Python implementations of machine learning algorithms for motion artifact detection in electrodermal activity (EDA) data
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Updated
Jul 27, 2017 - Python
Python implementations of machine learning algorithms for motion artifact detection in electrodermal activity (EDA) data
Classifying Body movement using wearrable data
PsyGlass: An open-source framework for implementing Google Glass in research settings
Hello World example for Tizen Watch / Samsung smart watch
MusicBelt- A musical seatbelt for kids
Android application (Mobile, HUD, Watch) for HUD vs. Watch dual-task study
List of categorized resources in the field of Personal Analytics. Simply put, personal analytics is an extension of quantified self that includes tracking and analyzing more parameters compared to just tracking health or activity. Personal analytics would include tracking in areas such as health, vitals, expenditures, productivity and much more. 📈
Human Activity Recognition(HAR) - Case Study : Wearable Computing: Accelerometers’ Data Classification of Body Postures and Movements, using Random forests classifier to quantify and predict best way to do exercise.
Interactex Designer is a configuration tool to easily setup, simulate and connect e-Textile hardware with smartphone functionality. Interactex Client is an app to store and replay projects made with Interactex Designer.
Wearables Development Toolkit - Visual programming tool
The Wearables Development Toolkit - a development environment for activity recognition applications with sensor signals
Getting and cleaning data using UCI HAR Dataset
wearablecompute is an open source Python package containing over 50 data and domain-driven features that can be computed from wearables and mHealth sensor data.
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PyTorch Implementation of IEEE/ACM CHASE 2021 paper "STranGAN: Adversarially-Learnt Spatial Transformer for Scalable Human Activity Recognition"
Open Source Wearable Microphone Array Glasses for Multi-Speaker Speech Recognition
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