Title :
Analog Integrated Circuits Design for Processing Physiological Signals
Author :
Li, Yan ; Poon, Carmen C Y ; Zhang, Yuan-Ting
fDate :
7/2/1905 12:00:00 AM
Abstract :
Analog integrated circuits (ICs) designed for processing physiological signals are important building blocks of wearable and implantable medical devices used for health monitoring or restoring lost body functions. Due to the nature of physiological signals and the corresponding application scenarios, the ICs designed for these applications should have low power consumption, low cutoff frequency, and low input-referred noise. In this paper, techniques for designing the analog front-end circuits with these three characteristics will be reviewed, including subthreshold circuits, bulk-driven MOSFETs, floating gate MOSFETs, and log-domain circuits to reduce power consumption; methods for designing fully integrated low cutoff frequency circuits; as well as chopper stabilization (CHS) and other techniques that can be used to achieve a high signal-to-noise performance. Novel applications using these techniques will also be discussed.
Keywords :
MOSFET; analogue integrated circuits; biomedical electronics; electro-oculography; electrocardiography; electroencephalography; electromyography; electroretinography; integrated circuit design; medical signal processing; neurophysiology; noise; patient monitoring; power consumption; analog front-end circuits; analog integrated circuit design; bulk-driven MOSFET; chopper stabilization; floating gate MOSFET; full integrated low cutoff frequency circuits; health monitoring; implantable medical devices; input-referred noise; log-domain circuits; lost body functions; low power consumption; physiological signal processing; power consumption; subthreshold circuits; wearable medical devices; Analog circuits; Biomedical equipment; Biomedical monitoring; Low power electronics; MOSFETs; Power demand; Threshold voltage; Transconductance; Analog integrated circuits; low frequency; low noise; low power; medical devices; Electronics, Medical; Equipment Design; Humans; Prostheses and Implants; Signal Processing, Computer-Assisted;
Journal_Title :
Biomedical Engineering, IEEE Reviews in
DOI :
10.1109/RBME.2010.2082521