A silicon implementation of the fly's optomotor control system

Flies are capable of stabilizing their body during free flight by using visual motion information to estimate self-rotation. We have built a hardware model of this optomotor control system in a standard CMOS VLSI process. The result is a small, low-power chip that receives input directly from the real world through on-board photoreceptors and generates motor commands in real time. The chip was tested under closed-loop conditions typically used for insect studies. The silicon system exhibited stable control sufficiently analogous to the biological system to allow for quantitative comparisons

Biologically inspired analog IC for visual collision detection

Journal ArticleWe have designed and tested a single-chip analog VLSI sensor that detects imminent collisions by measuring radially expanding optic flow. The design of the chip is based on a model proposed to explain leg-extension behavior in flies during landing approaches. We evaluated a detailed version of this model in simulation using a library of 50 test movies taken through a fisheye lens. The algorithm was evaluated on its ability to distinguish movies ending in collisions from movies in which no collision occurred. This biologically inspired algorithm is capable of 94% correct performance in this task using an ultra-low-resolution (132-pixel) image as input. A new elementary motion detector (EMD) circuit was developed to measure optic flow on a CMOS focal-plane sensor. This EMD circuit models the bandpass nature of large monopolar cells (LMCs) immediately postsynaptic to photoreceptors in the fly visual system as well as a saturating multiplication operation proposed for Reichart-type motion detectors. A 16 x 16 array of two-dimensional motion detectors was fabricated in a standard 0.5µm CMOS process. The chip consumes 140 µW of power from a 5 V supply. With the addition of wide-angle optics, the sensor is able to detect collisions 100-400 ms before impact in complex, real-world scenes. Index Terms-CMOS imager, collision detection, Gilbert multiplier, insect vision, neuromorphic systems, optic flow, smart sensor

Designing efficient inductive power links for implantable devices

Journal ArticleDue to limited battery life and size limitations, many implantable biomedical devices must be powered inductively. Because of weak coupling between implanted and external coils, obtaining high power efficiency is a challenge. Previous authors have addressed the issue of optimizing power efficiency in these systems. In this paper, we further this analysis for the case of planar spiral "pancake" coils at low RF frequencies (100 kHz - 10 MHz). We consider practical design constraints such as component variation, power amplifier limitations, and coil voltage limits. We introduce a new, complete expression for total power link efficiency

Wide-linear-range subthreshold CMOS transconductor employing the back-gate effect

Journal ArticleWe present a CMOS circuit that utilizes the back-gate effect to extend the linear range of a subthreshold MOS transconductor. Previous designs of wide-linear-range transconductors using bipolar transistors employed multiple differential pairs with input offset voltages used to shift the individual transfer functions. These voltages were chosen to maximize the linear range of the summed differential pair currents. Equivalent offset voltages were generated by sizing emitter areas appropriately. Similar techniques may be applied to MOS circuits by scaling WIL ratios, but transistor size increases exponentially as we extend the linear range by adding more differential pairs. We introduce a method of adding equivalent offset voltages by biasing the back gate (i.e., body) of well devices appropriately. Test circuits built in a standard 0.5μm CMOS process and using few transistors exhibit improved linear range over standard single-differential pair transconductors

Design of integrated circuits to observe brain activity

Journal ArticleThe ability to monitor the simultaneous electrical activity of multiple neurons in the brain enables a wide range of scientific and clinical endeavors. Recent efforts to merge miniature multielectrode neural recording arrays with integrated electronics have revealed significant circuit design challenges. Weak neural signals must be amplified and filtered using low-noise circuits placed close to the electrodes themselves, but power dissipation must strictly be limited to prevent tissue damage due to local heating. In modern recording systems with 100 or more electrodes, raw data rates of 15 Mb/s or more are easily produced. Micropower wireless telemetry circuits cannot transmit information at such high rates, so data reduction must be performed in the implanted device. In this paper, we present integrated circuits and design techniques that address the twin problems of neural signal amplification and data reduction for this severely size- and power-limited application

Low-power, low-noise CMOS amplifier for neural recording applications

Journal ArticleThere is a need among scientists and clinicians for lownoise, low-power biosignal amplifiers capable of amplifying signals in the mHz to kHz range while rejecting large dc offsets generated at the electrode-tissue interface. The advent of fully-implantable multielectrode arrays has created the need for fully-integrated micropower amplifiers. We designed and tested a novel bioamplifier that uses a MOS-bipolar pseudo-resistor to amplify signals down to the mHz range while rejecting large dc offsets. We derive the theoretical noise-power tradeoff limit - the noise efficiency factor - for this amplifier and demonstrate that our VLSI implementation approaches that limit. The resulting amplifier, built in a standard 1.5μm CMOS process, passes signals from 0.lmHz to 7.2kHz with an input-referred noise of 2.2μVrms and a power dissipation of 80μW while consuming 0.16mmz of chip area

Versatile integrated circuit for the acquisition of biopotentials

Journal ArticleElectrically active cells in the body produce a wide variety of voltage signals that are useful for medical diagnosis and scientific investigation. These biopotentials span a wide range of amplitudes and frequencies. We have developed a versatile front-end integrated circuit that can be used to amplify many types of bioelectrical signals. The 0.6-μm CMOS chip contains 16 fully-differential amplifiers with gains of 46 dB, 2μVrms input-referred noise, and bandwidths programmable from 10Hz to 10kHz

Fly-inspired VLSI vision sensors

Journal ArticleEngineers have long looked to nature for inspiration. The diversity of life produced by five billion years of evolution provides countless existence proofs of organic machines with abilities that far surpass those of our own relatively crude automata. We have learned how to harness large amounts of energy and thus far exceed the capabilities of biological systems in some ways (e.g., supersonic flight, space travel, and global communications). However, biological information processing systems (i.e., brains) far outperform today's most advanced computers at tasks involving real-time pattern recognition and perception in complex, uncontrolled environments. If we take energy efficiency into account, the performance gap widens. The human brain dissipates 12 W of power, independent of mental activity. A modern microprocessor dissipates around 50 W, and is equivalent to a vanishingly small fraction of our brain's functionality

Low-power analog VLSI visual collision detector

Journal ArticleWe have designed and tested a single-chip analog VLSI sensor that detects imminent collisions by measuring radially expansive optic flow. The design of the chip is based on a model proposed to explain leg-extension behavior in flies during landing approaches. A new elementary motion detector (EMD) circuit was developed to measure optic flow. This EMD circuit models the bandpass nature of large monopolar cells (LMCs) immediately postsynaptic to photoreceptors in the fly visual system. A 16 × 16 array of 2-D motion detectors was fabricated on a 2.24 mm × 2.24 mm die in a standard 0.5-μm CMOS process. The chip consumes 140 μW of power from a 5 V supply. With the addition of wide-angle optics, the sensor is able to detect collisions around 500 ms before impact in complex, real-world scenes

Single-chip CMOS visual orientation sensor

Journal ArticleWe present a single-chip, low-power vision sensor capable of measuring local edge orientation across a wide field of view. The sensor was fabricated in a 0.5-µm CMOS process. Quadratic spatial filters were implemented using differential pairs and an "antibump" circuit to give a current-mode output signal. Small spatial filters requiring only nearest-neighbor connectivity were used for edge detection. The sensor is able to detect its orientation relative to the dominant horizontal and vertical edges in indoor, man-made environments. This sensor consumes only 120 µW of power and could be used to control the attitude of an autonomous agent in an indoor environment