# IMEB-Exo Synthetic Time-Series Dataset v1.0.0

## Purpose
This repository artifact is a **fully synthetic, deterministic dataset** created to exercise and document the IMEB-Exo computational workflow for passive upper-limb exoskeleton research. It does **not** contain measurements from human participants and must not be interpreted as empirical evidence of discomfort, injury, tissue tolerance, or commercial-device performance.


## Creators
1. **Djunio Rosa de Melo Filho** — University of Campinas (UNICAMP), Brazil — d291223@dac.unicamp.br
2. **Anibal Tavares de Azevedo** — University of Campinas (UNICAMP), Brazil — atanibal@unicamp.br
3. **José Pereira Brittes** — University of Campinas (UNICAMP), Brazil — jose.brittes@fca.unicamp.br

**Dataset contact:** Djunio Rosa de Melo Filho (d291223@dac.unicamp.br).

## Funding context
- Funder: FAEPEX / Universidade Estadual de Campinas (UNICAMP)
- Process: 70262-26
- Project: *Métodos Multicritério Para Análise de Dados Monitorados No Uso de Exoesqueletos Passivos de Membros Superiores*

## Dataset design
- 24 virtual anthropometric models
- 3 overhead-assembly load scenarios: 0.5, 1.5, and 3.0 kg
- 2 conditions: `no_exo` and `passive_exo`
- 8 cycles per model/scenario/condition
- 6 s per cycle at 50 Hz (300 samples/cycle)
- 4 modeled attachment interfaces in the passive-exoskeleton condition: shoulder strap, upper-arm cuff, thoracic pad, waist belt
- Random seed: `7026226`
- Operational elevated-load threshold: `45.0 N` (synthetic analytical threshold only; **not clinical**)

## Core files
- `data/raw/kinematics_kinetics_timeseries.csv.gz`: OpenSim-compatible surrogate kinematic/kinetic time series.
- `data/raw/interface_timeseries.csv.gz`: long-format interface force and estimated mean-pressure time series.
- `data/processed/interface_cycle_metrics.csv`: per-cycle metrics used to construct multicriteria inputs.
- `data/processed/imeb_scores_by_model_scenario_interface.csv`: 288 region-level alternatives with IMEB-Exo scores/classes.
- `data/processed/critic_weights.csv`: CRITIC weights derived from the synthetic alternatives.
- `data/processed/interface_summary.csv`: overall interface ranking summary.
- `data/processed/scenario_interface_summary.csv`: ranking summary by load scenario.
- `imeb_exo_synthetic.sqlite`: SQLite copy of all major tables.
- `metadata/data_dictionary.csv`: variable definitions and units.
- `scripts/generate_synthetic_dataset.py`: reproducible generator.
- `scripts/compute_imeb_from_repository.py`: standalone recomputation of CRITIC/TOPSIS from processed metrics.

## Synthetic signal status
The time series mimic the *structure and units* expected from an OpenSim-centered workflow but are **not outputs of an executed OpenSim model**. They are deterministic surrogates generated from documented mathematical profiles plus seeded variability. Real OpenSim exports can replace these files without changing the data-processing architecture.

## IMEB-Exo criteria in v1.0.0
1. `f95_normal_N`
2. `frms_normal_N`
3. `impulse_normal_Ns`
4. `tangential_abs_p95_N`
5. `max_loading_rate_N_s`
6. `time_above_45N_pct`
`high_load_peak_count` is retained as a descriptive variable but is not part of the default v1.0.0 CRITIC/TOPSIS criterion set because discrete peak counts can dominate objective weighting in small or synthetic samples.

All selected criteria are treated as adverse/cost-type criteria. CRITIC weights are estimated across 288 alternatives (24 virtual models × 3 scenarios × 4 interfaces). TOPSIS is oriented so larger IMEB-Exo values indicate greater relative biomechanical criticality within this synthetic reference set.

## CCB-Exo operational classes
- Class 1: 0.00–<0.20 — Very low
- Class 2: 0.20–<0.40 — Low
- Class 3: 0.40–<0.60 — Moderate
- Class 4: 0.60–<0.80 — High
- Class 5: 0.80–1.00 — Very high / critical

These are operational classes only and are not validated discomfort or injury thresholds.

## DOI and citation
DOI: https://doi.org/10.5281/zenodo.22678689

**Recommended citation:**  
Djunio Rosa de Melo Filho, Anibal Tavares de Azevedo, and José Pereira Brittes. 2026. *IMEB-Exo Synthetic Time-Series Dataset for Passive Upper-Limb Exoskeleton Multicriteria Analysis*. Version 1.0.0. Research dataset. University of Campinas (UNICAMP). DOI: [10.5281/zenodo.22678689](https://doi.org/10.5281/zenodo.22678689).

## License
Suggested: CC BY 4.0 for data and MIT for code. Confirm institutional policy before deposit.