Title :
An efficiency comparison of analog and digital spike detection
Author :
Sarah Gibson;Rodney Chandler;Vaibhav Karkare;Dejan Markovic;Jack W. Judy
Author_Institution :
Department of Electrical Engineering, University of California, Los Angeles, USA
Abstract :
Many applications in science and medicine that use neurophysiology require on-chip spike detection. Since implantable electronics have strict requirements on area and power, spike detection must be as power- and area-efficient as possible. In this paper, we examine whether analog or digital spike detection is more efficient. The motivation behind an analog implementation for detection is to save the power spent to quantize the input samples, which has an exponential dependence on the bit resolution. From our analysis using 90-nm technology, we find that digital implementations are more efficient for lower resolutions (up to 8 or 9 bits), whereas analog implementations are more power-efficient for higher resolutions. This conclusion is found to be valid across a wide range of SNRs and neuronal firing rates.
Keywords :
"Lifting equipment","Timing","Decoding","Hardware","Neural engineering","Neurophysiology","Implants","Band pass filters","Neuroscience","Frequency"
Conference_Titel :
Neural Engineering, 2009. NER ´09. 4th International IEEE/EMBS Conference on
Print_ISBN :
978-1-4244-2072-8
Electronic_ISBN :
1948-3554
DOI :
10.1109/NER.2009.5109323