Browsing by Author "Hsu, Li-Chi"

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A NEW SMALL-SIZED NON-DISPERSIVE INFRARED (NDIR) SENSOR AND ITS DRIVE/READOUT CIRCUITS
(2016)
Chao, Paul C. -P.
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Hsu, Li-Chi
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Tran, Trong-Hieu
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
A new miniaturized, non-dispersive, infrared (NDIR) sensor for CO2 intended to be installed in mobile phones and its drive/readout circuits are presented in this study. A typical NDIR sensor consists of three main components; an infrared (IR) light emitter (light source), a gas chamber, a photo detector (PD) light receiver) and the associated drive/readout circuits. The geometry of the gas chamber is optimized to minimize the total module . size to approximately 10 mm x 5 mm x 5 mm, which is much smaller than commercially-available gas sensors. Driver and readout circuits are successfully designed and taped out. The driver circuit intends to generate pulse width modulation (PWM) signal to control proper dimming of LED. The readout circuit, which acquires small signal from photo detector then converts to digital values, includes amplifier, low pass filter and analog-to digital converter (ADC). The proposed circuit is fabricated by the TSMC 0.35 mu m CMOS process, where the area is 4.527 mm(2) while power consumption is 60.16 mW for the whole chip. The resolution is less than 12 ppm along with time constant is 0.1 sec.
Design and development of a new wireless fall detection module for homecare
(2015-12-01)
Tran, Trong-Hieu
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Chao, Paul C. -P.
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Hsu, Li-Chi
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Chiu, Chun-Wei
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Kao, Yung-Hua
This study aims to develop a decision procedure and associated small-sized, wearable wireless hardware module for successful fall detections of subjects for homecare. The detection procedure is developed based on a newly-proposed two-level criteria framework. The first-level criterion is forged based on two real-time signal vector magnitudes (SVMs) to determine whether falls can occur. The baseline SVM is further modified to accommodate varied gestures of the subjects prior to fall. It is designed that the modified SVM, named SVMB, with level exceeding 2.5 G indicates that the subject has fallen. The criterion at the second level is developed to prevent false detections, which considers especially the cases that some particular body movements other than falling would induce large SVMB values, such as running. Results based on a number of experimental trials validate the effectiveness of the proposed two-level criterion to detect falls while prevent false detections. A total of 100 experimental falls were tested, an average accuracy rate of 97 % in fall detection is achieved.
Design and development of a wireless fall detection module for homecare
(2014-01-01)
Chao, Paul C-P
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Hsu, Li-Chi
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Li, Yu-Feng
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Chun, Chin-Wei
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電機工程學系