LSL/XDF data to PyHRV about pyhrv HOT 1 CLOSED

Hi @sunshineinsandiego,

thanks for using pyHRV. You have most likely already solved this issue but as I am picking up on this project again after a long break, I'd like to share here some input.

pyHRV is not designed for real-time signal processing, but rather for post-processing of acquired R-Peak-to-R-Peak Interval (RRI) series. Real-time processing could technically be achieved with some simple HRV parameter computations, but from my experience the heavier functions (e.g. frequency domain) are too slow to be useful in real-time processing.

Also, it is important to highlight that pyHRV runs any RRI series in bumpy array format and is not exclusive to OpenSignals files. The examples provided with OpenSignals are only available as it was the software I used to record signals and test pyHRV during my thesis. With this being said, allow to answer your questions below:

Which brings me to another question, is there any way to use the PyHRV functions on numpy arrays?
Yes, this is perfectly possible and there are a few examples available in the Quickstart guide using the time domain functions here:

https://github.com/PGomes92/pyhrv/tree/master/pyhrv

If you already have a RRI series (or NNI) in an numpy array, it's quite straightforward to use it with pyHRV as shown in the example below:

# Import packages
import numpy as np
import pyhrv.time_domain as td 

# Load NNI sample series
nni = np.load('./files/SampleNNISeries.npy')

# Compute SDNN
result = td.sdnn(nni)

# Access SDNN value using the key 'sdnn'
print(result['sdnn'])

Polar input Data
If the Polar monitor provides you a full ECG in mV, the data must first be processed to run with pyHRV as you need to extract the heart rate series our RRI/NNI series from the ECG first.

For this, you can generally follow the same tutorial that's available for OpenSignals input data:

import biosppy
import numpy as np
import pyhrv.tools as tools

# Load sample ECG signal 
signal = your_signal # <- this should be your ECG signal in mV

# Get R-Peak locations from ECG signal
rpeaks = biosppy.signals.ecg.ecg(signal, show=False)[2]

# Compute NNI
nni = tools.nn_intervals(rpeaks)

# Compute SDNN
result = td.sdnn(nni)

Hope this information is still useful for anyone who comes across this issue and feels free to let me know if you have any questions.

from pyhrv.