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Segmentation Task API

The objective of segmentation is to delineate key segments of the signal. In the context of ECG signals, this involves identifying the different components of the cardiac cycle, including the P-wave, QRS complex, and T-wave. These segments are used to compute a number of clinically relevant metrics, including heart rate, PR interval, QRS duration, QT interval, and QTc interval. For PPG, the task involves segmenting the systolic and diastolic phases of the cardiac cycle. Segmentation models are useful for detecting arrhythmias, heart rate variability, and other cardiac abnormalities.

Classes:

Classes

SegmentationTask

heartKIT Segmentation Task

Functions

train staticmethod 
train(params: HKTaskParams)

Train model for segmentation task

Parameters:

Source code in heartkit/tasks/segmentation/__init__.py 
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@staticmethod
def train(params: HKTaskParams):
    """Train model for segmentation task

    Args:
        params (HKTaskParams): Task parameters
    """
    train(params)
evaluate staticmethod 
evaluate(params: HKTaskParams)

Evaluate segmentation model

Parameters:

Source code in heartkit/tasks/segmentation/__init__.py 
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@staticmethod
def evaluate(params: HKTaskParams):
    """Evaluate segmentation model

    Args:
        params (HKTaskParams): Task parameters
    """
    evaluate(params)
export staticmethod 
export(params: HKTaskParams)

Export segmentation model

Parameters:

Source code in heartkit/tasks/segmentation/__init__.py 
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@staticmethod
def export(params: HKTaskParams):
    """Export segmentation model

    Args:
        params (HKTaskParams): Task parameters
    """
    export(params)
demo staticmethod 
demo(params: HKTaskParams)

Run segmentation demo.

Parameters:

Source code in heartkit/tasks/segmentation/__init__.py 
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@staticmethod
def demo(params: HKTaskParams):
    """Run segmentation demo.

    Args:
        params (HKTaskParams): Task parameters
    """
    demo(params)