The Wearables Development Toolkit - a development environment for activity recognition applications with sensor signals

Wearable computing software framework for intelligence augmentation research and applications. Easily build smart glasses apps, relying on built in voice command, speech recognition, computer vision, UI, sensors, smart phone connection, NLP, facial recognition, database, cloud connection, and more. This repo is in beta.

Auritus: An Open-Source Optimization Toolkit for Training and Development of Human Movement Models and Filters Using Earables

Python implementations of machine learning algorithms for motion artifact detection in electrodermal activity (EDA) data

Open Source Wearable Microphone Array Glasses for Multi-Speaker Speech Recognition

Wearables Development Toolkit - Visual programming tool

"UBIWEAR: An end-to-end, data-driven framework for intelligent physical activity prediction to empower mHealth interventions" @ IEEE HealthCom 2022

Enhancing Efficiency in Multidevice Federated Learning through Data Selection

PsyGlass: An open-source framework for implementing Google Glass in research settings

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.

PyTorch Implementation of IEEE/ACM CHASE 2021 paper "STranGAN: Adversarially-Learnt Spatial Transformer for Scalable Human Activity Recognition"

GazeGraph: Graph-based Few-Shot Cognitive Context Sensing from Human Visual Behavior

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. 📈

Android application (Mobile, HUD, Watch) for HUD vs. Watch dual-task study

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.

Arm mounted computer, which includes detection for bio signatures, accleration, gyroscope(Orientaion to Gravity well), and uploads to master control server.

RealTimePose is a Python library for creating body-interactive GUIs using computer vision.

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.

Hello World example for Tizen Watch / Samsung smart watch

cvgui is a Python library for creating body-interactive GUIs using computer vision.