The remarkable and rapid growth in wearable sensor technology provides an affordable means to run experiments in an out-of-lab environment under real-life conditions, opening novel research avenues for HCI designers. However, in spite of the rapid development in portable hardware, there is still a glaring lack of equally affordable software solutions for the normalization of the acquired data and their analysis.
The “SensoMatrix” project addresses the need for developing a data format and a unifying framework to facilitate archiving and sharing data gathered from various wearable sensors.
This project is being completed in collaboration with Dr Habib Benali and the LORIS (loris.ca) team at McGill Centre for Integrative Neuroscience (MCIN: mcin-cnim.ca).
SensoMatrix (Alpha tested) provisions for:
- Standardized data format
- A software platform that wraps the entire workflow in a convenient GUI (Graphical User Interface), from data pre-processing, and filtering to multi-channel integration and correlation.
- Simulation code for generating normal and abnormal ECG and EEG signals, as well as capability to add machine learning algorithms to detect and annotate the abnormalities (currently implemented for cardiac signals.)
Visit the Github for more information: https://github.com/sensomatrix/sensocore