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Hi everyone,
I'm working on a project where I need to visualize ECG and ACC signals from PolarH10. Specifically, I want to plot the signals from the last 10 seconds of data in a small rectangle on an image. To fit the plots within this rectangle, I normalize the data each time I receive a new data packet from Polar.
Here’s the problem:
Whenever I get a new data packet, I normalize the values for the entire 10 seconds of data. This causes issues because if the new packet contains very high values, the existing normalized values become very small, and if the new packet contains very low values, the existing plots become large. This makes the plots very dynamic and hard to read.
One of the suggested way to deal with this issue is to use local gain, but I'm not sure how to implement this.
Can someone explain how to manage this issue or share how they’ve solved similar problems? Any advice or pointers to resources would be greatly appreciated!
Thank you!
The text was updated successfully, but these errors were encountered:
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Hi everyone,
I'm working on a project where I need to visualize ECG and ACC signals from PolarH10. Specifically, I want to plot the signals from the last 10 seconds of data in a small rectangle on an image. To fit the plots within this rectangle, I normalize the data each time I receive a new data packet from Polar.
Here’s the problem:
Whenever I get a new data packet, I normalize the values for the entire 10 seconds of data. This causes issues because if the new packet contains very high values, the existing normalized values become very small, and if the new packet contains very low values, the existing plots become large. This makes the plots very dynamic and hard to read.
One of the suggested way to deal with this issue is to use local gain, but I'm not sure how to implement this.
Can someone explain how to manage this issue or share how they’ve solved similar problems? Any advice or pointers to resources would be greatly appreciated!
Thank you!
The text was updated successfully, but these errors were encountered: