Arterial Stiffness Detection Depending on Neural Network Classification of the Multi- Input Parameters
Diagnostic and detection of the arterial stiffness is
very important; which gives indication of the associated increased risk of cardiovascular diseases. To make a cheap and easy method for general screening technique to avoid the future cardiovascular
complexes , due to the rising of the arterial stiffness ; a proposed algorithm depending on photoplethysmogram to be used. The
photoplethysmograph signals would be processed in MATLAB. The
signal will be filtered, baseline wandering removed, peaks and
valleys detected and normalization of the signals should be achieved
.The area under the catacrotic phase of the photoplethysmogram
pulse curve is calculated using trapezoidal algorithm ; then will used
in cooperation with other parameters such as age, height, blood
pressure in neural network for arterial stiffness detection. The Neural
network were implemented with sensitivity of 80%, accuracy 85%
and specificity of 90% were got from the patients data. It is
concluded that neural network can detect the arterial STIFFNESS
depending on risk factor parameters.
[1] World Health Organisation (WHO). The World Health Report 2004. 2004:120.
[2] H. Hasegawa, M. Ozawa, H. Kanai, N. Hoshimiya, N. Chubachi, Y. Koiwa, "Evaluation of elastic property of the arterial wall by measuring small velocity signals using ultrasound", Ultrasonics Symposium, 1997.
Proceedings, 1997 IEEE, Volume: 2, 5-8 Oct. 1997, Pages: 1169 - 1172 vol. 2.
[3] Avolio A, Jones D, Tafazzolo-Shadpour M " quantification of alteration
instructure and function of elastin in the arterial media" Hypertension 1998; 32(1):170-5
[4] John Allen, "Photoplethysmography and its application in clinical
Physiological measurement" Physiol. Meas. 28 (2007) R1-R39
[5] Y. Iketani et al" Second derivative of photoplethysmogram in children
and young people" Jpn Circ J. 2000; 64:110-116
[6] Hertzman A B and Spealman C R "Observations on the finger volume
pulse recorded photoelectrically" Am. J. Physiol. 1937, 119, 334-5
[7] M.Nitzan,I. Faib,H. Friedman" respiration-induced changes in tissue
blood volume distal to occluded artery,measured by
photoplethysmography" J. Biomed. Opt. 11(2006)040506
[8] Bernard Willers,Sep Verba" Neural Networks", ThinkQuest2000,project
on Neural Networks,Team C007395,2000
[9] Atkinson, Kendall E.," An Introduction to Numerical Analysis". (2nd
ed.), New York: John Wiley & Sons, ISBN 978-0-471-50023-0, 1989.
[10] Firas Salih, Qasem Qananwah,Omar Abdallah,and Armin Bolz"
normalized area under catacrotic phase of the photoplethysmogram
pulse for estimating vascular aging",9th international biomedical engineering , BioMed2012, Innsbruck-Austria, 2012
[1] World Health Organisation (WHO). The World Health Report 2004. 2004:120.
[2] H. Hasegawa, M. Ozawa, H. Kanai, N. Hoshimiya, N. Chubachi, Y. Koiwa, "Evaluation of elastic property of the arterial wall by measuring small velocity signals using ultrasound", Ultrasonics Symposium, 1997.
Proceedings, 1997 IEEE, Volume: 2, 5-8 Oct. 1997, Pages: 1169 - 1172 vol. 2.
[3] Avolio A, Jones D, Tafazzolo-Shadpour M " quantification of alteration
instructure and function of elastin in the arterial media" Hypertension 1998; 32(1):170-5
[4] John Allen, "Photoplethysmography and its application in clinical
Physiological measurement" Physiol. Meas. 28 (2007) R1-R39
[5] Y. Iketani et al" Second derivative of photoplethysmogram in children
and young people" Jpn Circ J. 2000; 64:110-116
[6] Hertzman A B and Spealman C R "Observations on the finger volume
pulse recorded photoelectrically" Am. J. Physiol. 1937, 119, 334-5
[7] M.Nitzan,I. Faib,H. Friedman" respiration-induced changes in tissue
blood volume distal to occluded artery,measured by
photoplethysmography" J. Biomed. Opt. 11(2006)040506
[8] Bernard Willers,Sep Verba" Neural Networks", ThinkQuest2000,project
on Neural Networks,Team C007395,2000
[9] Atkinson, Kendall E.," An Introduction to Numerical Analysis". (2nd
ed.), New York: John Wiley & Sons, ISBN 978-0-471-50023-0, 1989.
[10] Firas Salih, Qasem Qananwah,Omar Abdallah,and Armin Bolz"
normalized area under catacrotic phase of the photoplethysmogram
pulse for estimating vascular aging",9th international biomedical engineering , BioMed2012, Innsbruck-Austria, 2012
@article{"International Journal of Electrical, Electronic and Communication Sciences:62085", author = "Firas Salih and Luban Hameed and Afaf Kamil and Armin Bolz", title = "Arterial Stiffness Detection Depending on Neural Network Classification of the Multi- Input Parameters", abstract = "Diagnostic and detection of the arterial stiffness is
very important; which gives indication of the associated increased risk of cardiovascular diseases. To make a cheap and easy method for general screening technique to avoid the future cardiovascular
complexes , due to the rising of the arterial stiffness ; a proposed algorithm depending on photoplethysmogram to be used. The
photoplethysmograph signals would be processed in MATLAB. The
signal will be filtered, baseline wandering removed, peaks and
valleys detected and normalization of the signals should be achieved
.The area under the catacrotic phase of the photoplethysmogram
pulse curve is calculated using trapezoidal algorithm ; then will used
in cooperation with other parameters such as age, height, blood
pressure in neural network for arterial stiffness detection. The Neural
network were implemented with sensitivity of 80%, accuracy 85%
and specificity of 90% were got from the patients data. It is
concluded that neural network can detect the arterial STIFFNESS
depending on risk factor parameters.", keywords = "Arterial stiffness, area under the catacrotic phase of the photoplethysmograph pulse, neural network", volume = "6", number = "10", pages = "1216-4", }