Browsing by Author "Chen, Hsin"

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A 0.5V 1.27mW Nose-on-a-Chip for Rapid Diagnosis of Ventilator-Associated Pneumonia
(2014-01-01)
Tang, Kea-Tiong
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Chiu, Shih-Wen
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Shih, Chung-Hung
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Chang, Chia-Ling
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Yang, Chia-Min
A 1-V 2.6-mW Environmental Compensated Fully Integrated Nose-on-a-Chip
(2018-10-01)
Chou, Ting-I
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Chang, Kwuang-Han
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Jhang, Jia-Yin
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Chiu, Shih-Wen
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Wang, Guoxing
Miniature gas detection system is desirable for many applications. In this brief, we propose a fully integrated nose-on-a-chip for mobile phones and wearable devices. The chip has 36 on-chip sensors, a 36-channel adaptive interface with an integrated programmable amplifier, a four-channel frequency readout interface, one on-chip temperature sensor, a successive approximation analog-to-digital converter, a scalable learning kernel cluster, and a reduced instruction set computing core with low-voltage static random-access memory. This chip is fabricated using the TSMC 180-nm CMOS process and consumes 2.6 mW at 1 V. on-chip temperature and humidity sensors are included in this system for acquiring environmental information. An environmental compensation algorithm based on common principal components analysis is also implemented for high-accuracy odor classification. This fully integrated nose-on-a-chip provides promising results for odor detection and classification for use in mobile and wearable device applications.
A Fully Integrated Nose-on-a-Chip for Rapid Diagnosis of Ventilator-Associated Pneumonia
(2014-12-01)
Chiu, Shih-Wen
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Wang, Jen-Huo
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Chang, Kwuang-Han
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Chang, Ting-Hau
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Wang, Chia-Min
Ventilator-associated pneumonia (VAP) still lacks a rapid diagnostic strategy. This study proposes installing a nose-on-a-chip at the proximal end of an expiratory circuit of a ventilator to monitor and to detect metabolite of pneumonia in the early stage. The nose-on-a-chip was designed and fabricated in a 90-nm 1P9M CMOS technology in order to downsize the gas detection system. The chip has eight on-chip sensors, an adaptive interface, a successive approximation analog-to-digital converter (SAR ADC), a learning kernel of continuous restricted Boltzmann machine (CRBM), and a RISC-core with low-voltage SRAM. The functionality of VAP identification was verified using clinical data. In total, 76 samples infected with pneumonia (19 Klebsiella, 25 Pseudomonas aeruginosa, 16 Staphylococcus aureus, and 16 Candida) and 41 uninfected samples were collected as the experimental group and the control group, respectively. The results revealed a very high VAP identification rate at 94.06% for identifying healthy and infected patients. A 100% accuracy to identify the microorganisms of Klebsiella, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida from VAP infected patients was achieved. This chip only consumes 1.27 mW at a 0.5 V supply voltage. This work provides a promising solution for the long-term unresolved rapid VAP diagnostic problem.
A Low Quiescent Current and Cross Regulation Single-Inductor Dual-Output Converter with Stacking MOSFET Driving Technique
(2017-01-01)
Ma, Yu-Sheng
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Yang, Wen-Hau
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Lin, Yen-Ting
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Chen, Hsin
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Lin, Li-Chi
the stacking MOSFET structure composed of low-voltage devices suffers from deteriorated transient response or large footprint area when capacitor-free or dominant pole compensation low dropout (LDO) regulator biases the driver. Due to self-stabilized feature, the proposed stacking MOSFET driving (SMD) technique effectively drives the power stage and greatly reduces noise interference from the noisy node to achieve low cross regulation (CR) in the single-inductor dual-output (SIDO) converter. Moreover, two inherent low dropout (LDO) regulators in the SMD technique completely regulate two outputs with low quiescent current at no load condition. Experimental results show the tested chip fabricated in 0.25 mu m process with low cross regulation of 0.015mV/mA and ultra-low quiescent current of 5 mu A at no load condition.
A Single-Inductor Dual-Output Converter With the Stacked MOSFET Driving Technique for Low Quiescent Current and Cross Regulation
(2019-03-01)
Chen, Hsin
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Huang, Chao-Jen
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Kuo, Chun-Chieh
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Lin, Li-Chi
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Ma, Yu-Sheng
Stacked MOSFET structures made of low-voltage devices suffer from degraded transient response or large footprint when a capacitorless or dominant-pole compensated low-dropout (LDO) regulator biases the driver. Due to the self-stabilizing nature, the proposed stacked MOSFET driver (SMD) technology effectively drives the power stage and greatly reduces the noise at the switching nodes for low cross regulation (CR) in a single-inductor dual-output (SIDO) converter. In addition, two inherent LDO regulators in SMD technology fully regulate the dual outputs with the advantage of low quiescent current at no-load conditions. The experimental results show that the test chip fabricated under the 0.25-mu m process has low CR of 0.015 mV/mA and ultralow quiescent current of 5 mu A under no-load conditions.
Decomposition of EEG Signals for Multichannel Neural Activity Analysis in Animal Experiments
(2010)
Vigneron, Vincent
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Chen, Hsin
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Chen, Yen-Tai
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Lai, Hsin-Yi
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Chen, You-Yin
We describe in this paper some advanced protocols for the discrimination and classification of neuronal spike waveforms within multichannel electrophysiological recordings. Sparse decomposition was used to serarate the linearly independent signals underlying sensory information in cortical spike firing patterns. We introduce some modifications in the the IDE algorithm to take into account prior knowledge on the spike waveforms. We have investigated motor cortex responses recorded during movement in freely moving rats to provide evidence for the relationship between these patterns and special behavioral task.
Development of a Multisite, Closed-loop Neuromodulator for the Theranosis of Neural Degenerative Diseases
(2018-01-01)
Chen, Hsin
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Chang, Yen-Chung
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Yeh, Shih-Rung
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Hsieh, Chih-Cheng
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Tang, Kea-Tiong
Stimulating specific brain regions has been found useful for treating neural disorders, such as the Parkinson's disease, epilepsy, depression, etc. However, how electrical stimulation modulates neural activities remains not fully understood. As animal models provide the advantage of recording and stimulating different disease-related regions simultaneously, this paper introduces the latest development of a multisite, closed-loop-controlled microsystem for investigating novel treatments on neural degenerative diseases with freely-moving rats. The algorithms for recognizing pathological neural activities automatically are also developed and realized in hardware, so as to control the stimulation in a closed loop and in real time. The pilot studies on the efficacy of treating the Parkinson's disease with closed-loop-controlled stimulation will be presented and discussed. Finally, the feasibility of modelling and probing how neural dynamics and connectivity are modulated by stimulation will be an important topic for future research.
Dictionary-Based Classification Models. Applications for Multichannel Neural Activity Analysis
(2009)
Vigneron, Vincent
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Chen, Hsin
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Chen, Yen-Tai
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Lai, Hsin-Yi
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Chen, You-Yin
We describe in this paper advanced protocols for the discrimination and classification of neuronal spike waveforms within multichannel electrophysiological recordings. The programs are capable of detecting and classifying the spikes from multiple, simultaneously active neurons, even in situations where there is a high degree of spike waveform superposition on the recording channels. Sparse Decomposition (SD) approach was used to define the linearly independent signals underlying sensory information in cortical spike tiring patterns. We have investigated motor cortex responses recorded during movement in freely moving rats to provide evidence for the relationship between these patterns and special behavioral task. Ensembles of neurons were simultaneously recorded in this during long periods of spontaneous behaviour. Waveforms provided from the neural activity were then processed and classified. Typically, most information correlated across neurons in the ensemble were concentrated in a small number of signals. This showed that these encoding vectors functioned as a feature detector capable of selectively predicting significant sensory or behavioural events. Thus it encoded global magnitude of ensemble activity, caused either by combined sensory inputs or intrinsic network activity. SD on an overcomplete dictionary has recently attracted a lot of attention in the literature. because of its potential application in many different areas including Compressive Sensing (CS). SD approach is compared to the generative approach derived from the likelihood-based framework, in which each class is modeled by a known or unknown density function. The classification of electroencephalographic (EEG) waveforms present 2 main statistical issues: high dimensional data and signal representation.
Digital Low-Dropout Regulator with Anti PVT-Variation Technique for Dynamic Voltage Scaling and Adaptive Voltage Scaling Multicore Processor
(2017-01-01)
Tsou, Wen-Jie
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Yang, Wen-Hau
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Lin, Jian-He
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Chen, Hsin
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Chen, Ke-Horng
Direct Detection of Long, Periodic, ssDNA nanostructures Assembled on CMOS Transistor Arrays
(2009)
Lin, Ming-Yu
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Chang, Sheng-Ren
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Kao, Jiann-Shiun
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Chen, Hsin
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Yang, Yuh-Shyong
DNA is a wonderful material for the construction of nanostructures for a variety of applications. This paper describes a novel platform integrating single-stranded DNA (ssDNA) nanotemplates with CMOS-compatible, field-effect sensors. The field-effect sensor was based on oxide-semiconductor field-effect transistors (OSFETs), which were monolithically-integrated with signal-processing circuits to enhance the signal-to-noise ratio, and to detect the construction of ssDNA nanotemplate from complex DNA-protein interactions. The ssDNA nanotemplate on the transistor arrays was prepared by isothermal rolling circle amplification (RCA) through DNA aptamer-protein recognition and self-assembly strategy. The growth of the DNA nanostructure was monitored in situ, real-time and label-free on OSFET.
EEG Dynamics in Inhibition of Left-hand and Right-hand Responses during Auditory Stop-Signal Task
(2014)
Chikara, Rupesh Kumar
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Perumal, Ramesh
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Ko, Li-Wei
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Chen, Hsin
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生物科技學系
An experimental design is programmed using the presentation tool to investigate the global response inhibition process by quantifying the parameters such as inhibition efficiency, stop-signal delay (SSD) and stop-signal reaction time (SSRT) in the stop-signal paradigm. The aim of this study is to explore the response inhibition mechanisms in the left-hand and right-hand responses by using ERP and ERSP results obtained from the EEG data of different subjects. The inhibition efficiency of the right-hand response and left-hand response appears to be independent of each other as there is no significant difference between them. From these results, the inhibition mechanisms corresponding to these two regions of the brain may be viewed as statistically independent processes. Further, we inferred that the response inhibition mechanisms for both left-hand and right-hand responses have approximately the same spectral power observation analysis and we conclude that these processes are statistically independent of each other.
Flexible UV-Ozone-Modified Carbon Nanotube Electrodes for Neuronal Recording
(2010-05-18)
Hsu, Hui-Lin
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Teng, I-Ju
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Chen, Yung-Chan
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Hsu, Wei-Lun
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Lee, Yu-Tao
Carbon nanotubes were grown on flexible polyimide substrates at temperatures below 400 degrees C as electrodes for extracellularly neuronal recording. The electrical charge-transfer and electrochemical properties of such CNT electrodes were enhanced by UV-ozone exposure, which induced the formation of C-O, C=O, and O-C=O bonds and reduced the CNT/electrolyte interfacial impedance while increasing the interfacial capacitance.
High Accuracy Knee Voltage Detection for Primary-Side Control in Flyback Battery Charger
(2017-04-01)
Yang, Shang-Hsien
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Tsai, Tsung-Hsun
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Chen, Hsin
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Chiu, Chao-Chang
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Chen, Ke-Horng
In a primary-side control flyback charger, the accuracy of a conventional knee voltage detection (KVD) approach to obtain the output voltage is influenced by the inclusion of a snubber circuit. Although the snubber circuit dampens the ringing voltages due to switching, it also affect the resonance frequency which would reduce the timing of the sampling circuit, resulting in the inaccurate sampling of output voltage. By analyzing the snubber circuit and its resonance on the primary side, this paper implements a proposed accuracy knee voltage detection (AKVD) technique to compensate for the induced resonance frequency. Furthermore, the proposed constant current (CC) regulator ensures the accuracy of CC mode by compensating the sensing current error caused by the switching delay of the power transistor. A prototype consisting of a test chip fabricated with a 0.5 mu m BCD process demonstrates a voltage accuracy exceeding 99.63%. This is achieved by mitigating abnormal detections and thus ensuring correct control of charging current throughout the charging period.
Immobilized rolling circle amplification on extended-gate field-effect transistors with integrated readout circuits for early detection of platelet-derived growth factor
(2016-07)
Lin, Ming-Yu
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Hsu, Wen-Yang
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Yang, Yuh-Shyong
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Huang, Jo-Wen
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Chung, Yueh-Lin
Detection of tumor-related proteins with high specificity and sensitivity is important for early diagnosis and prognosis of cancers. While protein sensors based on antibodies are not easy to keep for a long time, aptamers (single-stranded DNA) are found to be a good alternative for recognizing tumor-related protein specifically. This study investigates the feasibility of employing aptamers to recognize the platelet-derived growth factor (PDGF) specifically and subsequently triggering rolling circle amplification (RCA) of DNAs on extended-gate field-effect transistors (EGFETs) to enhance the sensitivity. The EGFETs are fabricated by the standard CMOS technology and integrated with readout circuits monolithically. The monolithic integration not only avoids the wiring complexity for a large sensor array but also enhances the sensor reliability and facilitates massive production for commercialization. With the RCA primers immobilized on the sensory surface, the protein signal is amplified as the elongation of DNA, allowing the EGFET to achieve a sensitivity of 8.8 pM, more than three orders better than that achieved by conventional EGFETs. Moreover, the responses of EGFETs are able to indicate quantitatively the reaction rates of RCA, facilitating the estimation on the protein concentration. Our experimental results demonstrate that immobilized RCA on EGFETs is a useful, label-free method for early diagnosis of diseases related to low-concentrated tumor makers (e.g., PDGF) for serum sample, as well as for monitoring the synthesis of various DNA nanostructures in real time.
Self-adjustable Feed-forward Control and Auto-tracking Off-time Control Techniques for 95% Accuracy and 95% Efficiency AC-DC Non-isolated LED Driver
(2015)
Chen, Hsin
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Chen, Chi-Wei
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Hsieh, Hsueh-Yi
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Chen, Ke-Horng
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Tsai, Tsung-Yen
the non-isolated buck topology for LED driver is proposed to reduce volume and cost without the need of large transformer. Besides, in the entire universal range of AC input voltage, the proposed self-adjusted feed-forward control (SAFFC) technique ensures small variation in the LED current. The auto-tracking off-time control (ATOTC) technique is also adopted to adjust the off time to guarantee the current accuracy is better than that of the peak current control (PCC) technique while and the efficiency is better than that of the hysteresis current control (HCC) technique. Test chip fabricated in VIS 0.5 mu m 700V ultra-high voltage (UHV) process demonstrates power factor higher than 0.97, averaged 95% high accuracy, and 95% high efficiency.