Spike Sorting
Correlation-based signal classification for neuroscience and biomedical applications
The core goal of spike sorting is allocating a signal to its source. An algorithm that does this effectively has broad applications, but we targeted neuroscience - spike sorting is a foundational step in studying the brain and developing brain-computer interfaces.
The project produced a resource-saving, easy-to-use, and fast spike sorting algorithm based on correlation of spikes' waveforms.
Larionov, P. and Schanze T. (2018). Correlation Based Spike Sorting. Automed 2018 - Villingen-Schwenningen, March 15-16, Tagungsband, pp. 71-73.
Related work
This project became foundational for a series of publications, including an adaptation for ECG signal analysis and a multivariate extension for multichannel electrode arrays.
Role
Main author and developer.
Context
Institute of Biomedical Technology (IBMT), University of Applied Sciences, in the scientific group of Prof. Dr. Thomas Schanze (2018-2021). Presented at Automed 2018 scientific conference.