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Understanding diagnosis of thyroid disease by using

different IoT devices Sonia Rani, Dr. Apash Roy

School of Computer Science and Engineering

Lovely Professional University, Jalandhar, Punjab, India

ABSTRACT−In this Mainly Presents an IoT, Artificial Intelligence based Health Monitoring System for emergency medical problems.

Prediction is better than cure any disease before reach at last stage. Thyroid disease has now become 2nd largest disease in the endocrine

field. Thyroid monitoring can be done by either blood sample test or basal body temperature. For this SHIMMER, Thermal wireless

sensor is use. These systems based on artificial intelligence Thyroid hormonal problems can be diagnosed using an artificial neural

network approach. By using these techniques thyroid can be diagnosed without the blood sample test and any pain.

Keywords:, Thyroid, basal body temperature monitoring , thermal sensor, Diagnosis, Radial basis function, IoT

Devices, Artificial Intelligence.

Introduction

Due to different odd environment conditions like water pollution, air pollution etc., and life habits of human being

created lots of health issues in increasing rate. Issues related to health should be in upmost concern of human

beings. They should take care of their health not only by good life habits, but also a constant and periodic

monitoring of the health conditions. In different fields of medical, there are a number of technological instruments

and methods are been used. With the emerging trends in using technology, medical field is also a progressive area.

There is a most common and pathetic problem related to health is Thyroid. It is sometimes called the silent killer. A

butterfly shaped gland found just below of our neck is termed as thyroid. Patients suffering from thyroid problem

also victimized to so many deficiencies like calcium, vitamin D, in their body. There is no not cure for thyroid for

the whole life. After taking medicine it can be balanced only. The disease occur due to imbalance in production of

two hormones called “triodiothyronine (T3)” and “thyroxine (T4)” hormones which is synchronized by the

“Thyroid-Stimulating Hormone (TSH)” in the body. It affects the metabolism activities in human body, strength of

muscle, body weight, and temperature of our body.

In computer science there are different expert systems are developed to diagnose different kinds of diseases with

high accuracy and diagnosis the diseases at early stages. One of the major challenges in giving proper treatment is

always fast and accurate diagnosis of the diseases such as Diabetes, Thyroid, cancer, depression, stress, autism

spectrum disorder and so on .

Here are some of the related tools and technology found in the literature is discussed.

REST API is a open source system, which act as interface of exchanging data over solid http system connection

in IP enabled system. (Jabbar et al., 2017). It is a light weight system.

Raspberry Pi it is small packet card size single board microcontroller. It is very cheap and absolute method. The

main Target of using the system is, to update the data once and send an alert to doctor. The task is accomplished

by using MSSQL db module to link Raspberry Pi, GSM module and interface (Banka et al., 2018). Raspberry Pi

may be observed as a built in software which enables user to write program and design animation, play game or

video. For client server communication, Python language has been used in this work to write the script (Zhao et

al., 2015).

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Clinical Significance Hrv, heart failure, diabetic neurology, depression, and body temperature is measure by

DS18B20 sensor. The results are come in form of degree F and degree C (Rajput et al., 2016).

RFID At present many hospitals used IoT and merged with wifi sensor with RFID,NFC tag and sensor nodes

and also used E-healthcare system for getting the information of patient (Khan, 2017).

IBM Watson’s electronic thinking of information and plan the best treatment for patient by checking vital

medicinal examinations. (Rath & Pattanayak, 2018).

Evaluate mental disorder problems To find out mental disorder disease detection. An early warning system is

created to predict this type of disease match some specific symptoms. The categories of psychiatric biomarkers

include genetics, proteins or ‘neuroinaging’ findings (La et al., 2018).

NanoSmart Health Care: Small light device with image sensor to capture the footage and wirelessly send this

acquired data to data recorder is widely used in nowadays. The camera is either powered by a small battery or

induction charge with the help of data recorder. A pill- Camera is an example of such device. It is simple as

swallow a pill and getting high resolution picture of internal organs. (Sundaravadivel et al., 2018).

Cooey Smart Health: Cooey is length wise health monitoring BP. It not only store and organize the health

history, in fact it also give this info to your doctor (Gupta et al., 2016).

PHQ-9 Mind at Ease: It making the whole process less persistent by implementing Medical Imaging (Brain

Scans) and depression detection (Poonkodi et al., 2016).

Wearable devices: There are some devices which are specially designed; so that a human being can wear it and

the device can not only collect data, but some kind of processing also be performed by them. The devices

comprises of several sensors. They are useful in terms that they can be wearable in the human body, or can be

transported to interior places, where require services for healthcare is present or in case of medical emergency.

(Park & Subramaniyam, 2017).

(MANETS): Mobile Ad-hoc Networks. The Communication infrastructure is wireless network. In this type of

networking the sensor nodes acquires the data from the deployed environment and transmits the data to the

devices in the base station. (Alamelu & Mythili, 2017).

Water-resistant: These wrist worn devices can be used without discomfort during activities of daily living,

including sleep, to determine the physical activity of a person (Mannini et al., 2013).

Cloud Computing: Cloud computing, when combining with IoT can be a useful tool for short time duration.

(Yattinahalli & Savithramma, 2018).

Artificial Intelligence: Artificial Intelligence is widely applied to enhance the Intelligent, self-learning method

of analysis system. However, the records here needs to be entered manually, and this can be seen as a big

limitation. (Ullah et al., 2016).

GPRS and Bluetooth technology: Mobile health (MHealth) is a IoT based medical health infrastructure, which

includes the (GPRS), 4G systems, global positioning system (GPS), and Bluetooth technology. It is used to

examine, the human activities. (Subasi et al., 2018).

OMDP: (An ontology based model for diabetic patient) This healthcare system are applied for several

application including diabetes management, hypertension to make adequate therapeutic and diagnosis for

patients.

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Thyroid monitoring system: A computerized system to monitor thyroid is implemented in simulink in the work

(Mohanty et. al., 2016). This system uses a bottom up approach with consideration of the basal body temperature

module. The task is achieved by a ring oscillator along with the use of a counter and controller.

Objectives

1. Understanding diagnosis of thyroid disease by using different IoT sensors without any blood sample test or

without any pain, less cost at early stages.

2. Make the all people live healthy life. No one is suffering from any disease.

3. By making an alert generation system regarding any health problem so people have always alert about their

health.

Summary and Impact on society of smart healthcare monitoring system

It is certain that smart health care monitoring systems are very much beneficial for the all society. Because of these

systems we can easily diagnosis the many health problems with less cost, less time, anywhere and any anytime.

Thyroid hormonal problems can be diagnosed using an artificial neural network approach, thermal sensors so

thyroid diagnosis by without the blood sample test and any pain.

References

1. Alamelu, J. V., Mythili, A. (2017). Design of IoT based Generic Health Care System.

IoT data is valuable addition to other clinical data sources, such as (EHR). Artificial intelligence and vital

technologies for IoMT is considered as they provide to multiple benefits to patients and doctors. Recently by

Jessica Kent UC San Franscisco (UCSF) is launching the centre for Intelligent Imaging, which will advance the

applications of artificial intelligence tools in medical imaging. The combination of use the IoT, Artificial

Intelligence and machine learning and other emerging technologies to create smart hospitals and diagnosis the health

problems by needle less and cost effective health care solutions easily get.

TCP/IP: The protocol for internet that gives any microcontroller, access to the Wi-Fi network that supports

common standard of wi-fi. The microcontroller must be wi-fi or network enabled device.

International conference on Microelectronic Devices, Circuits and Systems.

2. Alqahtani, F. H. (2018). The Application of the IoT in Healthcare. International Journal of computer Applications. 180, 0975 – 8887.

3. Banka, S., Madan, I., & Saranya, S. S. (2018). Smart Healthcare monitoring using IoT.

4. International Journal of Applied Engineering Research. 13,11984-11989.

5. Gupta, P., Aggarwal, D., Chhabra, J., & Dhir, P. K. (2016). IoT based Smart HealthCare Kit. International Conference on

Computational Techniques in Information and Communication Technologies.

6. Jabbar, S., Ullah, F., Khalid, S., & Khan M. (2017). Semantic Interoperability in Heterogeneous IoT Infranstructure for Healthcare.

Wireless Communication and Mobile Computing. 2017, 1-10.

7. Khan, S. F. (2017). Health Care Monitoring System in Internet of Things by using RFID.

8. International Conference on Industrial Technology and Management.978, 5090-5330.

9. La, I. D., Diez, T., Franco, M.A., & Alonso, S.G. (2018). IoT-Based Services and Applications for Mental Health in the Literature. Journal of Medical System.36, 93-101.

10. Mannini, A., .Intille, S. S., & Haskell, W. (2013). Activity Recognition Using a Single Accelerometer Placed at the Wrist or Ankle.

Journal of the American College of Sports Medicine.45(11):2193-203.

11. Park, S. J., & Subramaniyam, M. (2017). Development of the Elderly Healthcare Monitoring System with IoT. Advances in Intelligent

Systems and Computing. 482,309- 315.

12. Poonkodi, M., Srinivasan, A., Tumma, B., & Ramaswamy, S. (2016). A Comprehensive Healthcare System to Detect Depression.

Indian Journal of Science and Technology. 9, 47.

13. Purri, S., Choudhury, T., Kumar, P., & Kashyap, N. (2017). Specialization of Iot Applications in Health care Industries. International

Conference on Big Data Analytics and Computational Intelligence.

14. Rajput, D. S., & Gour, R. (2016). An IoT Framework for Healthcare Monitoring Systems.

© 2018 IJRAR October 2018, Volume 5, Issue 4 www.ijrar.org (E-ISSN 2348-1269, P- ISSN 2349-5138)

IJRAR1BGP158 International Journal of Research and Analytical Reviews (IJRAR) www.ijrar.org 901

International Conference on Thermal, Mechanical and Multi-Physics

SimulationandExperimentsinMicroelectronicsandMicrosystem,2016,1-4.

15. International Journal of Computer science and Information Security.14, 5.

16. Rath, M. & Pattanayak, B. (2018). Technological improvement in modern health care applications using IoT and proposal of novel

health care approach. International Journal of Human Rights in Healthcare. 12 ,148-162.

17. Subasi, A., Radhwan, M., & Kurdi, R. (2018). IoT based Mobile Healthcare System for Human Activity Recognition. 15th Learning

and Technology Conference.

18. Sundaravadivel, P., Kougianos, E., & Mohanty, S.P. (2018). Everthing You Know About Smart Health Care. IEEE Consumer Electronics Magazine. 7, Issue 1.

19. Ullah, K., Shah, M. A., & Zhang, S. (2016). Effective Ways to Use Internet of Things in the Field of Medical and Smart Health Care.

International Conference on Intelligent Systems Engineering.

20. Yattinahalli, S. & Savithramma, R. M. (2018). A Personal Healthcare IoT System model using Raspberry Pi 3. International

Conference on Inventive Communication and Computational Technologies.

21. Zhao, C.W., Jegatheesan, J., & Loon, S. C. (2015). Exploring IoT using Raspberrry Pi.

22. Intentional Journal of Computer Networks and Applications.2, 2395-0455.

23. Mohanty, S.P., Kougianos, E. and Sundaravadivel, P. (2016). An energy efficient sensor for thyroid monitoring through the IoT. 17th