NDLI: Efficient online feature extraction algorithm for spike sorting in a multichannel FPGA-based neural recording system

Content Provider	IEEE Xplore Digital Library
Author	Peng Li Ming Liu Xu Zhang Hongda Chen
Copyright Year	2014
Description	Author affiliation: State Key Lab. on Integrated Optoelectron., Inst. of Semicond., Beijing, China (Peng Li; Ming Liu; Xu Zhang; Hongda Chen)
Abstract	A novel feature extraction algorithm for multichannel FPGA-based neural recording systems is presented in this paper. It contains the Dual Vertex Threshold (DVT) and the Minimum Delimitation (MD), which are used for spike detection and feature vector extraction respectively. By reducing the computational complexity of DVT and MD, the difficulty of this algorithm in application is greatly reduced. Based on this characteristic, a multichannel FPGA hardware architecture is implemented in this paper. Using extracted feature vectors, the sorting performance of K-means is as good as that with the PCA-based features. Additionally, the test result shows that the transmission bandwidth is reduced to 1.62% of original data rate.
Starting Page	1
Ending Page	4
File Size	567774
Page Count	4
File Format	PDF
ISBN	9781479923465
DOI	10.1109/BioCAS.2014.6981630
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-22
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Multiplexing low complexity FPGA Support vector machine classification high efficiency Feature extraction Principal component analysis Sorting
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Mr. Siddhartha Mukherjee siddhartha@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	ndl-support@iitkgp.ac.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Computationally Efficient Neural Feature Extraction for Spike Sorting in Implantable High-Density Recording Systems

On-chip feature extraction for spike sorting in high density implantable neural recording systems

A Method of Online Writeprint Identification Based on Principal Component Analysis

SPIKE SORTING WITH SUPPORT VECTOR MACHINES

Real-Time FPGA-Based Multichannel Spike Sorting Using Hebbian Eigenfilters

Feature Extraction Using Extrema Sampling of Discrete Derivatives for Spike Sorting in Implantable Upper-Limb Neural Prostheses

Dimensionality reduction using asynchronous sampling of first derivative features for real-time and computationally efficient neural spike sorting

Efficient VLSI Architecture for Spike Sorting Based on Generalized Hebbian Algorithm (2013)

Gender classification using selected independent-features based on Genetic Algorithm

Efficient online feature extraction algorithm for spike sorting in a multichannel FPGA-based neural recording system

Similar Documents

Computationally Efficient Neural Feature Extraction for Spike Sorting in Implantable High-Density Recording Systems

On-chip feature extraction for spike sorting in high density implantable neural recording systems

A Method of Online Writeprint Identification Based on Principal Component Analysis

SPIKE SORTING WITH SUPPORT VECTOR MACHINES

Real-Time FPGA-Based Multichannel Spike Sorting Using Hebbian Eigenfilters

Feature Extraction Using Extrema Sampling of Discrete Derivatives for Spike Sorting in Implantable Upper-Limb Neural Prostheses

Dimensionality reduction using asynchronous sampling of first derivative features for real-time and computationally efficient neural spike sorting

Efficient VLSI Architecture for Spike Sorting Based on Generalized Hebbian Algorithm (2013)

Gender classification using selected independent-features based on Genetic Algorithm

Efficient online feature extraction algorithm for spike sorting in a multichannel FPGA-based neural recording system