---
license: cc-by-4.0
task_categories:
- tabular-classification
- robotics
tags:
- imu
- biomechanics
- activity-recognition
- physical-ai
- sensor-certification
- opportunity-dataset
pretty_name: OPPORTUNITY — S2S Physics Certified
size_categories:
- 1K<n<10K
---

# OPPORTUNITY — S2S Physics Certified (v1.7.0)

Physics-certified windows from the OPPORTUNITY Activity Recognition dataset.
Validated against **8 biomechanical laws** using [S2S](https://github.com/timbo4u1/S2S).

## Two certifications provided

| File | Columns | Rejection | Notes |
|---|---|---|---|
| `opportunity_rua_certified.csv` | Documented RUA sensor (cols 10-12) | 14.4% | More accurate |
| `opportunity_certified.csv` | Auto-detected columns | 12.3% | Zero-config |

**Key finding:** Documented sensor columns give different results than auto-detection.
S2-ADL1 and S3-ADL1 show serious physics anomalies (20-22% pass rate).

## Statistics (RUA documented)

| Metric | Value |
|---|---|
| Total windows | 2,371 |
| Files | 24 (4 subjects × ADL1-5 + Drill) |
| Sample rate | 30.3Hz (auto-detected) |
| Window size | 256 samples |
| Overall rejection | 14.4% |
| Worst session | S2-ADL1: 78% rejected |
| Best session | S2-ADL3: 9% rejected |

## Key findings
S2-ADL1: 22% pass rate — serious sensor anomaly
S3-ADL1: 20% pass rate — serious sensor anomaly
S1-Drill: 79% pass — drill task cleanest
S2-ADL3/4/5: 90%+ pass — cleanest sessions

These anomalies are invisible to standard statistical checks.
S2S detects them through biomechanical law violations.

## Columns used (RUA documented)

From official OPPORTUNITY column documentation:
- Accel: cols 10-12 (Right Upper Arm accelerometer, milli-g)
- Gyro: cols 50-52 (Right Upper Arm gyroscope)

## Source dataset

Original OPPORTUNITY: https://archive.ics.uci.edu/dataset/226/opportunity+activity+recognition

4 subjects, 7 IMU sensors, 30Hz, daily activities + drill tasks.

## Citation
S2S Physics Certification Engine v1.7.0
https://github.com/timbo4u1/S2S
DOI: 10.5281/zenodo.18878307
pip install s2s-certify