Low power switched-resistor band-pass filter for neural recording channels in 130nm CMOS. Issue 8 (August 2020)

• Record Type: Journal Article
• Authors: Centurelli, Francesco; Fava, Alessandro; Monsurrò, Pietro; Scotti, Giuseppe; Tommasino, Pasquale; Trifiletti, Alessandro
• Is Part Of: Heliyon. Volume 6:Issue 8(2020)
• Publication Date: 2020-08
• Subjects: Biomedical engineering -- Electrical engineering -- Neuroscience -- Signal processing -- Wireless network -- Very-large-scale integration -- Neural recording -- Low-power -- Switched resistors filter -- Brain-computer interface -- Area efficient; Research -- Periodicals; Medical sciences -- Periodicals; Natural history -- Periodicals; Social sciences -- Periodicals; Earth sciences -- Periodicals; Physical sciences -- Periodicals; 507.2
• DOI: 10.1016/j.heliyon.2020.e04723
• Languages: English
• ISSNs: 2405-8440

Abstract

Abstract: In this work, we present a low-power 2 nd order band-pass filter for neural recording applications. The central frequency of the passband is set to 375Hz and the quality factor to 5 to properly process the neural signals related to the onset of epileptic seizure, and to strongly attenuate all the out of band biological signals and electrical disturbances. The biquad filter is based on a fully differential Tow Thomas architecture in which high-valued resistors are implemented through switched high-resistivity polysilicon resistors. A supply voltage as low as 0.8V and MOS transistors operating in the sub-threshold region are exploited to achieve a power consumption as low as 170nW, when driving a 1pF load capacitance. The filter exhibits a tuning range of the resonance frequency from 200Hz to 400Hz, and an area footprint of only 0.021 mm 2 . Very low power consumption and area occupation are key specifications for integrated, multiple-sensors, neural recording systems. Abstract : Biomedical engineering; Electrical engineering; Neuroscience; Signal processing; Wireless network; Very-large-scale integration; Neural recording; Low-power; Switched resistors filter; Brain-computer interface; Area efficient.