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—A 128-bit, 1.6 pJ/bit, 96% stable chip ID generation circuit utilizing process variations is designed in a 0.13 m CMOS process. The circuit consumes 162 nW from a 1 V supply at low readout frequencies and 1.6 W at 1 Mb/s. Cross-coupled logic gates were employed to simultaneously generate, amplify, and digitize the random circuit offset to create a stable(More)
In this paper we present a pre-amplifier designed for neural recording applications. Extremely low power dissipation is achieved by operating in an open-loop configuration, restricting the circuit to a single current branch, and reusing current to improve noise performance. Our amplifier exhibits 3.5 microVrms of input-referred noise and has a(More)
Advances in electronic-neural interfaces have shown great potential for both neuroscience research and medical devices. Much of the work to date has focused on short-range inductive links for power and communication transfer [1]. There is an emerging need for active miniaturized systems that stream neural data in the far field, which would enable the(More)
Many integrated circuit applications require a unique identification number (ID) on each die that can be read anytime during the lifetime of the chip. A robust read-only ID is important for labeling RFID tags, addressing low-power wireless sensor nodes, IC process quality control, and secure documentation. Traditional methods of writing addresses into ROMs(More)
— This paper presents two novel hardware random number generators (RNGs) based on latch metastability. We designed the first, the DC-nulling RNG, for extremely low power operation. The second, the FIR-based RNG, uses a predictive whitening filter to remove non-random components from the generated bit sequence. In both designs, the use of floating-gate(More)
The Bumblebee is a self-contained, ultra lightweight, low power 7.6 x 8.7 mm 2 wireless sensor capable of reliably transmitting data over 10 meters to a USB-compatible 433MHz receiver for approximately 3 days continuously on one 0.17g battery. With its small size, microvolt level noise floor, and 0.3g weight, the Bumblebee is well suited for on-body(More)
We have a developed an analog VLSI system that models the coordination of neurobiological segmental oscillators. We have implemented and tested a system that consists of a chain of eleven pattern generating circuits that are synaptically coupled to their nearest neighbors. Each pattern generating circuit is implemented with two silicon Morris-Lecar neurons(More)
— We present the NeuralWISP, a wireless neural interface operating from harvested RF energy. The NeuralWISP is compatible with commercial RFID readers and operates at a range up to 1m. It includes a custom low-noise, low power amplifier IC for processing the neural signal and an analog spike detection circuit for reducing digital computational requirements(More)
— We present a fully-integrated system for the detection and characterization of action potentials observed in extracellular neural recordings. The circuit includes an analog implementation of the nonlinear energy operator for spike detection. The minimum and maximum value of detected spikes are captured by peak detectors and digitized by an on-chip(More)
Rapid development in miniature implantable electronics are expediting advances in neuroscience by allowing observation and control of neural activities. The first stage of an implantable biosignal recording system, a low-noise biopotential amplifier (BPA), is critical to the overall power and noise performance of the system. In order to integrate a large(More)