Abstract
A neuronal recording system for brain-machine interfaces (BMI) based on asynchronous biphasic pulse coding is described. It demonstrates the first step in the development of a complete implanted wireless solution with fully integrated circuit architecture. A recording experiment comparing in parallel a commercial recording system (Tucker-Davis Technology (TDT)) and the UF's custom solution (FWIRE) is set up to compare performance. The novel aspect of the UF system is that the analog signal is represented by an asynchronous pulse train, which provides a low-power, low-bandwidth, noise-resistant means for coding and transmission. Taking advantage of neural firing features, the pulse-based approach uses only 3K pulses/second to record a 25 kHz bandwidth signal from a hardware neural simulator. ©2009 IEEE.
Recommended Citation
S. F. Yen et al., "An Integrated Recording System Using An Asynchronous Pulse Representation," 2009 4th International IEEE EMBS Conference on Neural Engineering Ner 09, pp. 399 - 402, article no. 5109317, Institute of Electrical and Electronics Engineers, Oct 2009.
The definitive version is available at https://doi.org/10.1109/NER.2009.5109317
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
978-142442073-5
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
27 Oct 2009
