch070": {"n_cols": 7, "n_channels": 70, "description": "7 columns × 10 rows centered on max-RMS column"}, | |
| "ch320": {"n_cols": 32, "n_channels": 320, "description": "Full grid, no subsampling"} | |
| }, | |
| "recording_count": { | |
| "combos": 21, | |
| "conditions_per_combo": 8, | |
| "channel_configs": 2, | |
| "total": 336 | |
| }, | |
| "data_format": "See BENCHMARK_DATA_FORMAT.md — npz with emg (T, M), spike_mu_{i} arrays, metadata scalars", | |
| "known_issues_fixed": [ | |
| "Initial v2 generation had a bug in NeuroMotion's Triangular angle profile (TargetAngle=0, RampDuration=0 yielded flat 0° signal). Fixed via scripts/patches/neuromotion_triangular_symmetric.patch which replaces the Triangular branch with a symmetric triangle wave using SinAmplitude + SinFrequency (matching Sinusoid's range and period). 168 triangular recordings regenerated." | |
| ] | |
| } | |