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Compression Methods

compressionKIT implements multiple compression approaches for physiological signals, ranging from classical signal processing to learned neural methods.

Method Comparison

Method Type Compression Latency Quality Deployable
RVQ Autoencoder Learned 2×–16× documented Low High INT8 TFLite
Wavelet + SPIHT Classical 2×–16× Very Low Medium Planned
Decimation Baseline 2×–16× Minimal Low Trivial

Design Principles

All compression methods in compressionKIT follow these principles:

  1. Portable to embedded C — No dynamic allocation, fixed memory layouts
  2. Quantization-friendly — Only operators that work with INT8/INT16x8 quantization
  3. Configurable via YAML — Major parameters exposed through configuration files
  4. Evaluated on clinical metrics — Not just MSE, but HR/HRV preservation