Accelerometer (ACC)¶

Accelerometer (ACC) signals capture body movement and orientation from linear acceleration measured along one or more axes. In biosignal workflows, ACC is commonly used to quantify physical activity, estimate posture transitions, and provide motion context for other modalities such as ECG or PPG.

API quick links: biosppy.signals.acc | biosppy.signals.acc.acc()

Example ACC signal plot.

Quick Usage with `biosppy.signals.acc.acc()`¶

import numpy as np
from biosppy.signals import acc

# Load a sample ACC recording (one or multiple axes).
signal = np.loadtxt("examples/acc.txt")

# sampling_rate is in Hz; show=False avoids opening the plot window.
out = acc.acc(signal=signal, sampling_rate=100.0, show=False)

# ReturnTuple behaves like a tuple + dict-style keys.
print(out.keys())

Inputs

signal: ACC samples (typically N x channels).
sampling_rate: acquisition frequency in Hz.
units / path / show: optional metadata, output path, and plotting control.

Outputs

A ReturnTuple with processed ACC information (timestamps, filtered views, and activity-related descriptors).
Use out.keys() to inspect all available outputs in your installed version.

Example of ACC summary plot:

Example ACC signal summary plot.