timeppg

TimePPG heart-rate regressor from PPG and accelerometer windows.

Adapted from eml-eda/q-ppg (revision ddf3866d, precision_search/model/TimePPG_float.py). Inputs are channels-last (time, channels) windows; the reference uses 256 samples of BVP at 32 Hz plus three accelerometer axes. Constructors initialize weights only: upstream publishes no trained checkpoints, so these models are untrained.

Machine-readable model

• buildfunctionConstruct an untrained TimePPG regressor with one linear output.

function

build

Python

Construct an untrained TimePPG regressor with one linear output.

helia_edge/models/timeppg.py:43

build(
    params: TimePPGParams,
    input_shape: tuple[int | None, ...],
    *,
    batch_size: int | None = None,
    name: str | None = None,
) -> keras.Model

Construct an untrained TimePPG regressor with one linear output.

The input is (time, channels) with a known time length that survives the 64x downsampling. The flattened features are channel-major, matching the upstream PyTorch layout.

Parameters

Parameters of build

Name	Type	Default	Description
params	TimePPGParams	Required	Model parameters.
input_shape	tuple[int | None, ...]	Required	``(time, channels)``, both known, time at least 64.
batch_size	int | None	None	Static batch size; None for a dynamic batch.
name	str | None	None	Model name; the family when None.

Returns

Returns of build

Type	Description
keras.Model	keras.Model: The model, named ``timeppg`` unless ``name`` is given.