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Abstrakty
Embolism - blocking of small arteries by small gaseous or solid bodies - may result in local ischaemia and very serious consequences. The embolizing elements produce ultrasonic Doppler signals with characteristic features. The basic requirement when detecting emboli is to discriminate between the actual embolic signals and the artifacts. The classification algorithm proposed employs signal level data and particle velocity data. The off-line software environment (C++) enables to set the sensitivity and temporal resolution of the analysis. Each analysed event is described with a number of parameters, like onset and duration, velocity at peak power, sample volume length and ratio of the power to the mean power of the signal. Its performance was positively validated on Doppler signals containing embolic signals from either solid and gaseous emboli and artifacts. The off-line software environment proposed is a starting platform for further studies on the emboli detection.
Słowa kluczowe
Wydawca
Czasopismo
Rocznik
Tom
Strony
35--49
Opis fizyczny
Bibliogr. 17 poz., rys., tab., wykr.
Twórcy
autor
- Institute for Precision and Biomedical Engineering, Faculty of Mechatronics, Warsaw University of Technology. św. A. Boboli 8, 02-525 Warsaw, Poland
autor
- Institute for Precision and Biomedical Engineering, Faculty of Mechatronics, Warsaw University of Technology. św. A. Boboli 8, 02-525 Warsaw, Poland
Bibliografia
- [1] Markus H.S., Harrison M.J.: Microembolic signal detection using ultrasound. Stroke. 1995, 26, 1517-1519.[
- [2] Austen W.G., Howry D.H.: Ultrasound as a method to detect bubbles or particulate matter in the arterial line during cardiopulmonary bypass. J. Surg. Res. 1964, 5, 283-284.
- [3] Spencer M.P., Campbell S.D., Sealey J.L., Henry F.C., Lindbergh J.: Experiments on decompression bubbles in the circulation using ultrasonic and electromagnetic flowmeters. J. Occup. Med. 1969, 11, 238-244.
- [4] Spencer M.P., Thomas G.I., Nicholls S.C.: Detection of middle cerebral artery emboli during carotid endarterectomy using transcranial Doppler ultrasonography. Stroke, 1990, 21, 415-423.
- [5] Markus H., Loh A., Brown M.M.: Detection of circulating cerebral emboli using Doppler ultrasound in a sheep model. J. Neurol. Sci. 1994, 122, 117-124.
- [6] Ackerstaff R.G.A., Babikian V.L., Georgiadis D., Russell D., Siebler M., Spencer M.P., Stump D.: Basic identification criteria of doppler microembolic signals. Consensus committee of the Ninth International Cerebral Hemodynamic Symposium. Stroke. 1995, 26, 1123.
- [7] Markus H., Loh A., Brown M.M.: Computerized detection of cerebral emboli and discrimination from artifact using doppler ultrasound. Stroke, 1993, 24, 1667-1672.
- [8] Markus H., Culinane M., Reid G.: Improved automated detection of embolic signals using a novel frequency filtering approach. Stroke, 1999, 30, 1610-1615.
- [9] Abts L.R., Beyer R.T., Gailetti M., Richardson P.D., Karron A., Massimino A., Karlson K.E.: Computerized discrimination of microemboli in extracorporeal circuits. Am. J. Surg., 1978, 135, 535-538.
- [10] Ries E, Tiemann K., Pohl C., Bauer C., Mundo M., Becher H.: High resolution emboli detection and differentiation by characteristic postembolic spectral patterns. Stroke. 1998, 29, 668-672.
- [11] Keunen R. W. M., Stam C.J., Tavy D.L.J., Mess W.H., Titulaer B.M., Ackerstaff R.G.A.: Preliminary Report of Detecting Microembolic Signals in Transcranial Doppler Time Series With Nonlinear Forecasting. Stroke, 1998, 29, 1638-1643.
- [12] Kemeny V., Droste D.W., Hermes S., Nabavi D.G., Schulte-Altedomeburg G., Siebler M., Ringelstein E.B.: Automatic embolus detection by a neural network, Stroke, 1999, 30, 807-810.
- [13] Van Zuilen E., Mess W.H., Jansen C., Van Der Tweel I., Van Gijn J., Ackerstaff R.G.A.: Automatic embolus detection compared with human experts. Stroke, 1996, 27, 1840-1843.
- [14] Smith J.L., Evans D.H., Bell P.R.F., Naylor A.R.: A comparison of four methods for distinguishing Doppler signals from gaseous and particulate emboli. Stroke, 1998, 29, 1133-1138.
- [15] Kałużyński K., Leśniak B., Liepsch D., Powałowski T., Pałko T., Trawiński Z.: Measurement setup for studies of arterial input impedance in models of carotid artery. Proc. 12th Conf. European Society of Biomechanics, Dublin 2000, 311.
- [16] Liepsch D., Zimmer R.: A method for the preparation of true-to-scale inflexible and natural elastic models of human arteries. Biomed. Tech., 1978, 23, 227-239.
- [17] Liepsch D., Thurston G., Lee M.: Studies of fluids simulating blood-like rheological properties and applications in models of arterial branches.Biorheology, 1991, 28, 39-52.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ1-0011-0016