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WORLDCOMP’16 CSUB 1/12
Department of Electrical and Computer Engineering & Computer Science
California State University Bakersfield
Wireless Spectrum-Capnography System for Detecting
Cholesterol Levels in the Blood
Jenny Villatoro and Vida Vakilian
July 27, 2016
Abstract
Abstract
WORLDCOMP’16 CSUB 2/12
 The human breath analysis can be used to determinate the values of volatile
organic compounds (VOCs), such as cholesterol (C27H26O) and isoprene
(C5H8), that are associated with some diseases, for example, lung cancer,
atherosclerosis, and diabetes.
 Despite the utility of this biochemical fluid analysis provides, it is a not very
preference method used for clinical diagnosis. Partly the reason is the cost
because the tools used for the analysis are expensive.
 This research concentrates on the spectrum-capnography system that will
detect isoprene and CO2 concentrations in order to measure the cholesterol
levels in the blood.
 To meet this challenge, we propose to design a low-cost wireless spectrum-
capnography prototype with an electrocardiographic (ECG) signal, thus
provides heart and respiratory rates, isoprene, and CO2 as a biomarker of
interest that are useful information to people with cardiovascular diseases.
Motivations
Motivations
WORLDCOMP’16 CSUB 3/12
Cardiovascular disease is burdensome on healthcare system due to its
associated cost of care and the fact that it is a silent killer. Regular
screening for cholesterol may help determine onset and presence of
the cardiovascular disease.
 Proposing a spectrum-capnography system that is able to detect the
concentration of CO2 and isoprene and therefore measure the cholesterol
(C27H26O) levels present in the blood.
 Developing a low-cost spectrum-capnography prototype using wireless
sensor networking.
Introduction
Introduction
WORLDCOMP’16 CSUB 4/12
Isoprene is a heat sensitive organic
compound. It can be found naturally
in the human body and in the
environment at relatively low
concentrations. The primary source of
isoprene in the human body has been
ascribed to the mevalonate pathway
of cholesterol biosynthesis.
Biosynthesis of the Cholesterol is
made from acetyl-CoA. Steroids are
biosynthetically from pyrophosphate
(active isoprene) that is the first
several compounds in the pathway in
the cholesterol production.
Fig. 1. Biochemical pathway of isoprene
Fig. 2. Biosynthesis of cholesterol
Introduction
Introduction
WORLDCOMP’16 CSUB 5/12
The Electrocardiogram (ECG) is a
diagnostic tool that records the
electrical activity of the heart. The
heart contracts as the electrical
impulse travels through the body.
The cardiac impulse came from
sinoatrial (SA) node and spread
through the His- Purkinje bundle into
the ventricles. The maximum positive
potential reaches 1 mV
The Electrocardiogram (ECG) is a diagnostic tool that records the electrical activity of the
heart. The heart contracts as the electrical impulse travels through the body. The cardiac
impulse came from sinoatrial (SA) node and spread through the His- Purkinje bundle into the
ventricles. The maximum positive potential reaches 1 mV.
The goal of this research is to propose a low-cost non-invasive monitoring device that can
read the cholesterol levels in the blood using the concentration of carbon dioxide with
ZigBee wireless technology and incorporates LabVIEW in order to display the biomedical
signals in mobile devices.
Fig. 3. Einthroven Triangle Fig. 4. ECG Signal
Hypothesis
Hypothesis
WORLDCOMP’16 CSUB 6/12
A low-cost breath analysis could be made it by using a spectrum-capnometer with ZigBee
technology. Spectrophotometer can detect the isoprene concentration and the
capnometer can detect CO2 concentration. This values could help us to find the
concentration of cholesterol in the blood. Also, the electrocardiographic (ECG) signal can
add more relevant information that would help the physician to detect cardiovascular
disease.
Signal
Acquisition
Stage.
Analog circuit
block: electrodes,
amplifiers, low and
high pass filters,
and conditioner DC
voltage adder
amplifier.
Z
I
G
B
E
E
C
A
R
D
M
I
C
R
O
C
O
N
T
R
O
L
E
R
Fig. 5. Block Diagram of the Wireless Monitor using ZigBee Technology
Physical Background and Methods
Physical Background and Methods
WORLDCOMP’16 CSUB 7/12
Spectrophotometry is the physical model and method used to measure the concentration and
absorption of CO2 and isoprene gases.
Electromagnetic Spectrum
Fig 6: Acquisition Method; (1) breath
source, (2) vacuum pump, (3) needle
valve, (4) pressure control point , (5) drift
tube, (6) CO2 sensor.
Fig.6. Acquisition Method
Signal Model
Signal Model
WORLDCOMP’16 CSUB 8/12
To measure the concentration of CO2, we first use the Beer’s law equation:
Results
Simulation Results
WORLDCOMP’16 CSUB 9/12
We record the breath rate continuously during 30 seconds. The maximum and
minimum levels of the recorded pCO2 are 66 and 6 mmHg, respectively.
Fig.7: Analysis of breath pCO2 concentration of a female adult during exercise. We then use
the obtained results to compare with the isoprene values that are strong related to the
pulmonary CO2 exchanges.
Results
Simulation Results
WORLDCOMP’16 CSUB 10/12
Using the infrared and visible lights to determine the pCO2 concentration in the
venous and arteries, respectively. The physiological range of venous CO2
concentration is between 30-50 mmHg, and arterial CO2 concentration is between
80-105 mmHg. .
These values are compared with the venous blood isoprene concentration to help
us to determine the cholesterol levels in blood.
Conclusions
Conclusions
WORLDCOMP’16 CSUB 11/12
 We proposed a new breath sampling method to determine the
cholesterol levels in the blood. The main idea is to sense the
exhaled breath gas using infrared (IR) light, CO2 sensor, and a
spectrophotometer to measure the isoprene concentration.
 The obtained data from these sensors contain information
about the pCO2 and isoprene (cholesterol biosynthesis)
concentrations that help to measure the cholesterol levels in
blood.
 We process the measured data via a microcontroller and ZigBee
card and display these values in a mobile device.
References
References
WORLDCOMP’16 CSUB 12/12
[1] S. Chatterjee and A. Miller, Biomedical Instrumentation Systems. Cengage Learning, 2010.
[2] [G. J. Tortora and B. H. Derrickson, Principles of anatomy and physiology. John Wiley & Sons,
2008.
[3] A. Prabhakar, “Portable sensors for breath analysis,” Ph.D. dissertation, Arizona State University,
2013.
[4] T. T. Kean, A. Teo, and M. Malarvili, “Feature extraction of capnogram for asthmatic patient,” in
Computer Engineering and Applications (ICCEA), 2010 Second International Conference on, vol.
2. IEEE, 2010, pp. 251–255.
[5] J. D. Fenske and S. E. Paulson, “Human breath emissions of vocs,” Journal of the Air & Waste
Management Association, vol. 49, no. 5, pp. 594–598, 1999.
[6] B. Buszewski, M. K˛esy, T. Ligor, and A. Amann, “Human exhaled air analytics: biomarkers of
diseases,” Biomedical Chromatography, vol. 21, no. 6, pp. 553–566, 2007.
[7] P. Kalsi, Spectroscopy of organic compounds. New Age International, 2007.
[8] Blei and G. Odian, General, Organic, and Biochemistry Media Update. Macmillan, 2008.
[9] R. A. Klocke, “Carbon dioxide transport,” Comprehensive Physiology, 1987.
[10] P. Frehill, D. Chambers, and C. Rotariu, “Using zigbee to integrate medical devices,” in
Engineering in Medicine and Biology Society,2007. EMBS 2007. 29th Annual International
Conference of the IEEE. IEEE, 2007, pp. 6717–6720.
[11] T. Karl, P. Prazeller, D. Mayr, A. Jordan, J. Rieder, R. Fall, and W. Lindinger, “Human breath
isoprene and its relation to blood cholesterol levels: new measurements and modeling,”
Journal ofApplied Physiology, vol. 91, no. 2, pp. 762–770, 2001.

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PsterPresentation2016

  • 1. WORLDCOMP’16 CSUB 1/12 Department of Electrical and Computer Engineering & Computer Science California State University Bakersfield Wireless Spectrum-Capnography System for Detecting Cholesterol Levels in the Blood Jenny Villatoro and Vida Vakilian July 27, 2016
  • 2. Abstract Abstract WORLDCOMP’16 CSUB 2/12  The human breath analysis can be used to determinate the values of volatile organic compounds (VOCs), such as cholesterol (C27H26O) and isoprene (C5H8), that are associated with some diseases, for example, lung cancer, atherosclerosis, and diabetes.  Despite the utility of this biochemical fluid analysis provides, it is a not very preference method used for clinical diagnosis. Partly the reason is the cost because the tools used for the analysis are expensive.  This research concentrates on the spectrum-capnography system that will detect isoprene and CO2 concentrations in order to measure the cholesterol levels in the blood.  To meet this challenge, we propose to design a low-cost wireless spectrum- capnography prototype with an electrocardiographic (ECG) signal, thus provides heart and respiratory rates, isoprene, and CO2 as a biomarker of interest that are useful information to people with cardiovascular diseases.
  • 3. Motivations Motivations WORLDCOMP’16 CSUB 3/12 Cardiovascular disease is burdensome on healthcare system due to its associated cost of care and the fact that it is a silent killer. Regular screening for cholesterol may help determine onset and presence of the cardiovascular disease.  Proposing a spectrum-capnography system that is able to detect the concentration of CO2 and isoprene and therefore measure the cholesterol (C27H26O) levels present in the blood.  Developing a low-cost spectrum-capnography prototype using wireless sensor networking.
  • 4. Introduction Introduction WORLDCOMP’16 CSUB 4/12 Isoprene is a heat sensitive organic compound. It can be found naturally in the human body and in the environment at relatively low concentrations. The primary source of isoprene in the human body has been ascribed to the mevalonate pathway of cholesterol biosynthesis. Biosynthesis of the Cholesterol is made from acetyl-CoA. Steroids are biosynthetically from pyrophosphate (active isoprene) that is the first several compounds in the pathway in the cholesterol production. Fig. 1. Biochemical pathway of isoprene Fig. 2. Biosynthesis of cholesterol
  • 5. Introduction Introduction WORLDCOMP’16 CSUB 5/12 The Electrocardiogram (ECG) is a diagnostic tool that records the electrical activity of the heart. The heart contracts as the electrical impulse travels through the body. The cardiac impulse came from sinoatrial (SA) node and spread through the His- Purkinje bundle into the ventricles. The maximum positive potential reaches 1 mV The Electrocardiogram (ECG) is a diagnostic tool that records the electrical activity of the heart. The heart contracts as the electrical impulse travels through the body. The cardiac impulse came from sinoatrial (SA) node and spread through the His- Purkinje bundle into the ventricles. The maximum positive potential reaches 1 mV. The goal of this research is to propose a low-cost non-invasive monitoring device that can read the cholesterol levels in the blood using the concentration of carbon dioxide with ZigBee wireless technology and incorporates LabVIEW in order to display the biomedical signals in mobile devices. Fig. 3. Einthroven Triangle Fig. 4. ECG Signal
  • 6. Hypothesis Hypothesis WORLDCOMP’16 CSUB 6/12 A low-cost breath analysis could be made it by using a spectrum-capnometer with ZigBee technology. Spectrophotometer can detect the isoprene concentration and the capnometer can detect CO2 concentration. This values could help us to find the concentration of cholesterol in the blood. Also, the electrocardiographic (ECG) signal can add more relevant information that would help the physician to detect cardiovascular disease. Signal Acquisition Stage. Analog circuit block: electrodes, amplifiers, low and high pass filters, and conditioner DC voltage adder amplifier. Z I G B E E C A R D M I C R O C O N T R O L E R Fig. 5. Block Diagram of the Wireless Monitor using ZigBee Technology
  • 7. Physical Background and Methods Physical Background and Methods WORLDCOMP’16 CSUB 7/12 Spectrophotometry is the physical model and method used to measure the concentration and absorption of CO2 and isoprene gases. Electromagnetic Spectrum Fig 6: Acquisition Method; (1) breath source, (2) vacuum pump, (3) needle valve, (4) pressure control point , (5) drift tube, (6) CO2 sensor. Fig.6. Acquisition Method
  • 8. Signal Model Signal Model WORLDCOMP’16 CSUB 8/12 To measure the concentration of CO2, we first use the Beer’s law equation:
  • 9. Results Simulation Results WORLDCOMP’16 CSUB 9/12 We record the breath rate continuously during 30 seconds. The maximum and minimum levels of the recorded pCO2 are 66 and 6 mmHg, respectively. Fig.7: Analysis of breath pCO2 concentration of a female adult during exercise. We then use the obtained results to compare with the isoprene values that are strong related to the pulmonary CO2 exchanges.
  • 10. Results Simulation Results WORLDCOMP’16 CSUB 10/12 Using the infrared and visible lights to determine the pCO2 concentration in the venous and arteries, respectively. The physiological range of venous CO2 concentration is between 30-50 mmHg, and arterial CO2 concentration is between 80-105 mmHg. . These values are compared with the venous blood isoprene concentration to help us to determine the cholesterol levels in blood.
  • 11. Conclusions Conclusions WORLDCOMP’16 CSUB 11/12  We proposed a new breath sampling method to determine the cholesterol levels in the blood. The main idea is to sense the exhaled breath gas using infrared (IR) light, CO2 sensor, and a spectrophotometer to measure the isoprene concentration.  The obtained data from these sensors contain information about the pCO2 and isoprene (cholesterol biosynthesis) concentrations that help to measure the cholesterol levels in blood.  We process the measured data via a microcontroller and ZigBee card and display these values in a mobile device.
  • 12. References References WORLDCOMP’16 CSUB 12/12 [1] S. Chatterjee and A. Miller, Biomedical Instrumentation Systems. Cengage Learning, 2010. [2] [G. J. Tortora and B. H. Derrickson, Principles of anatomy and physiology. John Wiley & Sons, 2008. [3] A. Prabhakar, “Portable sensors for breath analysis,” Ph.D. dissertation, Arizona State University, 2013. [4] T. T. Kean, A. Teo, and M. Malarvili, “Feature extraction of capnogram for asthmatic patient,” in Computer Engineering and Applications (ICCEA), 2010 Second International Conference on, vol. 2. IEEE, 2010, pp. 251–255. [5] J. D. Fenske and S. E. Paulson, “Human breath emissions of vocs,” Journal of the Air & Waste Management Association, vol. 49, no. 5, pp. 594–598, 1999. [6] B. Buszewski, M. K˛esy, T. Ligor, and A. Amann, “Human exhaled air analytics: biomarkers of diseases,” Biomedical Chromatography, vol. 21, no. 6, pp. 553–566, 2007. [7] P. Kalsi, Spectroscopy of organic compounds. New Age International, 2007. [8] Blei and G. Odian, General, Organic, and Biochemistry Media Update. Macmillan, 2008. [9] R. A. Klocke, “Carbon dioxide transport,” Comprehensive Physiology, 1987. [10] P. Frehill, D. Chambers, and C. Rotariu, “Using zigbee to integrate medical devices,” in Engineering in Medicine and Biology Society,2007. EMBS 2007. 29th Annual International Conference of the IEEE. IEEE, 2007, pp. 6717–6720. [11] T. Karl, P. Prazeller, D. Mayr, A. Jordan, J. Rieder, R. Fall, and W. Lindinger, “Human breath isoprene and its relation to blood cholesterol levels: new measurements and modeling,” Journal ofApplied Physiology, vol. 91, no. 2, pp. 762–770, 2001.