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There is an increasing demand for more advanced and effective medical devices due to the interest on real-time personal home health monitoring. The electroencephalogram (EEG) is a common noninvasive method for various applications, such as the prediction of epileptic seizure and brain-computer interfaces (BCIs). A key component of an EEG monitoring systems is the acquisition circuitry with ultra low-power...
We present the design of an adaptive neural spike detector that dynamically adjusts the spike detection threshold based on the signal to noise ratio of the neural data sets. We propose a self-learning architecture, with a threshold-lock loop that feeds back a spike sorting performance index to the FSM inside the adaptive spike detector. The FSM references this performance index and dynamically determines...
In this paper we present an autonomous and adaptive digital neural signal processor to enable real-time processing of neural signals for brain machine interfaces (BMIs). The algorithms and architectures provide autonomous operation with low computational and hardware complexity. This enables localized processing of neural signals to minimize wireless bandwidth and overall power dissipation.
This paper reports a highly integrated neural tag for biosignal streaming data recording. The analog front-end uses a time multiplexed architecture with tunable bandwidth amplifiers, a shared output stage and 8-bit SAR ADC, and achieves an NEF of 2.7 with input referred noise of 18nV/√Hz. Streaming digitized signal recordings are packetized and transmitted via a low power 915MHz backscattering modulator...
This letter presents progress toward an energy efficient neural data acquisition transponder for brain-computer interfaces. The transponder utilizes a four-channel time-multiplexed analog front-end and an energy efficient short-range backscattering RF link to transmit digitized wireless data. In addition, a low-complexity autonomous and adaptive digital neural signal processor is proposed to minimize...
This paper reports a highly integrated battery operated multi-channel instrumentation system intended for physiological signal recording. The mixed signal IC has been fabricated in standard 0.5μm 5V 3M-2P CMOS process and features 32 instrumentation amplifiers, four 8b SAR ADCs, a wireless power interface with Li-ion battery charger, low power bidirectional telemetry and FSM controller with power...
Transmitting large amounts of data sensed by multi-electrode array devices is widely considered to be a challenging problem in designing implantable neural recording systems. Spike sorting is an important step to reducing the data bandwidth before wireless data transmission. The feasibility of spike sorting algorithms in scaled CMOS technologies, which typically operate on low frequency neural spikes,...
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