@inproceedings{53b2976be0ec41038d271a50540adfaf,
title = "Improved linear BMI systems via population averaging",
abstract = "We investigate population averaging as a preprocessing stage for linear FIR BMIs. Population averaging is a biologically-inspired technique based on spatial constraints and neuronal correlation. We achieve a statistically significant improvement in accuracy while substantially (45%) reducing model parameters. Further analysis is performed to show that population averaging improves model accuracy by reducing variance in estimating the firing rate from spike bins. However, we find that population averaging provides a greater accuracy improvement than other groupings which also reduce firing rate variance. Our results suggest that appropriate spatial organization of neural signals enhances BMI performance.",
author = "Jack DiGiovanna and Sanchez, {Justin C.} and Principe, {Jose C.}",
year = "2006",
month = dec,
day = "1",
doi = "10.1109/IEMBS.2006.260496",
language = "English (US)",
isbn = "1424400325",
series = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",
pages = "1608--1611",
booktitle = "28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06",
note = "28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 ; Conference date: 30-08-2006 Through 03-09-2006",
}