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IOT Based Asthma Detection With CO2 Concentration Using Arduino

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Introduction

Asthma is one of the most widely recognized heterogeneous respiratory infections and has become the fundamental explanation to visit the crisis office and admission to the medical clinic setting each year. It has been viewed as fourteenth most basic illness on the planet as far as span and degree of inability. The worldwide asthma report uncovered that 334 million individuals were influenced by the asthma all through the world, of 14% youngsters and 8.6% youthful grown-ups (matured 18-45). Moreover, around 0.25 million individuals kick the bucket every year rashly because of ill-advised administration and absence of individual asthma checking instrument. Youthful grown-ups (age 18-25) experiencing asthma ought to have an individual asthma checking gadget to survey their sickness and decline their danger of fuel and medical clinic confirmation. Consequently the early determination of asthma what’s more, accomplishing worthy asthma oversight at the ideal time stays shifty in spite of the current strategies. There are two methods to diagnose asthma; firstly, through clinical investigation carried out by the specialized physician secondly, by applying diagnostic equipment such as Spirometer and peak flow meter. However, the first method could be inaccurate sometimes due to manual and involvement of human. Whereas, the second method such as Spirometer have its own drawback like adult patients experience dizziness due to fully physical involvement, chest pain, coughing, bronchospasm and oxygen desaturation due to lack of oxygen. Indeed, it is difficult to get an accurate result if the patient is not able to understand the set of instructions, having chest pain forbidding a forceful effort, or not able to cooperate. It indicates that a successful test required full cooperation and wall chest pain-free.

In addition, the error rate of the spirometer may increase up to 24% of the otherwise normal subject due to the limitation of existing reference equation. Similarly, the peak flow meter is highly patient dependent and relatively insensitive which shows that unless giving a hard and fast expiratory effort, the true peak will be undervalued. However, peak flow meter is easier than Spirometer. It requires only a short blow, not continued expiration until the lungs are completely emptied. Naturally, the patient has to repeat it thrice and highest result of three attempts is the actual peak flow values. Hence both the methods required a full, deep breath in, and blast it out as hard as fast as a patient can until no more air exists in the lungs. Therefore, the aim of our research is to develop a patient-independent and home monitoring early screening asthmatic device that can be used by both asthmatic adult and children. A Recent study shows that the capnograph can be considered as a new method to monitor the asthmatic condition as it uses an infrared technology to measure the concentration of carbon dioxide during exhalation and helps to understand the respiratory status of the patients including asthma. However, most of the studies were offline. Furthermore, the existing capnograph is bulky, costly and cannot estimate components of physiological dead space as well as not able to distinguish the end of expiration from the beginning of inspiration. Thus, we have developed a light weight, effort independent and portable asthma monitoring device that can measure the expired CO2 concentrations and differentiate early stage of asthma

Literature survey: Designing a Respiratory CO2 Measurement Device for Home Monitoring of Asthma Severity. In this research, a new portable and low-cost respiratory CO2 monitoring device based on MG-811 CO2 sensor and microcontrollers was proposed. The output information of this device can be shown either in a small LCD provided or in PC through USB port. The device design will be executed, and a prototype will be developed and tested for validation. So, this new portable capnograph can be used by asthmatic patients as a homemonitoring device instead of peak flow meter without any complicated instructions

Development of an Electronic Kit for detecting asthma in Human Respiratory System. In this research a low cost and portable asthma monitoring devices is proposed. For this device, the main component is carbon dioxide sensor, TFT LCD display and also Bluetooth module. The result from the user can be displayed using TFT LCD display and also PC; meanwhile the result display in a type of graph which can categorize the user either asthmatic or normal. In this research, three asthmatic and normal users are gather to test this device and the result for each of them are gather for analysis. The pattern of the graph for asthmatic user show a significant different compared with normal user.

Problem Statement

Asthma, a constant well being condition pre-dominant in kids can be portrayed by shortness of breath, chest snugness and hacking. An asthma assault can be activated by an assortment of components including ecological conditions, serious physical movement, mugginess and dust. Because of the high commonness of asthma in youngsters and the trouble associated with diagnosing the condition it gets basic to think of mechanical answers for ceaseless consideration and the board of patients with this incessant infection.

Methodology

The MG-811 sensor must be aligned before taking any further estimations. Without the procedure, it will just give futile outcomes. Two sources at known CO2 focus levels are required to accomplish a precise alignment result. In the information sheet it is recommended to adjust the MG811 sensor for 400 ppm and 1000 ppm. Not with standing, while the outside surrounding condition can be treated as around a 400 ppm source, it is difficult for most clients to gain admittance to a solid 1000 ppm source. The sensor can even now be touchy at high fixation levels. Consequently he proposed to utilize the breathed out air as an elective source which gives a subsequent adjustment point at 40,000 ppm. The two portrayals of the alignment program and activity program. To begin the adjustment, first burden the adjustment sketch into the Arduino UNO processor through the Arduino IDE programming. The capacity of this sketch is essentially 5000mV (5V) voltmeter. It is critical to utilize this voltmeter rather that connecting an outer meter.

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This is since any blunder between the Arduino esteem and the remotely estimated worth will truly disable the adjustment. The Arduino can give a conceivable however off base outcome on the off chance that it doesn’t get adequate force from the force flexibly. To check for right activity associate capacity to the Arduino and the CO2 sensor module. Likewise ensure that the showcase is fueled by means of the Arduino rationale pins. While the gadget is working under full burden, cautiously separate the yellow CO2 sensor yield wire from A0 of the Arduino and associate a hop wire from 3.3V to A0. Watch that the showcase peruses 3.3 Volts to inside 1% mistake, for example 2700-3300 mV. Any 17 deviation for the most part proposes that the force gracefully to the Arduino is deficient. This may be found if the Arduino is just force by a PC. Once the system has reached ‘steady state’ it is now time to determine the output voltage of the sensor at 400 ppm. The way by letting the device operate in a totally unoccupied and well ventilated space. Then observe the voltage without breathing on the sensor. Vacate the space for another hour and check again. If the voltage is substantially unchanged, take a note of the reading. This gives the value ‘v400ppm’ in the Arduino operational sketch. After the output voltage at 400 ppm and 40000 ppm are determined from the calibration, replace v400 and v40000 in sketch 2 with the new values, and then upload the uploaded sketch into Arduino via IDE software. The operation program allows the device to perform the following tasks:

  • Monitors the CO2 concentration value every 10 seconds
  • Displays the reading of CO2 concentration in ppm on the Liquid crystal Display continuously
  • Write the CO2 value to the serial monitor every 10 seconds (if connected)

Once the sketch is uploaded successfully, the display will immediately give the reading of CO2 concentration levels in ppm. The equation used to convert a voltage to a CO2 concentration can be deducted from the sketch:

IMPLEMENTATION STEPS

For asthma detection using breath samples and to acquire and display the CO2 signal on display module, the library, and the local variable was included into the software (Arduino IDE). In addition, the serial communication was made by assigning the baud rate (9600), data (8-bit), stop (1-bit) with no parity. To displaying the result used Liquid Crystal Display.

Hence, whenever there was an increase in the CO2 values above to the size of the display, the output of the CO2 was printed as a zero. Next, the CO2 value was calculated by multiplying with a factor of 10 and stored in the variable named Val for further assessment.Furthermore, the thresholding and window techniques were utilized to discriminate between asthma (mild) and non asthma. For this purpose, the output of expired CO2 value was limited to 28000 (2.8 % CO2) ppm as a threshold and data were recorded for 5 seconds. Implementation setup.

RESULTS AND DISCUSSION

Asthma is exceptionally normal its difficult to state without a doubt what causes asthma yet family hereditary qualities are accepted to be a key factor. Asthma frequently runs in families. Natural components for example presentation to used smoke or air contamination assume a role. Breath sample taken from the asthma patient to MG811 Sensor. CO2 concentration in a exhaled breath will be measured with the help of formula. Result will be Displayed on LCD Screen with humidity and temperature of the air.

CONCLUSION

Observing asthma and airway obstruction by using capnography is a new approach in medical technology. How ever capnograph is too expensive and not affordable for the home monitoring applications. There fore in this research a portable and low-cost respiratory co2 observing system based on mg-811 co2 sensor and micro controllers was proposed. The output information of this device can be shown either in a small LCD provided or in PC through USB port. The information can be accessed anywhere which allows the users to know elements about risk condition for their respiratory health.

REFERENCE

  1. Siti Zuleika binti Zaharudin, Mohsen Kazemi, M. B. Malarvili. 2014. Designing a Respiratory CO2 Measurement Device for Home Monitoring of Asthma Severity. IEEE Conference on Biomedical Engineering and Sciences, 8 – 10 December 2014, Miri, Sarawak, Malaysia
  2. Mark Jackson, Asthma, The biography, Oxford University Press. 2009.
  3. M. Cottini, and R. Asero, ‘Asthma phenotypes today,’ Eur. Ann. Allergy Clin. Immunol., vol. 45, no. 1, pp. 17–24, Feb. 2013.
  4. Steven Weinberger, A. Barbara Cockrill, and Jess Mandel, Principles of pulmonary medicine, 5th ed, Elsevier Inc., 2008.
  5. Melissa Langhan, ‘Continuous end-tidal carbon dioxide monitoring in pediatric intensive care units,’ J Crit Care, vol. 26, pp. 188-196, 2008.
  6. M. Folke, and B. Hok, ‘A new capnograph based on an electro acoustic sensor,’ in Proc. Int Conf IEEE Eng Med Biol Soc, 2008, pp. 856-860.
  7. D. Santoso, and F. D. Setiaji, ‘Design and Implementation of Capnograph for Laparoscopic Surgery,’ International Journal of Information and Electronics Engineering, vol. 3, no. 5, pp. 523–528, 2013.
  8. Shyam Sivaramakrishnan, Rajesh Rajamani, and Bruce D. Johnson, ‘Dynamic Model Inversion Techniques for Breath _ by-Breath Measurement of Carbon Dioxide from Low Bandwidth Sensors,’ IEEE Sensors Journal, vol. 10, no. 10, pp. 1637-1646, 2010.
  9. Tomasz Starecki, ‘Ultra-low-noise preamplifire for condenser microphones’ Review of Scientific Instruments, vol. 81, pp.124702;1-124702;4, 2010
  10. Napat Triroj, Papot Jaroenapibal, Haibin shi, Joanne I. Yeh,and Roderic Beresford, ‘Microfluidic chip-based nanoelectrode array as miniaturized biochemical sensing platform for prostate-specific antigen detection’ Biosensors and Bioelectronics, vol.26, no. 6, pp. 2927-2933, 2011.
  11. L. Zou, and T. Larsen, ‘Dynamic power control circuit forimplantable biomedical devices’ IET Circuits, Devices &Systems, vol. 5, no. 4, pp. 297-302, 2011.
  12. http://www.mindsirobotics.com/programming-resources
  13. Cheow Shek Hong, Ahmad Shahrizan Abdul Ghani, Ismail Mohd Khairuddin. 2018. IOP Conf. Series: Materials Science and Engineering 319 (2018) 012040 doi:10.1088/1757-899X/319/1/012040
  14. McPhee, S. J., & Hammer, G. D. (2010). Pathophysiology of disease: An introduction to clinical medicine (6th ed.). New York, NY: McGraw-Hill.
  15. Zuleika, S., Kazemi, M., & Malarvili, M. B. (2014). Designing a Respiratory CO 2 Measurement Device for Home Monitoring of Asthma Severity, (December), 8–10

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IOT Based Asthma Detection With CO2 Concentration Using Arduino. (2022, February 21). Edubirdie. Retrieved October 3, 2022, from https://edubirdie.com/examples/iot-based-asthma-detection-with-co2-concentration-using-arduino/
“IOT Based Asthma Detection With CO2 Concentration Using Arduino.” Edubirdie, 21 Feb. 2022, edubirdie.com/examples/iot-based-asthma-detection-with-co2-concentration-using-arduino/
IOT Based Asthma Detection With CO2 Concentration Using Arduino. [online]. Available at: <https://edubirdie.com/examples/iot-based-asthma-detection-with-co2-concentration-using-arduino/> [Accessed 3 Oct. 2022].
IOT Based Asthma Detection With CO2 Concentration Using Arduino [Internet]. Edubirdie. 2022 Feb 21 [cited 2022 Oct 3]. Available from: https://edubirdie.com/examples/iot-based-asthma-detection-with-co2-concentration-using-arduino/
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