Jaeeun Jang

14.2 A 502GOPS and 0.984mW dual-mode ADAS SoC with RNN-FIS engine for intention prediction in automotive black-box system

Advanced driver-assistance systems (ADAS) are being adopted in automobiles for forward-collision warning, advanced emergency braking, adaptive cruise control, and lane-keeping assistance. Recently, automotive black boxes are installed in cars for tracking accidents or theft. In this paper, a dual-mode ADAS SoC is proposed to support both high-performance ADAS functionality in driving-mode (d-mode) and an ultra-low-power black box in parking-mode (p-mode). By operating in p-mode, surveillance recording can be triggered intelligently with the help of our intention-prediction engine (IPE), instead of always-on recording to extend battery life and prevent discharge.

21.1 A 79pJ/b 80Mb/s full-duplex transceiver and a 42.5μW 100kb/s super-regenerative transceiver for body channel communication

Recently, smart phones or head-mounted displays enables high definition (HD) video streaming and image data to be shared with friends while wearable smart sensors continuously monitor and send users physiological information to a smart watch. Body channel communication (BCC), which uses the human body as the communication channel [1], has demonstrated better human-friendly interface and energy-efficient performance compared with air channel communication. However, most of the previous BCC research used only the frequency band below 100MHz and were only focused on either low data rate (<;10Mb/s) healthcare applications [2-5] or high data rate (60Mb/s) multimedia data transfer [6]. Its available channel bandwidth was limited <; 100MHz and the interference from FM radio due to body antenna effect had a significant effect on its performance. Moreover, [6] did not support full duplex communication so that the user interaction with wearable devices was not possible in live video streaming or real-time VR game applications.

A 502-GOPS and 0.984-mW Dual-Mode Intelligent ADAS SoC With Real-Time Semiglobal Matching and Intention Prediction for Smart Automotive Black Box System

The advanced driver assistance system (ADAS) for adaptive cruise control and collision avoidance is strongly dependent upon the robust image recognition technology such as lane detection, vehicle/pedestrian detection, and traffic sign recognition. However, the conventional ADAS cannot realize more advanced collision evasion in real environments due to the absence of intelligent vehicle/pedestrian behavior analysis. Moreover, accurate distance estimation is essential in ADAS applications and semiglobal matching (SGM) is most widely adopted for high accuracy, but its system-on-chip (SoC) implementation is difficult due to the massive external memory bandwidth. In this paper, an ADAS SoC with behavior analysis with Artificial Intelligence functions and hardware implementation of SGM is proposed. The proposed SoC has dual-mode operations of high-performance operation for intelligent ADAS with real-time SGM in D-Mode (d-mode) and ultralow-power operation for black box system in parking-mode. It features: 1) task-level pipelined SGM processor to reduce external memory bandwidth by 85.8%; 2) region-of-interest generation processor to reduce 86.2% of computation; 3) mixed-mode intention prediction engine for dual-mode intelligence; and 4) dynamic voltage and frequency scaling control to save 36.2% of power in d-mode. The proposed ADAS processor achieves 862 GOPS/W energy efficiency and 31.4GOPS/mm2 area efficiency, which are 1.53× and 1.75× improvements than the state of the art, with 30 frames/s throughput under 720p stereo inputs.

A 0.54-mW duty controlled RSSI with current reusing technique for human body communication

A low power adaptive controlled current-reusing received signal strength indicator (RSSI) is proposed for the human body communication (HBC). The proposed RSSI has three low power features. First, the power on controller (PoC) scheme is proposed to achieve the duty control of the RSSI. It significantly reduces the average power consumption of RSSI over 90%. Second, the current stacking scheme is adopted to share both eight rectifiers and eight amplifiers, composing the RSSI. By the current reusing technique, the power consumption of the RSSI is reduced to 45%. In addition, the reconfigurable LNA is used in the front-end of HBC TRX. The RSSI adaptively controls the gain and noise figure of the LNA to optimize the power consumption. The proposed RSSI occupies 0.85mm2 in 0.18-μm CMOS technology.

A 540-

An ultra-low-power duty controlled received signal strength indicator (RSSI) is implemented for human body communication (HBC) in 180 nm CMOS technology under 1.5 V supply. The proposed RSSI adopted 3 following key features for low-power consumption; 1) current reusing technique (CR-RSSI) with replica bias circuit and calibration unit, 2) duty controller, and 3) reconfigurable gm-boosting LNA. The CR-RSSI utilizes stacked amplifier-rectifier-cell (AR-cell) to reuse the supply current of each blocks. As a result, the power consumption becomes 540 μW with +/-2 dB accuracy and 75 dB dynamic range. The replica bias circuit and calibration unit are adopted to increase the reliability of CR-RSSI. In addition, the duty controller turns off the RSSI when it is not required, and this function leads 70% power reduction. At last, the gm-boosting reconfigurable LNA can adaptively vary its noise and linearity performance with respect to input signal strength. Fro current reusing technique m this feature, we achieve 62% power reduction in the LNA. Thanks to these schemes, compared to the previous works, we can save 70% of power in RSSI and LNA.

\mu\text{W}

Electrical impedance tomography (EIT) has been studied to monitor lung ventilation because it is the only real-time lung imaging method without large equipment [1–2]. However, previous EIT systems just provided 2D cross-sectional image with limited spatial information of the lung and unneglectable volume detection error depending on the location of 2D EIT belt relative to the patients lung. In spite of its importance, the 3D-EIT has not been realized in lung monitoring because it has many design challenges such as noises incurred by complicated wiring, long cable length, wide variation in electrode contact and signal, and large personal-to-person impedance variation. In this paper, we present a portable 3D-EIT SoC for real-time lung ventilation monitoring with following 5 features: 1) The active electrodes (AEs) system to reduce coupling noise, 2) High output impedance current stimulator to inject stable current, 3) Impedance spectroscopy to enable both time-difference (TD) EIT and frequency-difference (FD) EIT, and to select an optimal frequency for TD-EIT, 4) Wide-dynamic range front-end circuit to detect variable ranges of signal with high-input impedance and CMRR, 5) Calibration to reduce the electrical characteristics variations of AEs.

Duty Controlled RSSI With Current Reusing Technique for Human Body Communication

A sticker-type system with hybrid integration of CMOS IC and organic optical sensors is proposed to monitor photoplethysmogram (PPG) signals. To solve problems with the previous solely organic sensor-based works, CMOS IC is implemented in 180 nm technology under 5 V/1.5 V dual power supply. The silver-wire printed planar-fashionable circuit board (P-FCB) is used to connect the CMOS IC with organic sensors. The proposed hybrid system has the five following key features: 1) Power-efficient structure of organic sensor; 2) Integrated analog front-end and digital processor; 3) Degradation compensation scheme; 4) Large parasitic elements optimized design; and 5) Motion artifact rejection scheme. The sticker-type PPG monitoring system has mass of only 2g, including the batteries, and consumes only

21.2 A 1.4mΩ-sensitivity 94dB-dynamic-range electrical impedance tomography SoC and 48-channel Hub SoC for 3D lung ventilation monitoring system

233~\mu \text{W}

Sticker-Type Hybrid Photoplethysmogram Monitoring System Integrating CMOS IC With Organic Optical Sensors

to operate. The PPG signal could be acquired from various body parts (finger, wrist, and neck). The peripheral oxygen saturation level (SpO2 extraction results are verified by comparison with a commercial sensor device.

A 635 μW non-contact compensation IC for body channel communication

A low-power non-contact compensation IC for body channel communication (BCC) is proposed. The proposed IC has 3 key building blocks. First, a contact status detection unit (CSDU) based on a capacitance sensor is adopted. Second, non-contact compensation unit (NCU) with inductor and capacitance bank is proposed. Third, a reconfigurable low noise amplifier (LNA) for impedance matching is adopted. The input impedance of the LNA is controlled by a digital controller for high Q compensation. Thanks to the proposed features, 14 dB channel compensation is achieved and the IC consumed only 635 μW in 65 nm CMOS technology with 1.2 V supply. The proposed work is the first BCC IC with non-contact compensation.