Inventory reference ISSN 1812-7231 Klin.inform.telemed. Volume 1, Issue 2, 2004, Pages 237-239
Author(s) Bekir Karlik и Yousif Al-Bastaki
The College of Information Technology University of Bahrain
Article title Bad breathe diagnosis system using OMX-GR sensor and Neural Network for telemedicine
In work the description of the developed telemedical system for diagnostics of diseases under the analysis of exhaled air — odors, vapors, and gases (on the example of a sugar diabetes). The system will consist of digital sensor OM". Results of the analysis will be transformed by the sensor to the digital form and with the help of telemetry are transferred in the removed computer which has the software on the basis of neural network. The computer is trained to distinguish various aromas and them to classify, that then is used for diagnostics of a pathology (sugar diabetes).
Keywords the sensor of the analysis of odors, a telemedicine, neural networks, computer diagnostic systems
1. P. E. Keller, et al., Electronic Noses and Their Applications, Proceedings of the World Congress on Neural Networks'96, Mahwah, NJ, USA, 1996, 928–931.
2. T. Nakamoto et al. Odor recorder using active odor sensing system, Sensors and Actuators, B 76, 2001, 465–469.
3. P. Erdi and G. Barna, Neurodynamic Approach to Odor Processing, Proceeding of the International Joint Conference on Neural Networks (IJCNN'91), ISBN: 0078033016441, IEEE Press, Piscataway, NJ, 2, 1991, 653–656.
4. T. Nakamoto, et al., Gas/Odor Identification by Semiconductor Gas Sensor Array and an Analog Artificial Neural Network Circuit, Proceeding International Conference on Microelectronics, Bandung, Indonesia, 4, 1992, 1–9.
5. R. E. Baby, et al., 2000, Electronic nose: a useful tool for monitoring environmental contamination, Sensors and Actuators B 69 (3): 214–218.
6. T. Nakamoto and H. Hiramatsu, 2002, Study of odor recorder for dynamical change of odor using QCM sensors and neural network, Sensors and Actuators, B 85, 263–269.
7. B. Karlik and Y. Bastaki, Real Time Monitoring Odor Sensing System Using OMX-GR Sensor and Neural Network, WSEAS Transactions on Electronics, 1/2, 2004, 337–342.
8. P. Boilot, et al., Detection of Bacteria Causing Eye Infections using a Neural Network Based Electronic Nose System, in Electronic Nose and Olfaction 2000, Gardner, J. W., Persaud, K. C., editors, IOP Publishing, Bristol, UK, 189–196.
9. P. E. Keller, et al., Transmission of Olfactory Information for Telemedicine, Interactive Technology and the New Paradigm for Healthcare, K. Morgan, R. M. Satava, H. B. Sieburg, R. Matteus, and J. P. Christensen, (ed.s), IOS Press, Amsterdam, The Netherlands, 1995, 168–72.
10. A. K. Pavlou and A. P. Turner, Sniffing Out the Truth: Clinical Diagnosis Using the Electronic Nose, Clin. Chem. Lab. Med. 2000, 38(2): 99 – 112.
11. A. K. Pavlou, et al., Use of an Electronic Nose System for Diagnoses of Urinary Tract Infections, Biosens. Bioelectron. 2002, 17(10), 893–899.
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