jomy-kk / ltbio Goto Github PK

Extraction/ Calculation

Describe the bug
When plotting an ECG of 5 Segments in each channel, from the 3rd Segment and on they start to overlap on the plot.

Modules
biosignals

To Reproduce
Instructions that reproduce the behavior:

ecg = ECG(data_path, Sense('run_chest'), Patient('ME93'))
ecg.plot()

Expected behavior
Segments should be visibly separated.

Screenshots

Python Version
3.10.4

• apply method
• SNR
• MSE / RMSE
• Plot before/after
• Bode plots

Extends Biosignal and should hold Timeseries from different modalities.

Will this be useful when requiring multimodality in ML training?

Motivation

Currently, data from ScientISST SENSE files are being read as raw. And it is supposed to have data in mV, uS, G, whatever, depending on the biosignal modality. That can be solved by implementing transfer functions.

Specification

Transfer functions are relative to the source device from where the data was acquired, so source-specific transfer functions should be implemented for each BiosignalSource subclass. The class BiosignalSource demands _transfer to be implemented, so that's where the transfer functions will reside.

The signature of _transfer is the following:

@staticmethod
_transfer(samples: array, type) -> array

One can read it as "transfer these samples to the default unit of this biosignal type".

Arguments:

• samples: a numpy array of one dimension with some samples of a segment in floats;
• type: A subclass of Biosginal.

It should return a numpy array with the samples converted to the default unit. The default Unit of each biosignal type is maintained in a class-constant called DEFAULT_UNIT in each subclass.

>> To check if the implemented feature is complying with Specification, all tests should pass.

Example of Use

_transfer([1.0, 2.0, 3.0, ...], ECG)

should output

[0.82, 2.23, 2.87, ...]  # merely illustrational values

Branch

Use units branch to work on this issue.

• Filter Signal
• Calculate R peaks
• Calculate Heart Rate
• Smooth Heart Rate Signal
• Do this process for signal1
• Do this process for signal2
• Correlation Value with Adaptive Sliding Window
• Return offset temporal deviation between signal 1 and 2

Describe the bug
Overlap is ignored.

Modules
biosignals

To Reproduce
Instructions that reproduce the behavior:

x = Biosignal.load(biosignal_path)
median_filter1 = TimeDomainFilter(ConvolutionOperation.MEDIAN, timedelta(seconds=3), timedelta(seconds=3*0))
median_filter2 = FrequencyDomainFilter(ConvolutionOperation.MEDIAN, timedelta(seconds=3), timedelta(seconds=3*0.9))
y1 = median_filter1(x)
y1 = median_filter2(x)

The Problem
y1 and y2 are equal

Expected behavior
They should be different, because the overlap of each filter is different.

Python Version
3.11

Describe the bug
The way E4._read is implemented it expects csv files to be right on the given directory, but it should not.
Inside the given directory, it should expect subdirectories (probably named after the start timestamp), and each should be considered a Segment in time.

Example of tree:
--- given_path
    | ---- 1655923195_A0200B
        | ---- ACC.csv
        | ---- BVP.csv
    | ---- 1656324824_A0200B
        | ---- ACC.csv
        | ---- BVP.csv
    | ...

Modules
biosignals

To Reproduce
Instructions that reproduce the behavior:

E4._read(given_path, EDA)

Terminal/Console Error

Files were not found in path given_path

Expected behavior
To read files inside subdirectories, and consider each subdirectory as a Segment.

Python Version
3.10.4

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