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Tytuł artykułu

MOX based E- nose for non-invasive biomedical applications

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Warianty tytułu
PL
Wykorzystanie analizy wydychango powietrza do wykrywania chorób
Języki publikacji
EN
Abstrakty
EN
The non-invasive method to diagnosis any disease is an attractive topic of research due to its rapid, cost effective, convenient and efficient technique. The Health status of a patient can be directly known by examined of volatile organic compound (VOC) of a patient, and this VOC can be studied by an electronic nose (e-nose). E- Nose can be easily detect different types of diseases such as lung cancer, diabetics, by analyzing the exhaled breath of a patient. In the proposed work, a brief overview has been provided about different techniques used to develop the E-nose. The importance of Low temperature co-fired ceramics (LTCC) based breath analyzer and future objectives has discussed.
PL
EW artykule przedstawiono koncepcję wykorzystania analizatora zapachów tzw. E-nosa do wykrywania chorób na podstaiw badania wydychanego powietrza. Przedstawiono różne techniki analizy. Szczególną uwagę poświecono czujnikowi typu LTCC.
Rocznik
Strony
119--122
Opis fizyczny
Bibliogr. 30 poz., rys.
Twórcy
  • FKEKK, UTeM, Melaka, Malaysia
  • AMITY University Rajasthan, Kant Kalwar, NH 11-C, Delhi Highway, Jaipur 303002, Rajasthan, India
  • FKEKK, UteM, Melaka, Malaysia
autor
  • AMITY University Rajasthan, Amity Education Valley, Kant Kalwar, NH-11C, Jaipur-Delhi Highway, Jaipur 303002, India
Bibliografia
  • [1] Hsu, C. M., Liao, W. Y., Luo, C. H., & Chou, T. C. (2007) The 2.4 GHz biotelemetry chip for healthcare monitoring system, Sensors and Actuators A: Physical, 139, No. 1-2, 245-251.
  • [2] Turner, C., Španěl, P., & Smith, D. (2005). A longitudinal study of breath isoprene in healthy volunteers using selected ion flow tube mass spectrometry (SIFT-MS). Physiological Measurement, 27(1), 13.
  • [3] Saidi, T., Zaim, O., Moufid, M., El Bari, N., Ionescu, R., & Bouchikhi, B. (2018). Exhaled breath analysis using electronic nose and gas chromatography–mass spectrometry for noninvasive diagnosis of chronic kidney disease, diabetes mellitus and healthy subjects. Sensors and Actuators B: Chemical, 257, 178-188.
  • [4] Amann, A., & Smith, D. (Eds.). (2013). Volatile biomarkers: non-invasive diagnosis in physiology and medicine. Newnes.
  • [5] D’Amico, A., Pennazza, G., Santonico, M., Martinelli, E., Roscioni, C., Galluccio, G., ... & Di Natale, C. (2010). An investigation on electronic nose diagnosis of lung cancer. Lung cancer, 68(2), 170-176.
  • [6] Dragonieri, S., Schot, R., Mertens, B. J., Le Cessie, S., Gauw, S. A., Spanevello, A., ... & Bel, E. H. (2007). An electronic nose in the discrimination of patients with asthma and controls. Journal of Allergy and Clinical Immunology, 120(4), 856-862.
  • [7] Wu, C. C., Chiu, S. W., & Tang, K. T. (2019). An Electronic Nose System for Rapid Detection of Ketamine Smoke. IEEE Sensors Letters, 3(8), 1-4.
  • [8] Deng, C., Zhang, J., Yu, X., Zhang, W., & Zhang, X. (2004). Determination of acetone in human breath by gas chromatography–mass spectrometry and solid-phase microextraction with on-fiber derivatization. Journal of Chromatography B, 810(2), 269-275.
  • [9] Chakraborty, S., Banerjee, D., Ray, I., & Sen, A. (2008). Detection of biomarker in breath: A step towards noninvasive diabetes monitoring. Current Science, 237-242.
  • [10] Nasution, T. I., Nainggolan, I., Hutagalung, S. D., Ahmad, K. R., & Ahmad, Z. A. (2013). The sensing mechanism and detection of low concentration acetone using chitosan-based sensors. Sensors and Actuators B: Chemical, 177, 522-528.
  • [11] Davies, S., Spanel, P., & Smith, D. (1997). Quantitative analysis of ammonia on the breath of patients in end-stage renal failure. Kidney international, 52(1), 223-228.
  • [12] Park, Y., Yoo, R., ryull Park, S., Lee, J. H., Jung, H., Lee, H. S., & Lee, W. (2019). Highly sensitive and selective isoprene sensing performance of ZnO quantum dots for a breath analyzer. Sensors and Actuators B: Chemical, 290, 258-266.
  • [13] Phillips, M., Cataneo, R. N., Cummin, A. R., Gagliardi, A. J., Gleeson, K., Greenberg, J., ... & Rom, W. N. (2003). Detection of lung cancer with volatile markers in the breath. Chest, 123(6), 2115-2123.
  • [14] Chen, X., Xu, F., Wang, Y., Pan, Y., Lu, D., Wang, P., & Zhang, W. (2007). A study of the volatile organic compounds exhaled by lung cancer cells in vitro for breath diagnosis. Cancer: Interdisciplinary International Journal of the American Cancer Society, 110(4), 835-844.
  • [15] Yan, K., Zhang, D., Wu, D., Wei, H., & Lu, G. (2014). Design of a breath analysis system for diabetes screening and blood glucose level prediction. IEEE transactions on biomedical engineering, 61(11), 2787-2795.
  • [16] Moorhead, K., Lee, D., Chase, J. G., Moot, A., Ledingham, K., Scotter, J., ... & Endre, Z. (2007, August). Classification algorithms for SIFT-MS medical diagnosis. In 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 5178-5181). IEEE.
  • [17] Smith, D., & Španěl, P. (2005). Selected ion flow tube mass spectrometry (SIFT‐MS) for on‐line trace gas analysis. Mass spectrometry reviews, 24(5), 661-700.
  • [18] Wang, C., Mbi, A., & Shepherd, M. (2009). A study on breath acetone in diabetic patients using a cavity ringdown breath analyzer: exploring correlations of breath acetone with blood glucose and glycohemoglobin A1C. IEEE Sensors Journal, 10(1), 54-63.
  • [19] áP MILLER, G., & áB WINSTEAD, C. (1997). Inductively coupled plasma cavity ringdown spectrometry. Journal of Analytical Atomic Spectrometry, 12(9), 907-912.
  • [20] Blatt, R., Bonarini, A., Calabro, E., Della Torre, M., Matteucci, M., & Pastorino, U. (2007, August). Lung cancer identification by an electronic nose based on an array of MOS sensors. In 2007 International Joint Conference on Neural Networks (pp. 1423-1428). IEEE.
  • [21] Wang, C., Yin, L., Zhang, L., Xiang, D., & Gao, R. (2010). Metal oxide gas sensors: sensitivity and influencing factors. sensors, 10(3), 2088-2106.
  • [22] Lee, J., Choi, N. J., Lee, H. K., Kim, J., Lim, S. Y., Kwon, J. Y., ... & Yoo, D. J. (2017). Low power consumption solid electrochemical-type micro CO2 gas sensor. Sensors and Actuators B: Chemical, 248, 957-960.
  • [23] Jain, Y. K., & Khanna, V. K. (2007, December). Thick film, LTCC or silicon microhotplate for gas sensor and other applications. In 2007 International Workshop on Physics of Semiconductor Devices (pp. 714-717). IEEE.
  • [24] Kulhari, L., & Khanna, P. K. (2018). Design, simulation and fabrication of LTCC-based microhotplate for gas sensor applications. Microsystem Technologies, 24(5), 2169-2175.
  • [25] Yan, Y. Z., Lu, H. X., & Tang, X. P. (2015). Fabrication of typical 3D structure on ltcc for microsystem.
  • [26] Rydosz, A. (2018). Sensors for enhanced detection of acetone as a potential tool for noninvasive diabetes monitoring. Sensors, 18(7), 2298.
  • [27] Kulhari, L., Chandran, A., Ray, K., & Khanna, P. K. (2019). Design, fabrication and characterization of LTCC microhotplates for gas-sensing application. Microelectronics International.
  • [28] Kulhari, L., Ray, K., Paptan, A., Suri, N., & Khanna, P. K. (2020). Development of LTCC micro‐hotplate with PTC temperature sensor for gas‐sensing applications. International Journal of Applied Ceramic Technology, 17(3), 1430-1439.
  • [29] Kulhari, L., Ray, K., Suri, N., & Khanna, P. K. (2020). Detection and characterization of CO gas using LTCC microhotplates. Sādhanā, 45(1), 1-6.
  • [30] Rettig, F., & Moos, R. (2004). Ceramic meso hot-plates for gas sensors. Sensors and Actuators B: Chemical, 103(1-2), 91-97
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f4226e3f-b2bf-4261-9689-97c25df893e2
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