Detection of human respiration using square‐wave modulated electromagnetic impulses

Ong, Keat Ghee; Dreschel, William R.; Grimes, Craig A.

doi:10.1002/mop.10759

Cited by 12 publications

(2 citation statements)

References 8 publications

(11 reference statements)

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“…A sensor is attached to the bridge of the nose, which is highly intrusive. Ong et al used a square-wave modulated electromagnetic impulse to monitor human respiration rate [31]. This approach is intrusive and may also not be very safe.…”

Section: B Measurement Techniquesmentioning

confidence: 99%

An Intelligent Noninvasive Sensor for Driver Pulse Wave Measurement

et al. 2007

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Noninvasive sensors to detect human physiological parameters are becoming more and more important. This is especially useful to monitor driver state as driver-vehicle system is a safety-critical system. Unfortunately, current technologies in these noninvasive sensors development are not satisfactory. In this research, we developed an intelligent integrated device called "smart wheel" to monitor drivers' physiology. Specifically, a group of polyvinylidene fluoride (PVDF) sensor, semiconductor temperature sensor, and piezoresistive sensor were integrated into a driving steering wheel. The developed device has the capability of measuring a driver's pulse wave, breathing wave, skin temperature, and gripping force in a noninvasive manner and in real time. A pilot experiment was carried out to verify the pulse wave measurement of this intelligent sensor and the result was found satisfactory.Index Terms-Driver-vehicle system, intelligent sensor, noninvasive, physiological parameter, pulse wave.

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Section: B Measurement Techniquesmentioning

confidence: 99%

An Intelligent Noninvasive Sensor for Driver Pulse Wave Measurement

et al. 2007

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“…Recently, adaptation capability under dynamically changing environments becomes more important since advanced applications need service-oriented, pervasive, and ubiquitous computing [1,2]. In this paper, we discuss about the framework of evolution system that can behave in an adaptive and robust manner under dynamic variations of application environments.…”

Section: Introductionmentioning

confidence: 99%

Sensor based Environment Adaptive Learning System for Person Authorization

Lee

Lee²,

Chung

et al. 2008

2008 Second International Conference on Future Generation Communication and Networking

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This paper presents a robust distributed architecture for adaptive and intelligent systems, called EAS (Environment Adaptive Learning Scheme), with self-learning capability to use under dynamic and uneven environments. Our proposed system adopts the concepts of situation-awareness with the evolutionary computations where the working environments are modeled and identified as environmental situations. We have used ART2 for Environment modeling while unsupervised learning algorithm for environment identification. Environment adaptive algorithm, for its adaptive criteria, is used to explore action configuration for each identified situation to implement our concept. We have achieved very encouraging experimental results for CCD camera visual sensor based face detection, recognition system and ECG sensor system.

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