By Topic

Digital signal processing algorithms for the detection of afferent nerve activity recorded from cuff electrodes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Upshaw, B. ; Center for Sensory-Motor Interaction, Aalborg Univ., Denmark ; Sinkjaer, T.

Due to the very poor signal-to-noise ratios (SNR's) usually encountered with whole nerve-cuff signals, the processing method typically applied, rectification and windowed (bin)-integration (RBI), can have serious shortcomings in extracting reliable information. In order to improve detection accuracy, these signals were further analyzed using statistical signal detection algorithms based on their second and higher order spectra (HOS). A comparison with both analog and digital RBI processing suggests that the statistical methods, due to their ability to separate the signal and noise subspaces, are superior. It was determined that the noise typically encountered with nerve-cuff electrode signals is normally (Gaussian) distributed. Therefore, third-order statistics can be applied to, ideally, completely reject the noise component. When cutaneous nerve recordings from the calcaneal nerve (innervating the heel area) were used in a drop-foot correction neural prosthesis, the detection percentage and the insensitivity to algorithm parameters were increased through the use of these statistical methods as to warrant their real-time implementation, and the inherent additional processing hardware that entails

Published in:

Rehabilitation Engineering, IEEE Transactions on  (Volume:6 ,  Issue: 2 )