[Show abstract][Hide abstract] ABSTRACT: This paper discusses a real time stimulus timing detection for a Brain-Machine-Interface (BMI). We present a low complexity detector for detecting the stimulus onset time from real multichannel, multi-unit electro-physiological data, recorded from a brainstem area called Pontine Nucleus (PN). The detector contains a novel pre-processing block, which takes advantage of the high coherence between different channels during response, in order to enhance the Signal-to- Noise Ratio (SNR), as well as to achieve higher detection rates. An intuitive effective method for fusion and combination of different channels based on spike counts is used. A full detailed description of the algorithm blocks is presented, along with its optimized parameters according to real data performance evaluation.
[Show abstract][Hide abstract] ABSTRACT: In this paper we propose a Rapid Prototyping Environment (RPE) for real-time biosignal analysis including ECG, EEG, ECoG and EMG of humans and animals requiring a very precise time resolution. Based on the previous RPE which was mainly designed for developing Brain Computer Interfaces (BCI), the present solution offers tools for data preprocessing, analysis and visualization even in the case of high sampling rates and furthermore tools for precise cognitive stimulation. One application of the system, the analysis of multi-unit activity measured from the brain of a rat is presented to prove the efficiency of the proposed environment. The experimental setup was used to design and implement a biomimetic, biohybrid model for demonstrating the recovery of a learning function lost with age. Throughout the paper we discuss the components of the setup, the software structure and the online visualization. At the end we present results of a real-time experiment in which the model of the brain learned to react to the acquired signals.