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license: other
license_name: ambiq-model-weights-license
license_link: https://github.com/AmbiqAI/compressionkit/blob/main/LICENSE-MODEL-WEIGHTS.md
library_name: compressionkit
pipeline_tag: other
tags:
- compressionkit
- signal-compression
- ppg
- rvq
- tflite
- edge-ai
---
# compressionkit-ppg-4x
A **PPG** signal compression codec using Residual Vector Quantization (RVQ), optimized for edge and wearable devices.
## Model Details
- **Modality:** PPG
- **Sample Rate:** 64 Hz
- **Compression Ratio:** 4x
- **Quantization:** INT8
- **RVQ Levels:** 4
- **Codebook Size:** 256 entries × 16D
- **Encoder Input:** `[None, 1, 320, 1]`
- **Encoder Output:** `[None, 1, 80, 16]`
## Quality Metrics
### Time Domain
| Metric | Mean | Median | P90 |
|--------|------|--------|-----|
| PRD (%) | 7.4052 | 2.7741 | 14.4301 |
| RMSE | 0.0306 | 0.0245 | 0.0499 |
| Cosine Similarity | 0.9869 | 0.9996 | 0.9998 |
### Spectral
- **Band Total Relative Error (median):** 0.0357
### Bitrate
- **Codec CR (uniform):** 4.0x
- **Codec CR (learned prior):** 4.55x
## Usage
### Python (compressionkit runtime)
```python
from compressionkit.runtime import RVQCodec
codec = RVQCodec.from_pretrained("Ambiq/compressionkit-ppg-4x")
# Encode: float32 signal → RVQ indices
indices = codec.encode(signal)
# Decode: RVQ indices → reconstructed signal
recon = codec.decode(indices)
```
### Local deployment directory
```python
codec = RVQCodec("path/to/deploy/")
```
## Files
| File | Description |
|------|-------------|
| `encoder_int8.tflite` | INT8 quantized encoder (on-device) |
| `encoder.h` | C header for encoder |
| `decoder_float32.tflite` | Float32 decoder (server-side evaluation) |
| `decoder_int8.tflite` | INT8 decoder (optional, on-device) |
| `codebook.npz` | RVQ codebook tables |
| `codebook.h` | C header for codebook |
| `config.json` | Deployment manifest |
| `sample_stimulus.npz` | Synthetic test data |
| `quality_scorecard.json` | Full evaluation metrics |
## Dataset & License
Training data: MESA (NSRR restricted). Sample data uses synthetic physiokit waveforms only — no patient data is redistributed.
Model weights are released under the **Ambiq Model Weights License** — deployment is restricted to Ambiq silicon devices. See `LICENSE-MODEL-WEIGHTS.md` for full terms.
## Citation
```bibtex
@software{compressionkit,
author = {Ambiq AI},
title = {compressionKIT: Signal Compression for Edge AI},
url = {https://github.com/AmbiqAI/compressionkit}
}
```
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