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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Yifan Jiang Junmin Jiang Yan Lu State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macao China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China

This paper presents a fully-integrated reconfigurable dual-ring switched-capacitor (DRSC) converter that overcomes the coarse output voltage resolution limitation of traditional switched-capacitor (SC) converters. The proposed DRSC converter cascades multiple stages of SC cells and achieves a fine voltage conversion ratio resolution from 1/n to (n-1)/n, where n is the number of phases. To improve efficiency, the bottom-plate parasitic loss is mitigated by the charge redistribution technique. Also, the power switches are divided into several segmentation groups to reduce the output ripple with different loads. This work is designed in a 180nm CMOS process with 30 cascaded reconfigurable SC power cells. It achieves a wide output voltage range of 0.5-3.3V from a battery input voltage (2.7-4.2V). The load regulation is implemented with a pulse-frequency modulation (PFM) control. The simulated peak efficiency is 78%, with a load current range of 0 to 20mA, using 1.5nF on-chip capacitors in total.

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Window-Based Quaternion Principal Component Analysis of Eye Gaze Dynamics for Depression Severity Prediction

Window-Based Quaternion Principal Component Analysis of Eye ...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Hung, Kevin Man, Gary Man-Tat Chui, John Kwok-Tai Chow, Daniel Hung-Kay Ling, Bingo Wing-Kuen Pun, Sio-Hang Liu, Tai-Wa The School of Science and Technology Hong Kong Metropolitan University Hong Kong The Education University of Hong Kong The Department of Health and Physical Education Hong Kong The School of Information Engineering Guangdong University of Technology Guangdong Province China University of Macau The State key Laboratory of Analog and Mixed Signal Vlsi China The School of Nursing and Health Studies Hong Kong Metropolitan University Hong Kong

ISBN: (纸本)9798350350821

Depression is a global health issue that necessitates severity identification for effective treatment. Although early detection and monitoring of mental abnormalities are crucial for mitigating adverse conditions, standard diagnostic approaches for depression, including self-rating scales and clinician-based interviews, fall short of meeting these needs. Wearable sensors offer an opportunity for unobtrusive evaluation of patients' status throughout their daily life, but it presents challenges in feature extraction and depression severity prediction. Studies have shown that eye gaze dynamics in term of 3-D rotations are a good indicator of depression. However, their traditional representation in Euler angles is computationally inefficient and overlooks the channel-wise interrelations, thereby reducing their discriminative power in medical diagnosis. This paper proposes a novel approach to address these challenges. It uses a window-based quaternion principal component analysis algorithm to extract features of eye gaze dynamics, preserving the channel-wise interrelations and temporal information. The proposed algorithm was tested and validated using a benchmark depression dataset from previous studies. Results showed that the algorithm achieved higher accuracy in depression severity prediction with a root mean square error of 5.08, outperforming existing state-of-the-art prediction methods that only use visual data. The results were further analyzed and discussed, providing valuable insights into the effectiveness and potential applications of wearable sensor for mental health diagnostics. © 2024 IEEE.

关键词： Mean square error

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A Two-Phase Linear-Exponential Incremental ADC with Second-order Noise Coupling

A Two-Phase Linear-Exponential Incremental ADC with Second-o...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Qingxun Wang Yuhan Pan Kaiquan Chen Yu Lin Biao Wang Liang Qi Department of Micro-Nano Electronics Shanghai Jiao Tong University Shanghai China State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macao China

This paper presents a two-phase linear-exponential incremental analog-to-digital converter (IADC) with using second-order noise coupling (NC). In the first phase, it works as a first-order IADC. Then the second-order NC path is activated in the second phase to significantly expedite the accumulation speed. Moreover, during the second phase, the integrator is disabled to achieve a large maximum stable amplitude (MSA). Simulations demonstrated that the proposed architecture could achieve a higher signal-to-quantization-noise ratio (SQNR) while avoiding the noise penalty and keeping the high effectiveness of data weighting averaging (DWA) compared with the prior art with using first-order NC. Mathematical analysis and further simulation results are presented to confirm the theory of the proposed structure.

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Distributed Quantitative Vibration Demodulation with Direct-detection based Phase-sensitive OTDR Assisted by Acousto-optic Phase Shifting Technique 19

Distributed Quantitative Vibration Demodulation with Direct-...

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19th International Conference on Optical Communications and Networks, ICOCN 2021

作者： Liu, Shuaiqi Yu, Feihong Xu, Weijie Vai, Mang I. Shao, Liyang Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen China State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau China

ISBN: (纸本)9781665424462

Quantitative demodulation of the external vibration is demonstrated with a direct-detection based Phase-sensitive OTDR system. An acousto-optic modulator is utilized for both probe pulse generation, and optical phase shifting simultaneously. The fiber under test is probed with a phase shifted double pulse pair scheme, with the phase difference between the two pulses periodically shifted with a π/2 step. The optical phase information is retrieved using the homodyne inter-pulse interference signal with direct detection only. Experimental results show good consistence between the phase demodulation result and the applied vibration amplitude under a cost-effective system configuration. © 2021 IEEE.

关键词： Demodulation

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MemMIMO: A Simulation Framework for Memristor-Based Massive MIMO Acceleration

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Xu, Jiawei Zheng, Yi Stathis, Dimitrios Wang, Ruijia Shen, Ruisi Zheng, Li-Rong Zou, Zhuo Hemani, Ahmed University of Macau State-Key Laboratory of Analog and Mixed-Signal VLSI Institute of Microelectronics Faculty of Science and Technology ECE Department China Fudan University State Key Laboratory of Integrated Chips and Systems School of Information Science and Technology Shanghai China KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Stockholm Sweden

Memristor-based crossbar architectures have proven highly effective for matrix vector multiplication (MVM) operations, making them a promising solution for accelerating the MVMs widely used in precoding algorithms for multiple input multiple output (MIMO) wireless communication systems. However, real-world implementation of memristor-based computing systems face challenges due to commonly observed non-idealities in both the devices themselves and the circuits they’re built into. To facilitate a rapid design flow and investigate the impact of non-idealities, an integrated open-source simulation framework MemMIMO is developed. The simulation framework estimates the accuracy and hardware performance of the computing system, offering a variety of flexible design options. MemMIMO integrates a behavioral model of the mix-signal architecture with a digital front-end. There are three major building blocks in MemMIMO: the device fitting block, the mapping block, and the performance estimation block. These blocks work together to map the complex MVMs in precoding algorithms for MIMO systems to crossbar-based architectures that incorporate memristor models characterized by physical device behavior. Using two typical use cases targeting six-generation (6G) massive MIMO communication as case studies, MemMIMO is used to model different memristor devices, explore the impact of non-idealities on system accuracy, and benchmark circuit-level performance metrics including area, speed, and power. © 1982-2012 IEEE.

关键词： System-on-chip

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Impacts of Cortical Regions on EEG-based Classification of Lexical Tones and Vowels in Spoken Speech

Impacts of Cortical Regions on EEG-based Classification of L...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Mingtao Li Sio Hang Pun Fei Chen State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Taipa Macau China Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen China

Speech impairment is one of the most serious problems for patients with communication disorders, e.g., stroke survivors. The brain-computer interface (BCI) systems have shown the potential to alternatively control or rehabilitate the neurological damages in speech production. The effects of different cortical regions in speech-based BCI systems are essential to be studied, which are favorable for improving the performance of speech-based BCI systems. This work aimed to explore the impacts of different speech-related cortical regions in the electroencephalogram (EEG) based classification of seventy spoken Mandarin monosyllables carrying four vowels and four lexical tones. Seven audible speech production-related cortical regions were studied, involving Broca’s and Wernicke’s areas, auditory cortex, motor cortex, prefrontal cortex, sensory cortex, left brain, right brain, and whole brain. Following the previous studies in which EEG signals were collected from ten subjects during Mandarin speech production, the features of EEG signals were extracted by the Riemannian manifold method, and a linear discriminant analysis (LDA) was regarded as a classifier to classify different vowels and lexical tones. The results showed that when using electrodes from whole brain, the classifier reached the best performances, which were 48.5% for lexical tones and 70.0% for vowels, respectively. The vowel classification results under Broca’s and Wernicke’s areas, auditory cortex, or prefrontal cortex were higher than those under the motor cortex or sensory cortex. No such differences were observed in the lexical tone classification task.

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A Single-Channel 14b 500 MS/s Pipelined-SAR ADC with Reference Ripple Mitigation Techniques and Adaptive-Biased Floating Inverter Amplifier

A Single-Channel 14b 500 MS/s Pipelined-SAR ADC with Referen...

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2022 IEEE Asian Solid-state Circuits Conference, A-SSCC 2022

作者： Jiang, Wenning Zhu, Yan Chan, Chi-Hang Martins, Rui State-Key Laboratory of Analog and Mixed-Signal VLSI/IME-DECE/FST University of Macau China Frontier Institute of Chip and System/Zhangjiang Fudan International Innovation Center Fudan University Shanghai China On Leave Instituto Superior Técnico Universidade de Lisboa Portugal

ISBN: (数字)9781665471435

ISBN: (纸本)9781665471435

The accuracy and speed of the residue handover process are crucial in two-step architectures. Advanced residue amplifiers (RAs) [1]-[5] enable a fast residue handover operation in Pipelined ADCs but often necessitate calibrations. Furthermore, with a short acquisition time and a large capacitive DAC in high-resolution designs, it is challenging to ensure the reference voltage of the DAC is sufficiently settled before the amplification. Eventually, the reference buffer (RBUF) calls for a considerable power and/or area overhead. This work introduces an adaptive-biased floating inverter amplifier (ABFIA) as the RA in a single-channel 14b 500MS/s Pipelined-SAR (Pipe-SAR) ADC, reaching a 16x calibration-free gain in a short time. Further, by leveraging a Reference Ripple Cancellation (RRC)coarse SAR ADC and Reference Ripple Neutralization (RRN)assisted RBUF, it avoids large sizing multi-input-pair in the comparator and the stringent timing requirement in conventional RRN [6] and RRC [7] technique, respectively. © 2022 IEEE.

关键词： Pipelines

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A 12.87-dB Gain 10.5-dBm OPldB60-to-66-GHz LNA in 0.15-μm GaAs pHEMT Technology

A 12.87-dB Gain 10.5-dBm OPldB60-to-66-GHz LNA in 0.15-μm G...

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Asia Pacific Conference on Postgraduate Research in microelectronics & Electronics (PrimeAsia)

作者： Xuefeng Li Yuting Wang Tianxiang Wu Yong Chen Junyan Ren Shunli Ma State Key Laboratory of ASIC and System School of Microelectronics Fudan University Shanghai China State-Key Laboratory of Analog and Mixed-Signal VLSI and IME/ECE-FST University of Macau Macao China

This paper presents a V-band low noise amplifier (LNA) implemented in a $\boldsymbol{0.15-\mu} \mathbf{m}$ Gallium Arsenide (GaAs) pseudomorphic high electron-mobility transistor (pHEMT) technology. The LNA adopts a three-stage common-source (CS) topology. Each transistor has a bias circuit, and the microstrip-line inductor is used to realize the input noise matching network, the interstage, and the output matching network. Circuit simulations show that our LNA scores a 12.87-dB small-signal gain, the 3-dB bandwidth ranges from 60 GHz to 66 GHz, and the current consumption is 30 mA under a 5-V supply voltage. Its noise figure is 5.9 dB, and the output 1-dB compression point is 10.5 dBm. The chip area is $\boldsymbol{1.32}\times \boldsymbol{1.5}\mathbf{mm}^{2}$ .

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Single-Cell Electric Impedance Sensor Based on Integrated Circuit Chip

Single-Cell Electric Impedance Sensor Based on Integrated Ci...

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BioSensors Conference (BioSensors), IEEE

作者： Wenhao Hui Ren Shen Pui-In Mak Rui P. Martins Ka-Meng Lei Yanwei Jia State-Key Laboratory of Analog and Mixed-Signal VLSI Institute of Microelectronics University of Macau Macau China Faculty of Science and Technology – ECE University of Macau Macau China On Leave from Instituto Superior Técnico Universidade de Lisboa Portugal Faculty of Health Sciences University of Macau Macau China

ISBN: (数字)9798350395136

ISBN: (纸本)9798350395143

Drug screening using in-vitro primary tumor cells offers a direct approach to assessing drug sensitivity, playing a crucial role in personalized cancer diagnosis and precision medicine. However, existing tumor drug screening methods encounter a common challenge: the presence of normal cells alongside cancer cells in patient tumor samples complicates the accurate evaluation of drug effects on cancer cells alone. In this study, we introduce a real-time impedance sensing method based on an integrated circuit (IC) chip to distinguish between cancer and normal cells at the single-cell level, enabling individual analysis of their sensitivity to drugs. This innovative approach integrates impedance calculation circuits directly beneath an array of 352 single-cell-sized sensing electrodes, effectively reducing the high background noise that typically hampers the detection of ultra-weak signals. We validated this method across various cancer types, demonstrating its capability for impedance-based classification on IC chips. Our findings highlight the potential of this real-time, non-invasive, and label-free single-cell distinguishing method for precision medicine, laying the foundation for the development of ultra-miniaturized biological signal sensors and the realization of lab-on-IC technology.

关键词： Integrated circuits Drugs Precision medicine Cells (biology) Real-time systems Sensors Impedance Biosensors Cancer Tumors

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A Preliminary Exploration of Magnetic Resonance Coupled Human Body Communication in Out-to-In Body Transmission for Leadless Pacemakers

A Preliminary Exploration of Magnetic Resonance Coupled Huma...

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IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications

作者： Shuang Yang Ziliang Wei Lina Chen Hanyue Liu Sio Hang Pun Mang I Vai Yueming Gao College of Physics and Information Engineering Fuzhou University Fuzhou China Affiliated High School of Fujian Normal University Fuzhou China State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macau China

ISBN: (数字)9798350322996

ISBN: (纸本)9798350323009

Out-to-in (O2I) body wireless communication is crucial for achieving personalized parameter modulation and ensuring reliable cardiac rhythm management in leadless cardiac pacemakers. Compared to traditional radio frequency (RF) wireless communication technology, magnetic resonance coupled human communication (MRC-HBC) technology is a promising method of O2I communication that utilizes human tissue as a conduction medium for electrical signals. In this paper, we present an O2I body communication method that combines low power consumption and high reliability for leadless cardiac pacemakers to enhance the performance of programmed management of leadless cardiac pacemakers (LCPs) and prolong the operating life of the pacemakers. Based on the dielectric properties of human tissues, a transceiver coil was designed for executing O2I body magnetic resonant coupling signal transmission. An O2I body multilayer electromagnetic model for finite element numerical computation was further constructed, and a chest phantom experimental platform was built for mutual verification. The results show that the highest channel gains of simulation and phantom experiment is −35.02 dB @ 13.56 MHz and −27.84 dB @ 13.56 MHz respectively, when the relative distance between the transceiver coils is in the range of 8–12 cm, which represents a significant advantage over the RF wireless communication methods used in previous studies.

关键词： Wireless communication Radio frequency Couplings Magnetic multilayers Pacemakers Magnetic resonance Phantoms

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