Low-Power Circuits for Brain-Machine Interfaces

Sarpeshkar, Rahul; Wattanapanitch, Woradorn; Rapoport, Benjamin I.; Arfin, Scott K.; Baker, Maureen; Mandal, Soumyajit; Fee, Michale S.; Musallam, Sam; Andersen, Richard A.

doi:10.1109/iscas.2007.378505

Cited by 28 publications

(17 citation statements)

References 39 publications

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“…16 A versatile VLSI system which can interface to all these modalities is highly desirable. Several VLSI systems have been developed previously [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] to acquire different neural signals. Typically the range of frequencies covered by any one of these systems is limited to one or two signal modalities, to accommodate high efficiency for the targeted application.…”

Section: Neuropotential Interfacementioning

confidence: 99%

Simultaneous wireless electrophysiological and neurochemical monitoring

et al. 2008

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Information processing and propagation in the central nervous system is mostly electrical in nature. At synapses, the insulating gaps between neurons, electrical signals cause the release of chemical messengers called neurotransmitters which travel across the synapse and modulate the postsynaptic neuron electrical activity. The interrelated nature of these signals and their implication in several clinical and basic neural pathways motivate their simultaneous monitoring. We present an integrated system for continuous acquisition of both data modalities in awake behaving rats. It features one channel each of a configurable electrophysiological and a neurochemical acquisition system. The electrophysiological system comprises of a 40 dB gain fully differential amplifier with tunable bandwidth from 140 to 8200 Hz. The amplifier offers noise below 2 µV rms for all bandwidth settings. The neurochemical module features a picoampere sensitivity potentiostat with a dynamic range spanning 6 decades from picoamperes to micoamperes. Both systems have independent on-chip configurable ∆Σ ADCs with programmable digital gain and resolution. The system was also interfaced to a wireless power harvesting and telemetry module capable of powering up the circuits, providing clock for ADC operation and telemeter out the data at up to 32 kbps over 4 cm with a bit error rate (BER) < 10 −5 . Characterization and experimental results from both the electrophysiological and neurochemical modules as well as the full system are presented.

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Section: Neuropotential Interfacementioning

confidence: 99%

Simultaneous wireless electrophysiological and neurochemical monitoring

et al. 2008

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“…It is now common for neuroscientists and clinicians to observe the behavior of diverse signals as part of their research, and this has motivated the development of lownoise, low-power neural recording systems [1][2][3][4]. Since most neurological and behavioral disorders can be observed by brain activity, brain computer interfaces (BCIs) have been developed for the acquisition of neural signals by electroencephalography (EEG) signals [5].…”

Section: Introductionmentioning

confidence: 99%

A 4×32-Channel Neural Recording System for Deep Brain Stimulation Systems

Kim

Yang

et al. 2017

JSTS:Journal of Semiconductor Technology and Science

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“…Additionally, which transfer we will focus o r, we will ded idea is to use ls will be selec riven by 10 MH ually amplified ransistor will b gic transistors. n the digital sp e digital data w nerated using a ifier which ca umption will b n of number el sidering the int 0.1 nW of stati KAUST over th e can safely a e for signal acq trodes with 1:1 uch dimension ioned by the U we will rest (both digital lo cm 2 with furthe he power coup tem [62][63][64][65][66][67] . n in the chosen a % power rs power on using dicate 10 e counter cted oneHz clock d using a be fed to .…”

Section: Introductionmentioning

confidence: 99%