Titlebook: Ultra Low-Power Integrated Circuit Design for Wireless Neural Interfaces; Jeremy Holleman,Fan Zhang,Brian Otis Book 2011 Springer Science+

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Spike Detection and Characterization,cal stimulation. To this end, the spike detector is combined with feature extraction circuitry, which measures the maximum and minimum of detected spikes, and an ADC, which digitizes the detected values.

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,A 500μW Wireles Neural Streaming System,r range from the receiver and to transmit more data. Because of the low power consumption in the analog front end and the wireless transmitter, the system can operate from a very small battery, resulting in an extremely lightweight system with a small form-factor.

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A Low-Power Low-Noise Open-loop Amplifier for Neural Recording,edance. Because of the small signal amplitudes, amplifier noise must be minimized in order to avoid unnecessary degradation of the signal. Additionally, the high impedance of neural electrodes necessitates a high impedance input.

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Closed-loop Bio-signal Amplifiers: Experimental Results,apter. In order to compare and contrast the performance of these two LNA designs, we fabricated both LNAs in a 0.13 .m CMOS process. As the analog front-end of a neuralrecording channel, each LNA is followed with a variable-gain amplifier (VGA) to accommodate signals of various amplitudes. Fig. 5.1

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Design and Implementation of chopper-stabilized amplifiers,ise optimization techniques target thermal noise. However, flicker noise is a significant concern for EMG/EEG/ECoG applications, where the bandwidth of interest is much lower (<500Hz) than that of neural applications (∼10kHz). Therefore, we will devote this chapter to discussing techniques to combat