File size: 2,512 Bytes
949e581 0a848b2 949e581 0a848b2 949e581 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 | ---
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-2x
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:** 2x
- **Quantization:** INT8
- **RVQ Levels:** 4
- **Codebook Size:** 256 entries × 16D
- **Encoder Input:** `[None, 1, 320, 1]`
- **Encoder Output:** `[None, 1, 160, 16]`
## Quality Metrics
### Time Domain
| Metric | Mean | Median | P90 |
|--------|------|--------|-----|
| PRD (%) | 6.1800 | 2.2707 | 10.7564 |
| RMSE | 0.0241 | 0.0199 | 0.0386 |
| Cosine Similarity | 0.9912 | 0.9998 | 0.9999 |
### Spectral
- **Band Total Relative Error (median):** 0.0263
### Bitrate
- **Codec CR (uniform):** 2.0x
- **Codec CR (learned prior):** 3.11x
## Usage
### Python (compressionkit runtime)
```python
from compressionkit.runtime import RVQCodec
codec = RVQCodec.from_pretrained("Ambiq/compressionkit-ppg-2x")
# 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}
}
```
|