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HELIA

TimePPG (PPG heart-rate regression)

helia_edge.models.timeppg.build builds the TEMPONet-derived TimePPG regressor from Q-PPG (Burrello et al., 2022). TimePPGParams holds the backend-free config. The presets timeppg_big, timeppg_medium and timeppg_small use the channel widths in upstream precision_search/model/TimePPG_float.py at eml-eda/q-ppg@ddf3866d.

from helia_edge.models import TIMEPPG_PRESETS, ModelSpec, build


model = build(ModelSpec(params=TIMEPPG_PRESETS["timeppg_medium"], input_shape=(256, 4)))

Input: a channels-last window. The reference uses 256 samples: blood volume pulse decimated from 64 Hz to 32 Hz, plus three accelerometer axes (PPG-DaLiA, 8 s windows with a 2 s hop). Normalization and channel order belong to the caller.

Architecture: three stages. Each stage has two dilated temporal blocks followed by one strided convolution block, then two dense regressor layers and a single linear output. Upstream order is kept exactly:

Block Layers Parameters
Temporal Conv1D, then BatchNorm, then ReLU6 kernel 3, dilations 2/2, 4/4, 8/8, same padding, no bias
Strided convolution Conv1D, then AveragePooling 2, then BatchNorm, then ReLU6 kernel 5, strides 1/2/4, explicit padding 2/2/4, no bias; a 256-sample window reaches 128, 32 and 4 steps
Regressor Dense without bias, then BatchNorm, then ReLU6 two layers
  • Features are flattened channel-major, matching the upstream PyTorch layout.
  • BatchNorm uses PyTorch’s defaults (epsilon 1e-5, momentum 0.1). During training, Keras updates the running variance with the biased batch variance where PyTorch uses the unbiased one, so running statistics drift slightly apart; inference is unaffected.
  • Trainable parameter counts equal the upstream definition. For example, timeppg_medium has 40,542 parameters and about 3.9M MACs per window.

Weights and terms

Section titled “Weights and terms”

Upstream publishes no trained checkpoints. These constructors produce untrained models, suited to performance measurement only; no heart-rate accuracy is implied. The upstream code is Apache-2.0, and its notice is retained in helia_edge/models/licenses/timeppg-apache-2.0.txt. PPG-DaLiA is CC BY 4.0.