Signal Processing

The signal submodule contains lots of underlying signal processing functionality used by the higher-level modules. This includes filtering routines, noise injection, and transformations.

Filtering

signal.filter contains a number of filtering routines such as a generic second order section biquad filter, resampling, normalizing, smoothing, and more. Below we highlight a few of these routines.

Function	Description
pk.signal.resample_signal	Resamples a signal to a new sampling rate.
pk.signal.resample_categorical	Resamples a categorical signal to a new sampling rate.
pk.signal.normalize_signal	Normalizes a signal to a new range.
pk.signal.filter_signal	Filters a signal using a second order section biquad filter.
pk.signal.remove_baseline_wander	Removes baseline wander from a signal.
pk.signal.smooth_signal	Smooths a signal using a Savitzky-Golay filter.
pk.signal.quotient_filter_mask	Applies a quotient filter to identify outliers from list.

Example

In the following snippet, we generate a synthetic PPG signal with a heart rate of 64 BPM sampled at 1000 Hz. We then filter the signal using a second order section biquad filter.

import physiokit as pk

fs = 1000  # Hz
tgt_hr = 64  # BPM

ppg = pk.ppg.synthesize(
    duration=10,  # in seconds
    sample_rate=fs,
    heart_rate=tgt_hr,
)

ppg_clean = pk.signal.filter_signal(
    data=ppg_noise,
    lowcut=0.5,
    highcut=4,
    order=3,
    sample_rate=fs
    forward_backward=True
)

Noise Injection

signal.noise contains a number of noise injection routines such as Gaussian noise, uniform noise, and more. Below we highlight a few of these routines.

Function	Description
pk.signal.add_baseline_wander	Adds baseline wander to a signal.
pk.signal.add_motion_noise	Adds motion noise to a signal.
pk.signal.add_burst_noise	Adds burst noise to a signal.
pk.signal.add_powerline_noise	Adds powerline noise to a signal.
pk.signal.add_noise_sources	Adds additional noise sources to a signal.

Example

In the following snippet, we generate a synthetic PPG signal and inject the following noises: baseline wander, powerline noise, and custom noise sources.

import physiokit as pk

fs = 1000  # Hz
tgt_hr = 64  # BPM

ppg = pk.ppg.synthesize(
    duration=10,  # in seconds
    sample_rate=fs,
    heart_rate=tgt_hr,
)

# Add baseline wander
ppg_noise = pk.signal.add_baseline_wander(
    data=ppg,
    amplitude=2,
    frequency=1,
    sample_rate=fs
)

# Add powerline noise
ppg_noise = pk.signal.add_powerline_noise(
    data=ppg_noise,
    amplitude=0.05,
    frequency=60,
    sample_rate=fs
)

# Add additional noise sources
ppg_noise = pk.signal.add_noise_sources(
    data=ppg_noise,
    amplitudes=[0.05, 0.05],
    frequencies=[10, 20],
    sample_rate=fs
)

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Transformations

signal.transform contains a number of transformation routines such as the fast Fourier transform, the inverse fast Fourier transform, and more. Below we highlight a few of these routines.

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API

Refer to signal API for more details