Seunghyun Oh

Body Sensor Networks: A Holistic Approach From Silicon to Users

Body sensor networks (BSNs) are emerging cyber-physical systems that promise to improve quality of life through improved healthcare, augmented sensing and actuation for the disabled, independent living for the elderly, and reduced healthcare costs. However, the physical nature of BSNs introduces new challenges. The human body is a highly dynamic physical environment that creates constantly changing demands on sensing, actuation, and quality of service (QoS). Movement between indoor and outdoor environments and physical movements constantly change the wireless channel characteristics. These dynamic application contexts can also have a dramatic impact on data and resource prioritization. Thus, BSNs must simultaneously deal with rapid changes to both top-down application requirements and bottom-up resource availability. This is made all the more challenging by the wearable nature of BSN devices, which necessitates a vanishingly small size and, therefore, extremely limited hardware resources and power budget. Current research is being performed to develop new principles and techniques for adaptive operation in highly dynamic physical environments, using miniaturized, energy-constrained devices. This paper describes a holistic cross-layer approach that addresses all aspects of the system, from low-level hardware design to higher level communication and data fusion algorithms, to top-level applications.

A 116nW multi-band wake-up receiver with 31-bit correlator and interference rejection

This paper presents a 116nW wake-up radio complete with crystal reference, interference compensation, and baseband processing, such that a selectable 31-bit code is required to toggle a wake-up signal. The front-end operates over a broad frequency range, tuned by an off-chip band-select filter and matching network, and is demonstrated in the 402-405MHz MICS band and the 915MHz and 2.4GHz ISM bands with sensitivities of -45.5dBm, -43.4dBm, and -43.2dBm, respectively. Additionally, the baseband processor implements automatic threshold feedback to detect the presence of interferers and dynamically adjust the receivers sensitivity, mitigating the jamming problem inherent to previous energy-detection wake-up radios. The wake-up radio has a raw OOK chip-rate of 12.5kbps, an active area of 0.35mm2 and operates using a 1.2V supply for the crystal reference and RF demodulation, and a 0.5V supply for subthreshold baseband processing.

21.3 A 6.45μW self-powered IoT SoC with integrated energy-harvesting power management and ULP asymmetric radios

A 1 trillion node internet of things (IoT) will require sensing platforms that support numerous applications using power harvesting to avoid the cost and scalability challenge of battery replacement in such large numbers. Previous SoCs achieve good integration and even energy harvesting [1][2][3], but they limit supported applications, need higher end-to-end harvesting efficiency, and require duty-cycling for RF communication. This paper demonstrates a highly integrated, flexible SoC platform that supports multiple sensing modalities, extracts information from data flexibly across applications, harvests and delivers power efficiently, and communicates wirelessly.

A −32dBm sensitivity RF power harvester in 130nm CMOS

This paper discusses a RF power harvester optimized for sensitivity and therefore wireless range, for applications requiring intermittent communication. The RF power harvester produces a 1V output at -32dBm sensitivity and 915MHz. This is achieved using a CMOS rectifier operating in the subthreshold region and an off-chip impedance matching network for boosting the received voltage. Equations predicting the rectifier performance are presented and verified through measurements of multiple rectifiers using different transistors in a 130nm CMOS process.

Exploiting Channel Periodicity in Body Sensor Networks

This paper models the periodic characteristics of body sensor network (BSN) wireless channels measured using custom hardware in the 900-MHz and 2.4-GHz bands. The hardware logs received signal strength indication (RSSI) values of both bands simultaneously at a sample rate of 1.3 kS/s. Results from a measurement campaign of BSNs are shown and distilled to reveal characteristics of BSN channels that can be exploited for reducing the power of wireless communication. A new channel model is introduced to add periodicity to existing 802.15.6 WBAN path loss equations. New parameters, activity factor and location factor, are introduced to estimate the model parameters. Finally, a strategy for exploiting the periodic characteristics of the BSN channel is presented as an example, along with the power savings from using this strategy.

A 6.45

This paper presents a batteryless system-on-chip (SoC) that operates off energy harvested from indoor solar cells and/or thermoelectric generators (TEGs) on the body. Fabricated in a commercial 0.13 μW process, this SoC sensing platform consists of an integrated energy harvesting and power management unit (EH-PMU) with maximum power point tracking, multiple sensing modalities, programmable core and a low power microcontroller with several hardware accelerators to enable energy-efficient digital signal processing, ultra-low-power (ULP) asymmetric radios for wireless transmission, and a 100 nW wake-up radio. The EH-PMU achieves a peak end-to-end efficiency of 75% delivering power to a 100 μA load. In an example motion detection application, the SoC reads data from an accelerometer through SPI, processes it, and sends it over the radio. The SPI and digital processing consume only 2.27 μW, while the integrated radio consumes 4.18 μW when transmitting at 187.5 kbps for a total of 6.45 μW.

\mu{\rm W}

In 1968, Volker Strassen, a young German mathematician, announced a clever algorithm to reduce the asymptotic complexity of n×n matrix multiplication from the order of n 3 to n 2.81. It soon became one of the most famous scientific discoveries in the 20th century and provoked numerous studies by other mathematicians to improve upon it. Although a number of improvements have been made, Strassens algorithm is still optimal in his original framework, the bilinear systems of 2 × 2 matrix multiplication, and people are still curious how Strassen developed his algorithm. We examined it to see if we could automatically reproduce Strassens discovery using a search algorithm and find other algorithms of the same quality. In total, we found 608 algorithms that have the same quality as Strassens, including Strassens original algorithm. We partitioned the algorithms into nine different groups based on the way they are constructed. This paper was made possible by the combination of genetic search and linear-algebraic techniques. To the best of our knowledge, this is the first work that automatically reproduced Strassens algorithm, and furthermore, discovered new algorithms with equivalent asymptotic complexity using a search algorithm.

Self-Powered SoC With Integrated Energy-Harvesting Power Management and ULP Asymmetric Radios for Portable Biomedical Systems

In this paper, we present a step recovery diode (SRD) based ultra-wideband (UWB) transmitter. No custom integrated circuits (ICs) are used, and all of the components are commercially available off-the-shelf products, targeting low-cost and fast turn-around. UWB pulses are generated using SRDs, and pulse position modulation (PPM) is implemented by a microcontroller. Detailed analysis and equations for the SRD-based impulse generation are provided and verified with experimental results. This UWB transmitter has a measured full width half maximum (FWHM) pulse width of 213ps, pulse amplitude of 1.6V, and peak power of 17dBm. The data rate is 2.5MHz, which is limited by the maximum clock frequency of the microcontroller. The supply voltage for the entire circuit is 3V, which is compatible with coin batteries. The power consumption of the SRD pulse generator is 57mW, and the total power consumption of the complete transmitter is 70mW.