Advanced Spike Sorting Approaches in Implantable VLSI Wireless Brain Computer Interfaces: A Survey
Year: 2024
Type: conference-paper
Abstract: Brain Computer/Machine Interfaces (BCI/BMIs) have substantial potential for enhancing the lives of disabled individuals by restoring functionalities of missing body parts or allowing paralyzed individuals to regain speech and other motor capabilities. Due to severe health hazards arising from skull incisions required for wired BCI/BMIs, scientists are focusing on developing VLSI wireless BCI implants using biomaterials. However, significant challenges, like power efficiency and implant size, persist in creating reliable and efficient wireless BCI implants. With advanced spike sorting techniques, VLSI wireless BCI implants can function within the power and size constraints while maintaining neural spike classification accuracy. This study explores advanced spike sorting techniques to overcome these hurdles and enable VLSI wireless BCI/BMI implants to transmit data efficiently and achieve high accuracy.
Author: Soujatya Sarkar
Institution: Bose Institute
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Funders: University of Calcutta, Bose Institute
OpenAlex ID: W4404521094