WO2020159464A2

WO2020159464A2 - An electronic nose system for determining early diagnosis and attacks of hereditary metabolic diseases

Info

Publication number: WO2020159464A2
Application number: PCT/TR2020/050059
Authority: WO
Inventors: Isil OZER; Unal KIZIL; Ahmet Cumhur KINACI; Bahattin AVCI
Original assignee: Canakkale Onsekiz Mart Universitesi Rektorlugu; Ondokuz Mayis Universitesi Rektorluk
Priority date: 2019-01-29
Filing date: 2020-01-29
Publication date: 2020-08-06
Also published as: WO2020159464A3

Abstract

The invention is related to a low-cost electronic nose system that is used for determining early diagnosis and attacks of hereditary metabolic diseases by measuring the smell of the air that has been drawn out of the aero chamber comprising a mask and a spray tank, and that has been transferred into the sample container.

Description

AN ELECTRONIC NOSE SYSTEM FOR DETERMINING EARLY DIAGNOSIS AND ATTACKS OF HEREDITARY METABOLIC

DISEASES Technical Field

The invention is related to a low-cost electronic nose system that is used for determining early diagnosis and attacks of hereditary metabolic diseases by measuring the smell of the air that has been drawn out of the aero chamber comprising a mask, and that has been transferred into the sample container. Prior Art

The developments carried out in recent years in electronic and artificial intelligence fields in modem technology, enable us to easily measure and characterize various properties of biological materials (Ouellette, 1999). Within this scope, the electronic noses that are taken into consideration can be used in several different fields including food and environmental safety and even human health. Electronic noses are systems that operate by imitating the human olfactory system. In the human olfaction mechanism, which is quite a complex structure, the receptor cells are the initial place where the smell is sensed. Electronic nose systems use sensors instead of these cells. The organ which processes the signals received from the receptor cells and defines the smell is brain. In electronic nose systems, instead of the brain, Artificial Neural Networks (ANN) are used which carry out a classification process using sophisticated pattern recognition (Barisci et al. 1997; Panigrahi et al. 2002).

Several studies have been conducted regarding electronic nose applications. In one of these studies Balasubramanian et al., (2005) have used an electronic nose that is commercially sold in order to determine the freshness of beef that is sold in markets. The system they have used has been successful in classifying fresh or spoiled meat.

Again in a similar study Dodd et al., (2005) have classified different stale stages of tilapia fish ( Oreochromisniloticus ) using an electronic nose that is formed of 16 metal-oxide gas sensors that were sensitive to different gasses.

In another study, Younts et al. (2005) have tried to distinguish different bacteria types by using the ANNs method by means of a system they have created, which is formed of gas sensors. The system they developed has been able to distinguish Escherichiacoli 0157:H7 from Escherichiacoli Non-0157 :H7. The main operating principle of the system is to determine the pattern difference of gasses that were released by two different bacteria types.

Another application of electronic nose systems to human health has been carried out by Machado et al. (2005). They have detected lung cancer using an electronic nose. The system was tested on 59 volunteers (14 patients with lung cancer, 25 patients with other lung diseases and 20 healthy people) and patients having cancer were distinguished from the smell of their breath.

Electronic nose systems have been applied in the food safety area. Gomez et al. (2007) have tried to determine properties such as the ripeness, acidity degree, and soluble solid material content of tangerines based on different harvesting/picking times , by using an electronic nose. According to research results, the quality properties of tangerine have been able to be defined by means of a correlation coefficient that varied between 0.66 to 0.73. Li and Heinemann (2007) have used an electronic nose system to determine the physical damages on apples. They were able to determine the physical damage and with a precision of approximately 85%.

Different studies have also been conducted in order to use the electronic nose in manure management. Kizil and Lindley (2001) have tried to determine plant nutrient contents in the manure of farm animals using tin-dioxide gas sensors. As a result of the study, the total-N, organic-N, NH4, and K contents of the manure were able to be determined with high correlation coefficients such as 0.81, 0.72, 0.92 and 0.72, respectively Under the scope of the results obtained from Kizil and Lindley (2001) and Kizil et al. (2001) and, Kizil (2006) identified N, P, and K contents in manure with high correlation coefficients by means of a system developed by using metal-oxide semiconductive sensors that are sensible to methane, ammonium and hydrogen sulfate gasses. Components such as mini-pumps, circulation fans, data collection cards have been used in order to increase the performance of previously developed systems. Kizil et al., (2011) have defined the design principles of the electronic nose system. Moreover, Saqan and Kizil (2010) have discussed the possibility of using electronic nose systems in biosystems engineering. However, these systems are quite expensive and they are difficult to use (Markom et al. 2007). Therefore low- cost systems need to be developed.

The human brain senses the effect of volatile chemical compounds as“smell” collectively, without being able to classify said compounds separately. As a result, it is expected for the sensors that are used in electronic nose systems to be sensitive to a wide variety of chemicals (Stussi et al. 1996). Different sensor types are used in electronic nose systems. The most frequently used systems can be listed as metal- oxide semiconductors (MOS), modified metal-oxide semiconductors (NMOS), conductive polymers (CP) and conductive oligomers (CO). When these sensors are subjected to smell the electrical conductivities of active agents change due to oxidation or swelling. Therefore this change in conductivity affects the voltage value that is sensed by the sensor. The intensity of the smell and its properties can be understood by measuring the voltage changes with a simple electric circuit (Kizil et al., 2001). Several studies have been conducted in order to use the electronic nose systems for diagnosis based on the changes in the breaths particularly in diseases such as respiratory diseases. It was noted that successful results were obtained especially regarding diseases such as lung cancers, respiratory tract infections, cystic fibrosis and chronic obstructive pulmonary diseases (Phillips et al. 2012; Kuban and Foret. 2013; Dragonieri et al 2017). It has been shown that it was successful in the diagnosis and tracking of pneumoconiosis (Hsiao-YuYang et al. 2018). It has been reported that the system provided 91% precision in distinguishing from healthy individuals and 93% precision in making a successful diagnosis in relation to pulmonary tuberculosis (Teixeira et al. 2017). However, tracking patients with diabetes by the changes of respiration was less successful in comparison to observing blood sugar (Leopold et al. 2017).

The smell of breath is a definitive symptom of several metabolic diseases. These different types of smells can be used as clinical examination findings. The source of the smell is investigated in order to make a diagnosis, using tandem mass spectrophotometry (Tandem MS) in blood and gas chromatography -mass spectrophotometry (GC-MS) in urine samples (Saudubray et al. 2006). Early scanning of hereditary metabolic diseases in newborn babies are present. However as the results of such scanning may take 10-14 days, maple syrup urine disease (MSUD), organic acidemia such as isovaleric acidemia and urea cycle defects have not been included in such diseases since they show early symptoms. As toxic metabolite succinylacetone is a volatile agent, Tyrosinemia disease has also not been included within the scan group as its scan exams may be erroneous and result to be negative. However, it is recommended for scans to be carried out by searching for succinylacetone in a dry blood sample in order to diagnose tyrosinemia (Chinsky and ark 2017). However early-stage neonatal tyrosinemia may still show symptoms earlier than the result of scanning succinylacetone from dry blood samples. In the Chinese patent document numbered CN107647869 of the prior art, a wearable respiration detector that comprises an electronic nose system is disclosed. The respiration detector comprises a respiration collection device, an air inlet filter box, and a single direction ventilation valve. By means of using a detector in the invention developed, the abnormal smell created by the respiration of the user, cell mutation changes and the changes in converting the expansion stress of the oral cavity into an electric value can be analyzed and such changes can be evaluated using a graphene sensor. Therefore it is enabled to detect the abnormal condition of the health of the user's body and respiration conditions. In the United States Patent document numbered US2010198521 of the prior art, an electronic nose device has been developed, that is based on chemically-sensitive field-effect transistors. This device is used to diagnose diseases comprising various cancer types.

In the United States Patent document numbered US2005082175 of the prior art, a method or apparatus that has been developed to detect smell emissions that are sourced from diseases caused by microorganisms or metabolic changes that are caused by diseases is disclosed. The apparatus that has been developed comprises a sensor, a sample feeding system connected to the sensor, a computer or a microcontroller connected to the sensor. In the article titled;“Classification of Artificial Neural Networks of Different Objects Using an Electronic Nose” of the prior art, that has been published in 2015, the volatile chemical components of 9 different objects were classified, using a low- cost electronic nose device formed of 8 different gas sensors.

In the article titled;“Advances in Electronic-Nose Technologies for the Detection of Volatile Biomarker Metabolites in the Human Breath” of the prior art, that has been published in 2015, the prevalent usage of an electronic nose in orderto provide early diagnosis of diseases such as particularly lung cancer and diabetes in the health sector, has been disclosed.

However the electronic nose systems of the prior art very expensive and costly. Therefore it was required to develop an electronic nose system. Aims of the Invention

The aim of this invention is to provide a low-cost electronic nose system.

Another aim of the invention is to provide an electronic nose system that is used for determining early diagnosis and attacks of hereditary metabolic diseases by measuring the smell of the air that has been drawn out of the aero chamber and that has been transferred into the sample container.

Another aim of the invention is to provide a portable electronic nose system that is easy to use.

Detailed Description of the Invention

The electronic nose system developed in order to reach the aims of the invention has been shown in the figures.

According to these figures;

Figure 1 : Is the schematic view of the electronic nose system subject to the invention.

The parts in the figures have each been numbered and their references have been listed below.

1. Mask

2. Tank 3. Aerochamber

4. Main body

5. Sample container

6. Micropump

7. Pump control unit

8. Sensor chamber

9. Power unit

10. Data collection card

11. Computer The invention is an electronic nose system comprising; an aerochamber (3) comprising a mask (1) and a spray tank (2), through which the gas inside is inhaled into the lungs of the user,

a sample container (5) that is connected to the aerochamber (3) and the main body (4), into which the volatile gasses are collected following the exhalation of breath that was inhaled from the aerochamber (3), a micropump (6), located inside the main body (4) which enables to deliver the volatile gasses obtained from the sample container (5) into the main body (4),

a pump control unit (7) that adjusts the flow rate of the gas drawn by means of the micropump and that is connected to the micropump (6) located in the main body (4),

a series of sensors (8) located in the main body (4) formed of metal oxide gas sensors and temperature/humidity sensors, by means of which the measurements of volatile gasses inside the sample container (5) are conducted,

a power unit (9) connected to the series of sensors (8) and the pump control unit (7), used for providing the power that is required for the electronic nose system to operate, a data collection card (10) located in the main body (4), connected to the series of sensors (8) that are used to obtain and release response data from series of sensors (8),

a computer (11) connected to a data collection card that enables the information in the data collection card (10) to be transferred to the server and to be stored in said server.

In the electronic nose system that has been developed the breath provided with the aerochamber (3), is collected inside the sterile and disposable sample container (5), the collected breath is received from the sample container (5) via a diaphragm micropump (6) and is transferred into the main body (4) and the series of sensors (8) located in the main body (4) obtains breath data.

Signal collection processes are applied onto the raw breath data that has been obtained and following the signal correction process, normalization is carried out. Following the calculation of the areas that remain below the data curves that were normalized, the data within the calculated area is classified as being infected and not infected. The classified data is separated and the early diagnosis of hereditary metabolic diseases is performed.

In order to be able to obtain data by sniffing the breath in electronic nose systems, the exhaled breath needs to be collected within a certain period of time and it needs to be driven from the sampling medium to the system by means of the electronic nose system. Accordingly, an aerochamber (3) has been used in the system that has been developed. The aerochamber (3) is a tool that is especially used for inhaling a spray by children with asthma. The aerochamber (3) comprises a mask (1) and a special tank (2) which includes spray therein. The spray that is placed into the tank (2) delivers the spray and other similar medicines to the lungs of the child when the child inhales. By means of the air that is discharged from a separate route when the user exhales, the inhaled and exhaled breath does not mix. In the system that has been developed, only the exhaled breath of the patient shall be collected inside the disposable sample containers (5) by means of the aerochamber (3). (Figure 1) The volatile gasses inside the sample container (5) shall be drawn out of the sample container (5) by means of a diaphragm micropump (6) and shall be delivered to the main body (4). The micropump (6) is operated with a power source of 12 V (D/C) and it provides a maximum 350 mL/min flow capacity. The micropump (6) includes a pump control unit (7) in order to adjust the flow rate.

REFERENCES

[1] Balasubramanian, S., Panigrahi, S., Louge, C.M., Marchello, M., Doetkott, C., Gu, H., Sherwood, J., Nolan, L. 2005.“Spoilage Identification of Beef Using an Electronic Nose System”, Transactions of the ASAE, 47(5), 1625-1633. [2] Barisci, J., Andrew, M., Harris, P., Patridge, A., Wallace, G. 1997.

“Development of an Electronic Nose”, Proc. of Smart Electric Nose Spie, 3242, 164-171.

[3] Chinsky, J. M., Singh, R., Ficicioglu, C., van Karnebeek, C.D.M., Grompe, M., Mitchell, G. , Waisbren, S. E., Gucsavas-Calikoglu, M., Wasserstein, M. P., Coakley, K., Scott, C.R. 2017.“Diagnosis and treatment of tyrosinemia type E a US and Canadian consensus group review and recommendations”, Genet Med. 19(12).doi: 10.1038/gim.2017.101. Epub 2017 Aug 3.

[4] Dodd, T.H., Hale, S.A., Blanchard, S.M. 2005.“Electronic Nose Analysis of Tilapia Storage”, Transactions of the ASAE, 47(1), 135-140. [5] Dragonieri, S., Pennazza, G., Carratu, P., Resta, 0.2017. “Electronic

NoseTechnology in RespiratoryDiseases”, Lung, 195,157-165.

[6] Gomez, A.H., Wang, J., Pereira, A.G. 2007.“Mandarin Ripeness Monitoring and Quality Attribute Evaluation Using an Electronic Nose Technique”, American Society of Agricultural and Biological Engineers, 50(6), 2137-2142. [7] Hammerstrom, D. 1993.“Working with Neural Networks”, IEEE Spectrum,

July 1993, 46-53.

[8] Haykin, S. 1994.“Neural Networks: A Comprehensive Foundation”, Macmillan College Publishing Company, New York.

[9] Kizil, LI., Lindley, J.A. 2001.“Comparison of Different Techniques in the Determination of Animal Manure Characteristics”, ASAE/CSAE North Central

Sections Conference. Brookings, South Dakota September 28-29, 2001. Paper No: SD 01-106. [10] Kizil, ϋ , Lindley, J.A., Panigrahi, S. 2001. “Determination of Manure Characteristics Using Gas Sensors”, ASAE Annual International Meeting. Sacramento, California July 29-August 1, 2001, Paper No: 01-1024.

[11] Kizil, ϋ , Gen<j, L., Sa9an, M. 2011.“Elektronik Burun Sistemlerinin Tasarim ilkeleri”, U. TJ. Ziraat Fakiiltesi Dergisi, 25(1), 109-118.

[12] Kizil, LI., Gen , L., Gen9, T., Rahman, S.,L Khaitsa, M. 2015.“E-Nose Identification Of Salmonella Enterica In Poultry Manure”, British Poultry Science, 56(2), 149-156.

[13] Kizil, U, Gen9, L, Rahman, S., L Khaitsa, M., Gen9, T. 2015.“Design And Test Of A Low-Cost Electronic Nose System For Identification Of Salmonella

Enterica In Poultry Manure”, Transactions Of The ASABE, 58(3), 819-826.

[14] Kubann, P., Foret, F. 2013.“Exhaled breath condensate: Determination of non volatile compounds and their potential for clinical diagnosis and monitoring. A review”, Analytica Chimica Acta 805,1- 18. [15] Leopold, J. FL, Bos, L.D.J., Colombo, C., Sterk, P. J., Schultz, M. J., Abu-

Hanna, A. 2017.“Non-invasive breath monitoring with eNose does not improve glucose diagnostics in critically ill patients in comparison to continuous glucose monitoring in blood”, J. Breath Res. 11(2), 026002.

[16] Li, C., Heinemann, P.H. 2007.“ANN Integrated Electronic Nose And Znose System for Apple Quality Evaluation”, Transactions of the ASABE, 50(6), 2285-

2294.

[17] Machado, R.F., Laskowski, D., Deffenderfer, O., Burch, T., Zheng, S., Mazzone, P.J., Mekhail, T., Jennings, C., Stoller, J.K., Pyle, J., Duncan, J., Dweik, R.A., Erzurum, S.C. 2005.“Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath”, Am. J. Respiratory Critical Care Med., 171,1286-1291. [18] Markom, M.A., Shakaff, A.Y., Adorn, A.H., Fikri, N.A., Khan, S.F., Abdullah, A.H., Isa, C.M.NC. 2007.“Development of Low Cost Electronic Nose”, University Malaysia Perils., http://hdl.handle.net/123456789/7454.

[19] Ouellette, J. 1999.“Electronic Noses Sniff out New Markets”, Industrial Physicist, 5(1), 26-29.

[20] Panigrahi, S., Kizil, U., Balasubramanyan, S., Doetkott, C., Logue, C., Marchello, M., Gu, FL, Kubiak, A., Nolan, L., Schneider, J., Wiens, R. 2002.” Electronic Nose System for Meat Quality Evaluation”, ASAE/CIGR Annual International Meeting. Chicago, Illinois, Paper No., 026094. [21] Phillips, C. O., Syed, Y., Parthalain, N. M., Zwiggelaar, R., Claypole, T.C.,

Lewis, K. E. 2012. “Machine learning methods on exhaled volatile organic compounds for distinguishing COPD patients from healthy controls”, J. Breath Res. 6 ,036003 (lOpp).

[22] Sagiroglu, §., Be§dok, E., Erler, M. 2003. “Miihendislikte Yapay Zeka Uygulamalari-I” , Yapay Sinir Aglan, Ufuk Yaymevi, Kayseri.

[23] Saudubray, J.M., Desguerre, F, Sedel, F., Charpentier, C. 2006.“A Clinical Approach to Inherited Metabolic Diseases” Fourth, Revised Edition. Springer Medizin Verlag Heidelberg.

[24] Stussi, E., Celia, S., Serra, G., Verier, G. 1996.“Fabrication of Conducting Polymer Patterns for Gas Sensing By A Dry Technique”, Materials Science And

Engineering C4, 1996,27-33.

[25] Teixeira, R. C., Rodriguez, M., de Romero, N. J., Bruins, M., Gomez, R., Yntema, J. B., Abente, G. C., Gerritsen, J. W., Wiegerinck, W., Bejerano, D. P., Magis-Escurra, C.2017.”The potential of a portable, point-of-care electronic nose to diagnose tuberculosis”, J Infection, 75, 441-447. [26] White, H., Gallant, A. R., Hornik,K., Stinchcombe, M., Wooldridge, J. 1992. “Artificial Neural Networks: Approximation and Learning Theory”, Cambridge, Mass.: Blackwell Publishers.

[26] Yang, H.Y., Peng, HY, Chang, C.J., Chen, P.C. 2018.“Diagnostic accuracy of breath tests for pneumoconiosis using an electronic nose”, J. BreathRes. 12.

[27] Younts, S., Alocilja, E.C., Osburn, W.N., Marquie, S., Grooms, D.L. 2005. “Differentiation of Esch richiacoliO\ 57:H7 from non-0157:H7 E. Coli Serotypes Using a Gas Sensor based, Computer-controlled Detection System”, Transactions of the ASAE, 45(5), 1681-1685.

Claims

1. The invention is an electronic nose system comprising,

a micropump (6), located inside the main body (4) which enables to deliver the volatile gasses obtained from the sample container (5) from the sample container (5) into the main body (4),

a series of sensors (8) located in the main body (4) formed of metal oxide gas sensors and temperature/humidity sensors, by means of which the measurements of gasses inside the sample container (5) are conducted, a power unit (9) connected to the series of sensors (8) and the pump control unit (7), used for providing the power that is required for the electronic nose system to operate,

a data collection card (10) located in the main body (4), connected to the series of sensors (8) that are used to obtain and release response data from said series of sensors (8), characterized by comprising; an aerochamber (3) comprising a mask (1) and a spray tank (2), through which the gas inside is inhaled into the lungs of the user,

a sample container (5) that is connected to the aerochamber (3) and the main body (4), into which the volatile gasses are collected following the exhalation of breath that was inhaled from the aerochamber (3).

2. An electronic nose system according to claim 1; characterized by comprising a pump control unit (7) that adjusts the flow rate of the gas drawn by means of the micropump, and that is connected to the micropump (6) located in the main body (4).

3. An electronic nose system according to claim 1 or 2; characterized by comprising a computer (11) that is connected to a data collection card that enables the information in the data collection card (10) to be transferred to the server and to be stored in said server.