BIOELECTRONICS Rahul Sarpeshkar Associate Professor Research Lab of Electronics Electrical Engineering and Computer Science Bio-inspired Electronics:Electronics inspired by biology. Biomedical Electronics:Ultra-low-power electronics for medical applications CBA NSF talk. 10/12/06
BIOLOGICAL COCHLEAR NUMBERS Dynamic Range 120 dB at input Power Dissipation ~14W (Estimated) Power Supply Voltage ~150 mV Volume ~35mm x 1cm x 1 cm Det. Thr. At 3 kHz 0.05 Angstroms at eardrum Frequency Range 20 Hz – 20 kHz (in babies?) Outlet Taps ~35,000 Filter Computations >1 GFLOPS Phase locking threshold ~5 kHz Information is reported with enough fidelity so that the auditory system has thresholds for ITD discrimination at ~10 s Freq. discrimination at 2 Hz (at 1kHz) Loudness discrimination ~1 dB
Transmission Line Analogy: Fluid is an Inductor, Membrane Stiffness is a Capacitor
Transformer HF (5GHz) LF (250MHz) Single stage Bias & programming The RF cochlea • UMC 0.13µm CMOS process
Spiking-Neuron-Inspired Analog-to-Digital Converter At 0.12pJ/quantization level, a version of this A-to-D may be the most energy-efficient A-to-D ever reported thus far. It is the first time-based A-to-D converter whose conversion time scales linearly with bit precision.
An Ultra-Low-Power Analog Bionic Ear Processor The Bionic Ear (Cochlear Implant) Block Diagram of Processor • Microphone • Cable • Speech Processor • Coil • Implanted Receiver • Electrodes • Auditory Nerve The 251mW 16-channel Programmable Processor Performance Summary • 20x power improvement over best design today • Better or comparable performance in 1.5mm technology today than A-D-then-DSP solution at the end of Moore’s law in an advanced nanometer technology. • First test with a deaf patient was successful, and she understood speech with it.
An Analog Architecture for Neural Recording, Decoding, and Learning Allows 1kbs-1 instead of 24Mbs-1 data bandwidth across the skull Adaptive 7mW neural amplifier SPICE simulation of performance with real monkey data
PRINCIPLES FOR ENERGY-EFFICIENT DESIGN IN BIOLOGY AND ELECTRONICS • Special-Purpose Architectures • Exploit analog basis functions for efficient preprocessing before digitization or signal-to-symbol conversion • Slow-and-Parallel • Exponential computing primitives (high gm/I ratio in transistor) 5. Balance Computation and Communication Costs 6. Adaptive Architectures with Learning