Towards Low Frequency Low NoiseLow Power System-on-Chip for Pervasive Healthcare

Towards Low Frequency Low Noise Low Power System-on-Chip for Pervasive Healthcare Lei Wang SIAT, Chinese Academy of Sciences 12th March 2010

SIAT Location Institute of Advanced Integration Technology Shenzhen Institutes of Advanced Technology Institute of Biomedical and Health Engineering Institute of Advanced Computing and Digital Engineering

Ubiquitous Monitoring Devices
Personalized
Continuous 24/7
Preventative
Earlier diagnosis
Home-based
Chronic diseases manage
Post-operative monitoring
Unobtrusive
Minimal interventions
Miniaturized
Integrated
Networked
Digitized
Smart
Various resources ASIC is the key technology for these devices Objective MINDS

Body Sensor Networks New devices New technologies New concepts

SoC is the key technology for ubiquitous monitoring and pervasive healthcare.
Self-contained with minimal off-chip components, size reduction makes monitoring devices more resilient. 10x
Power consumptions further reduced by fully-customized design. 10x
Cost-effective, beneficial for volume production. 10x
That is 1000 times performance enhancement comparing with using off-the-shelf components.
Moore’s Law -> More Than Moore (SoC)
Low Frequency Low Noise Low Power …
Motivation The human body is a significant application area of the semiconductor industry - Toumazou, Imperial College.

Architecture of the proposed SoC and associated test bench

Different MPWs SMIC 0.18um CMOS Low Frequency Low Noise Low Power

Performance Summary of the 3L SoC variable gain quantizer TX and RX < 5mW @1Mbps Fully-differential LNA 10MHz or 20MHz carrier frequency, FSK modulation Wireless Communication ARM0.3mW/MHz 256-point FFT < 0.6 mW/MHz All integrated simulation 1MHz - 10MHz Digital Processing Gated comparator, <90uW@250Kbps conversion rate Fully-differential, hybrid R-C DAC, 12-bit resolution 10Kbps - 250Kbps Analogue Digital Conversion <100uW per channel Fully-differential, input refer noise < 1.5uV@1Hz 0.5Hz-35Hz,14Hz-40Hz, 25Hz-250Hz, gain programmable Signal Acquisition Low Power Low Noise Low Frequency

Prospective Applications Interactive Gaming Control Targeted Muscle Re-innervations (sEMG) Next-generation Body Sensor Network platform Wearable Devices and Biofeedback Low-cost Homecare Electronics

Team Introduction Guang-Zhong Yang received Ph.D. in Computer Science from Imperial College London and has served as a senior and then principal scientist of the Cardiovascular Magnetic Resonance Unit of the Royal Brompton Hospital prior to assuming his current full-time academic post. He is widely regarded as the founder of Body Sensor Networks (BSN), which is attracting increasingly significant international focus. Lei Wang received his B.Eng in Information and Control Engineering and Ph.D in Biomedical Engineering, in 1995 and 2000, respectively, from Xi’an Jiaotong University, China. Subsequently he took various research roles at different UK universities. His research interests are Body Sensor Networks, Biomedical IC design and data fusion. He has published more than 50 scientific papers, co-authored one book and filed several patents. Zedong Nie received his M.D from Wuhan University of Science and Technology in 2006. His research interests include System on Chip architecture, biomedical signal processing, and digital IC design. Huang Jin received the M.S. degree in microelectronics from Peking University, Beijing, China, in 2006. His research interests include RF integrated circuit design, analog integrated circuit design and body channel communication. Jinyong Zhang received the M.E. degree in microelectronics from South China University of Technology, China, in 2009. His research interests include high-performance analog and mixed-signal circuit design for biomedical application. Benny YU received the MSc degree in IC Design Engineering from The Hong Kong University of Science and Technology, Hong Kong SAR, China, in 2008. His current research interests include low-power analog circuits design and layout for biomedical applications.

Towards Low Frequency Low NoiseLow Power System-on-Chip for Pervasive Healthcare

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