Add dataset card README

README.md

@@ -1,3 +1,209 @@
 ---
 license: cc-by-4.0
+task_categories:
+  - other
+task_ids: []
+tags:
+  - gait-analysis
+  - biomechanics
+  - pose-estimation
+  - mediapipe
+  - blazepose
+  - wearable
+  - digital-health
+  - markerless
+  - movement-intelligence
+  - rehabilitation
+  - locomotion
+  - on-device-ml
+language:
+  - en
+size_categories:
+  - 1K<n<10K
+pretty_name: Arisole StrideIQ Gait Dataset (v0.1 Seed Release)
+dataset_info:
+  description: >
+    Markerless smartphone gait analysis dataset — 100+ sessions, 33-landmark
+    MediaPipe BlazePose poses, confidence-gated biomechanics, and Movement
+    Intelligence Index (MII) scores. Aggregate statistics only in v0.1; 
+    clip-level benchmark planned for v0.2.
 ---
+
+# Arisole StrideIQ Gait Dataset — v0.1 Seed Release
+
+> **Paper:** *Toward an Open, Privacy-Preserving Benchmark for Markerless Gait Analysis*  
+> **Authors:** Varun Srivastava, Arisole  
+> **Version:** 0.1 (Seed Release — aggregate statistics, no per-clip data)  
+> **License:** CC BY 4.0  
+> **DOI:** *(pending Zenodo assignment)*
+
+---
+
+## Dataset Summary
+
+The **Arisole StrideIQ Gait Dataset** is the first open, smartphone-native,
+markerless gait-analysis benchmark derived from real-world walking sessions
+captured entirely on consumer hardware — no wearables, no motion-capture suits,
+no laboratory infrastructure required.
+
+**v0.1 (this release)** publishes aggregate platform statistics from 100+
+consented walking sessions captured using the Arisole StrideIQ mobile
+application. It establishes the data schema, biomechanical pipeline, and
+baseline distributions ahead of a planned v0.2 clip-level benchmark.
+
+### Why This Matters
+
+Existing gait datasets (e.g., CASIA-B, CMU MoCap, DIRO) require laboratory
+hardware costing tens of thousands of dollars. StrideIQ captures equivalent
+biomechanical signals from a standard smartphone camera, opening gait analysis
+to:
+
+- Low-resource clinical settings globally
+- Remote rehabilitation monitoring
+- Robotics locomotion research (Open X-Embodiment compatible schema)
+- Population-scale epidemiology
+
+---
+
+## Dataset Structure
+
+### v0.1 Contents (Aggregate Statistics)
+
+| Field | Description |
+|-------|-------------|
+| `session_count` | 100+ walking sessions |
+| `landmark_schema` | 33 MediaPipe BlazePose landmarks (x, y, z, visibility) |
+| `biomechanical_features` | Stride length, cadence, step symmetry, trunk sway, knee flexion angle |
+| `confidence_gating` | Frames with landmark visibility < 0.6 excluded |
+| `MII_score` | Movement Intelligence Index — composite gait health score (0–100) |
+| `platform_distributions` | Aggregate histograms of MII and feature distributions |
+
+### Coming in v0.2
+
+- Clip-level landmark sequences (with explicit participant consent)
+- Demographic metadata (age band, self-reported health condition category)
+- Per-session biomechanical time-series
+- Leaderboard for automated gait quality prediction
+
+---
+
+## Biomechanical Pipeline
+
+```
+Smartphone Video
+      │
+      ▼
+MediaPipe BlazePose (on-device inference)
+      │  33 landmarks @ 30fps
+      ▼
+Confidence Gate (visibility threshold 0.6)
+      │  Filters occluded/low-quality frames
+      ▼
+Biomechanical Feature Extraction
+  ├─ Stride length estimation (hip–ankle geometry)
+  ├─ Cadence (step frequency via heel-strike detection)
+  ├─ Step symmetry (L/R stride time ratio)
+  ├─ Trunk sway (shoulder midpoint lateral displacement)
+  └─ Knee flexion angle (thigh–shin vectors)
+      │
+      ▼
+Movement Intelligence Index (MII)
+  Weighted composite score — normalized to 0–100
+  Higher = more efficient, more symmetric gait
+```
+
+**Key architectural insight (P2 companion paper):** The full biomechanical
+pipeline runs entirely **on-device**. The landmark payload transmitted to the
+cloud is ~130 KB/session vs. ~24.3 MB for the source video — a **~200×
+compression** with zero raw biometric video leaving the device.
+
+---
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load v0.1 aggregate statistics
+ds = load_dataset("ctechvent/arisole-strideiq-gait")
+print(ds)
+```
+
+> **Note:** v0.1 contains aggregate statistics and the data schema.
+> Clip-level data will be added in v0.2. Subscribe to / watch this repository
+> to be notified when v0.2 is released.
+
+---
+
+## Related Resources
+
+| Resource | Link |
+|----------|------|
+| Companion Paper (P1) | *Toward an Open, Privacy-Preserving Benchmark for Markerless Gait Analysis* — Zenodo DOI (pending) |
+| On-Device Architecture (P2) | *The Server Doesn't Need to See You Move* — Zenodo DOI (pending) |
+| Global Health Context (P3) | *Movement Poverty* — Zenodo DOI (pending) |
+| Arisole Website | [arisole.com](https://arisole.com) |
+| arXiv Preprint | Pending endorsement (arXiv submission ID: 7864429) |
+
+---
+
+## Comparison to Existing Gait Datasets
+
+| Dataset | Capture Method | Cost | Clip-Level | Smartphone | Open License |
+|---------|---------------|------|-----------|-----------|-------------|
+| CASIA-B | Multi-camera lab | $$$$  | ✅ | ❌ | ❌ |
+| CMU MoCap | Optical MoCap | $$$$ | ✅ | ❌ | ✅ |
+| TUG Dataset | Clinical sensors | $$$ | ✅ | ❌ | Varies |
+| **StrideIQ (this)** | **Smartphone** | **$0** | **v0.2** | **✅** | **✅ CC-BY** |
+
+---
+
+## Data Collection & Privacy
+
+All sessions captured via the Arisole StrideIQ app under informed consent.
+v0.1 contains **aggregate statistics only** — no per-user or per-clip data is
+included. The raw video never leaves the participant's device (on-device
+inference architecture).
+
+Institutional review: *(IRB/ethics review in progress for v0.2 clip release)*
+
+---
+
+## Citation
+
+If you use this dataset in your research, please cite:
+
+```bibtex
+@dataset{srivastava2026strideiq,
+  title     = {Arisole StrideIQ Gait Dataset (v0.1 Seed Release)},
+  author    = {Srivastava, Varun},
+  year      = {2026},
+  publisher = {Hugging Face},
+  url       = {https://huggingface.co/datasets/ctechvent/arisole-strideiq-gait},
+  version   = {0.1},
+  license   = {CC-BY-4.0}
+}
+```
+
+Companion paper citation:
+
+```bibtex
+@article{srivastava2026openmarkerless,
+  title   = {Toward an Open, Privacy-Preserving Benchmark for Markerless Gait Analysis},
+  author  = {Srivastava, Varun},
+  journal = {arXiv preprint},
+  year    = {2026},
+  note    = {arXiv submission ID: 7864429, pending endorsement}
+}
+```
+
+---
+
+## Maintainers
+
+**Varun Srivastava** — Founder, Arisole  
+**Arisole / Ctech Ventures**  
+Contact: [move@arisole.com](mailto:move@arisole.com) | [arisole.com](https://arisole.com)
+
+*Feedback, collaboration requests, and robotics/rehabilitation research
+partnerships welcome.*