DocumentCode :
1645523
Title :
Adaptive detection of action potentials using ultra low-power CMOS circuits
Author :
Gosselin, Benoit ; Sawan, Mohamad
Author_Institution :
Dept. of Electr. Eng., Ecole Polytech. de Montreal, Montreal, QC
fYear :
2008
Firstpage :
209
Lastpage :
212
Abstract :
We present ultra low-power CMOS analog circuits for automatic detection of action potentials (APs). The proposed detection strategy locates AP waveforms and completely preserves their integrity. An adaptive threshold is implemented using a local time-averaging filter presenting a large time constant. The filter uses very small transconductances implemented by means of dedicated circuit techniques and subthreshold operation of MOS transistors. Also, a compact voltage squarer pre-processor is introduced to emphasize neural APs prior to detection. The proposed circuits were implemented in a CMOS 0.18-mum process and achieve ultra low-power consumption. Both circuits have been validated in simulations with synthetic neural waveforms. The adaptive threshold circuit dissipates only 27.2 nW, whereas the voltage squarer dissipates 76.7 nW.
Keywords :
CMOS analogue integrated circuits; MOSFET circuits; adaptive signal detection; bioelectric potentials; biomedical electronics; biomedical measurement; low-power electronics; medical signal detection; waveform analysis; MOS transistors; action potential waveforms; adaptive detection; adaptive threshold circuit; automatic signal detection; local time-averaging filter; power 27.2 nW; power 76.7 nW; synthetic neural waveforms; time constant; ultra low-power CMOS circuits; ultra low-power consumption; voltage squarer; voltage squarer pre-processor; Adaptive filters; Background noise; CMOS analog integrated circuits; CMOS process; Detectors; Disk recording; Implants; Propagation delay; Telemetry; Threshold voltage; Adaptive integrated circuit; Analog processor; Biopotential detection; Neural recording; Ultra low-power;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Circuits and Systems Conference, 2008. BioCAS 2008. IEEE
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-2878-6
Electronic_ISBN :
978-1-4244-2879-3
Type :
conf
DOI :
10.1109/BIOCAS.2008.4696911
Filename :
4696911
Link To Document :
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