Mobile-Sensing-and-UbiComp-Laboratory/NormWear
A Foundation Model for Multivariate Wearable Sensing of Physiological Signals.
This project helps researchers and healthcare professionals analyze complex physiological data from wearable sensors. It takes raw data like heart rate (PPG, ECG), brain activity (EEG), skin response (GSR), and movement (IMU) and transforms it into insightful patterns. The output helps in evaluating mental health, body states, vital signs, or disease risks, enabling a deeper understanding of human physiology.
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Use this if you need to extract meaningful, generalizable insights from diverse wearable physiological sensor data for health-related applications, even for scenarios you haven't explicitly trained for.
Not ideal if your primary goal is simple data visualization or if you only work with a single, highly specialized sensor type and don't need to generalize across different data sources or applications.
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42
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12
Language
Python
License
Apache-2.0
Category
Last pushed
Jun 16, 2025
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