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This paper presents a wearable wireless surface electromyogram (sEMG) integrated interface that utilizes a proposed analog pseudo-wavelet preprocessor (APWP) for signal acquisition and pattern recognition. The APWP is integrated into a readout integrated circuit (ROIC), which is fabricated in a 0.18-μm complementary metal-oxide-semiconductor (CMOS) process. Based on this ROIC, a wearable device module and its wireless system prototype are implemented to recognize five kinds of real-time handgesture motions, where the power consumption is further reduced by adopting low-power components. Real-time measurements of sEMG signals and APWP data through this wearable interface are wirelessly transferred to a laptop or a sensor hub, and then they are further processed to implement the pseudo-wavelet transform under the MATLAB environment. The resulting APWP-augmented pattern-recognition algorithm was experimentally verified to improve the accuracy by 7 % with a real-time frequency analysis.

This paper presents a reconfigurable multisensor mobile interface architecture that is applicable to heterogeneous sensor applications and also easy to generate new types of combined services. The multisensor interface attributes compactness and flexibility to reconfigurable readout integrated circuits (ROICs) and migration of signal processing and computation burdens from a sensor tag to a smartphone. Two reconfigurable ROICs which were designed and fabricated in a 0.18-μm CMOS process generate raw digital data from environmental and healthcare sensors. Their detected raw data are wirelessly sent to the smartphone where real-time calibration and postprocessing are performed optimally for each sensor. In an application to industrial systems, an in-vehicle system prototype supporting combined monitoring services of air-quality and healthcare was integrated into a steering wheel cover and experimentally verified to provide real-time measurement of three environmental sensor signals and two healthcare physiological signals with the results displayed on a smartphone.

This paper presents a flexible multi-functional physiological sensing system that provides multiple noise-immune readout architectures and hybrid-sensing capability with an analog pre-processing scheme. The proposed multi-functional system is designed to support five physiological detection methodologies of piezo-resistive, pyro-resistive, electro-metric, opto-metric and their hybrid, utilizing an in-house multi-functional e-skin device, in-house flexible electrodes and a LED-photodiode pair. For their functional verification, eight representative physiological detection capabilities were demonstrated using wearable device prototypes. Especially, the hybrid detection method includes an innovative continuous measurement of blood pressure (BP) while most previous wearable devices are not ready for it. Moreover, for effective implementation in the form of the wearable device, post-processing burden of the hybrid method was much reduced by integrating a proposed analog pre-processing scheme, where only simple counting process and calibration remain to estimate the BP. This multi-functional sensor readout circuits and their hybrid-sensing interface are fully integrated into a single readout integrated circuit (ROIC), which is designed to implement three readout paths: two electrometric readout paths and one impedometric readout path. For noise-immune detection of the e-skin sensor, a pseudo-differential front-end with a ripple reduction loop is proposed in the impedometric readout path, and also state-of-the-art body-oriented noise reduction techniques are adopted for the electrometric readout path. The ROIC is fabricated in a CMOS process and in-house e-skin devices and flexible electrodes are also fabricated.

A multi-purpose sensor interface that provides dual-mode operation of fingerprint sensing and physiological signal detection is presented. The dual-mode sensing capability is achieved by utilizing inter-pixel shielding patterns as capacitive amplifier’s input electrodes. A prototype readout circuit including a fingerprint panel for feasibility verification was fabricated in a 0.18 mm CMOS process. A single-channel readout circuit was implemented and multiplexed to scan two-dimensional fingerprint pixels, where adaptive calibration capability against pixel-capacitance variations was also implemented. Feasibility of the proposed multi-purpose interface was experimentally verified keeping low-power consumption less than 1.9 mW under a 3.3 V supply.

This paper presents a portable magnetic induction tomography (MIT) transceiver integrated circuit to miniaturize conventional equipment-based MIT systems. The miniaturized MIT function is enabled through single-chip transceiver implementation. The proposed MIT transceiver utilizes a phase-locked loop (PLL) for frequency sweeping and a phase-domain sigma&ndash, delta modulator with phase-band auto-tracking for a full-range fine-phase resolution. The designed transceiver is fabricated and verified to achieve the measured signal to noise and distortion ratio (SNDR) of 101.7 dB. Its system-level prototype including in-house magnetic sensor coils is manufactured and functionally verified for four different material types.