Extremely-Wide-Range Supply-Independent CMOS Voltage References for Telemetry-Powering Applications

This paper reports a voltage reference circuit in standard CMOS process. It exhibits excellent supply independency for a wide input voltage range, which is of great importance in telemetry-powered systems. This circuit is based on the well-known V GS -reference supply-independent current reference circuit, but it is designed to serve as a voltage reference . While the reference current generated by this circuit varies with the supply voltage, a self-compensating mechanism can be found in voltage-mode operation of the circuit that results in a supply-independent reference voltage. This supply independency is well observed in the static operation of the circuit over an extremely wide input range, as well as in its dynamic behavior for high frequency ripples on the input voltage. Based on the proposed idea, a multi-output voltage reference and a CMOS DC level shifter are also designed. The proposed voltage reference circuits have been fabricated using MOSIS 1.6 μm standard CMOS process. The basic voltage reference provides 957 μV/V static supply dependency, rejects input ripples of up to 8 MHz by 60± 3dB, and consumes only 15.8–36.9 μA when the input voltage varies in the range 2.6–12 V.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44083/1/10470_2006_Article_1644.pd

Implantable Biomedical Microsystems: A New Graduate Course in Biomedical Circuits and Systems

AbstractAfter 2+ decades of research on design anddevelopment of implantable biomedical microsystems, now it istime to organize research achievements in this area in aconsolidated and pedagogical form. This paper introduces a newgraduate course in advanced biomedical circuits and systems.Designed for graduate students with electrical and biomedicalengineering backgrounds, this course provides a generaloverview on the multi-disciplinary field of implantablebiomedical microsystems. In addition to some introductorymaterials on physiology and biology where needed, this coursecomprises extensive contents and in-depth discussions on bothsystem- and circuit-level aspects of the design of implantablemicrosystems. Moreover, this course also deals with issuesconcerned with design for implantability and envisions fortestability. Wireless interfacing, signal processing,microelectrode array fabrication, and circuit design forimplantable neural recording microsystems are studiedextensively. Different design aspects of neural stimulationmicrosystems, cochlear implants, and visual prostheses are alsoreviewed briefly.4 Halama

A framework for on-implant spike sorting based on salient feature selection

On-implant spike sorting methods utilize static waveform features for the classification. Here, the authors propose a framework based on dynamic selection of features that is more accurate and requires less memory

Intertwined-pulse modulation for compressive data telemetry

Abstract This paper presents a novel approach for anisochronous pulse-based modulation. In the proposed approach, referred to as the intertwined-pulse modulation (IPM), every pair of consecutive symbols overlap in time. This allows for shortening the time allocated for the transmission of the symbols, hence achieving temporal compaction while the data goes through the line encoding step in a digital communication system. The IPM is also uniquely superior to other existing anisochronous pulse-based modulation schemes in the fact that it exhibits robust symbol error rate against unwanted variations in both rise/fall times of the pulses in the modulated waveform, and in the threshold level used for data detection on the receiver side. An experimental setup was developed to implement an IPM encoder using standard digital hardware, and an IPM decoder as a part of the receiver system in software. According to the experimental results (supported by simulation results and theoretical studies), for the data mean value of mid-full-scale range, the proposed IPM scheme exhibits a time-domain compaction rate of up to 209.2%