Bio-integrated Software Development for Adaptive Sensor Networks

This project aims at creating software tools for the utilization of biological cells as part fo sensor motes of a sensor network. Tools developed are related to connectivity and causality analysis between cells, models of biological networks organizing on a Multi-Electrode Array (MEA), pattern recognition and on-site computing from sensor motes (e.g. Raspberry Pi).

This repository collects the work of various developers involved in this project. The purpose of this repository is to regroup in one place all developments related to the BioSWdev4ASN project.

This collection available here regroups:

• models for the simulation of biological neurons plated on MEA (SiMEA developed by MSc. Vafa Andalibi)

• a model simulating the stimulation of a Spiking Neural Network for simple pattern recognition (difference between cross and circle). This model was presented in SPLST conference in 2015.

• an implementation of the Cox method for the analysis of network effective connectivity from spike-timing processes (also developed by MSc. Vafa Andalibi)

• a lightweight Spiking Neural Network simulator developed in Lua language (simulator developed by Ville Lehtola)

• a face recognition and tracking application developed for embedded systems (application developed by Ville Lehtola)