Real-Time Vital Signs Monitoring System

Real-Time Vital Signs Monitoring System

Srishti Dhingra1, Madhuri Sharma2, Hitesh Arora3, Anupam Misra4, Surabhi Nayak5

Department of Computer Science and Engineering SRM-IST, NCR Campus, Modinagar

Abstract In this paper, we will discuss the modern visionary of the health care industry in order to provide better health care to patient anytime and anywhere in the world in a more economic and patient-friendly manner. Therefore, for increasing the patient care efficacy, this arises a need to improve the patient monitoring devices. The medical world today faces basic two problems: when it comes to patient monitoring, firstly the need of healthcare providers present the bedside pharmacy to the patient and secondly the patient is restricted to bed and wired to large machines [2]. In order to achieve better quality patient care, the above-cited problems have to be solved. This paper discusses the acquisition of physiological parameters such as heart rate, body temperature, breathing and ECG and displaying them in Graphical User Interface for being viewed by the doctor.

1. INTRODUCTION

   The main objective is to make a health monitoring system simple and provide the accuracy that helps a lot in monitoring only body temperature, heart rate, breathing, but a future perspective further expands our system by measuring various parameters like ECG and providing security measures through face-recognition. Analyze these parameters helps in identifying the problem to give the patient a better cure as soon as possible.

   A framework will be designed that can wirelessly transmit the readings immediately to the doctor anywhere in the world that will incorporate through the concept of IOT. This framework measures each and every single parameter through this integrated environment.

2. HARDWARE REQUIRED & USED

   ARDUINO UNO

   Arduino Uno is a micro-controller board developed by Arduino.cc which is an open-source electronics platform mainly based on AVR microcontroller Atmega328.

   HEART-BEATSENSOR

   Heartbeat Sensor is a device and is used to measure the heart rate i.e. speed of the heartbeat.

   ECG SENSOR

   Heart activity is closely linked to physiological and psychological arousal, making it ideal for understanding our mental states in greater detail.

   The electrocardiogram (ECG) is a diagnostic tool used for recording the electrical and muscular activity of the heart over a given time period.

   BREATHING SENSOR

   A spirometer is an apparatus for measuring the volume of air inspired and expired by the lungs. It is used in the case of lung and respiratory tract diseases such as asthma or chronic- obstructive bronchitis.

   It measures the respiratory flow rate and calculates the respiratory volume breathed in and out (inspiratory and expiratory lung volume) from this. These devices are usually designed as lightweight, portable systems that can be used conveniently in medical practices and in patients homes.

   SKIN RESPONSE SENSOR

   It is the measure of the continuous variations in the electrical characteristics of the skin, i.e., for instance, the conductance, caused by the variation of the human body sweating.

   LCD display

   A liquid crystal display is a thin, flat electronic visual display that uses the light modulating properties of liquid crystals (LCs).

   TABLE I. NORMAL RANGE OF VITAL SIGNS

   NORMAL RANGE
   Heart Rate	60-100 beats per minute
   Breathing Rate	12-20 breaths per minute
   Skin Response	Dry Skin: 0-40 Normal Skin: 40-70 Oily Skin: 70-90
   ECG Response	Normal: -30o to 105o Left Axis Deviation: -30o to -90o Right Axis Deviation: +105o to +180o

3. ASSEMBLING OF THE DEVICES

   To implement this framework; create an Arduino-based low-power Internet-of-Things (IOT) device with built-in sensors that can send the data to any location.

   Fig. 1. Assembling of the Various Devices

   In this system, it measures the patients parameters (temperature, heart rate, pulse, breathing rate, skin response, etc.) through the different available sensors. This sensor collected data i.e. biometric information is given to raspberry pi and then it is transferred to the server. The data stored in a database and can be displayed on a website that can be accessed only by authorized personnel.

   This finger type heartbeat sensor works by detecting the pulses from fingers by touching the device. Every heartbeat will alter the amount of blood in the finger and the light from the IR LED passing through the finger and thus detected by the Photo Diode will also vary.

   The pulsation point of the skin surface and the vital sign can be calculated from the measured signal.

   The proposed system will assist patients in remote locations (e.g. home healthcare) and that is not just about observing a severe disease state, but about helping the patients by giving those references of several doctors.

   By evening this project, it will provide an inexpensive system for patients health monitoring which can shield their lives by proving emergency attention in real-time.

   Data gathered from this device is analyzed and stored, and the aggregation from multiple sensors and medical devices helps make informed decisions in a timely manner.

4. PROPOSED APPROACH

   Fig. 2. Data Flow Diagram

   Fig. 3. Flow Chart

5. IMPLEMENTATION OF THE SYSTEM

   HEART RATE

   In this, as we put our finger in the clip; the sensor attached to the clip analyzes the blood that flows through the vessels under the skin. The frequency of flowing blood will provide a movement that will be read by the sensor, this will be our Heart Rate.

   Fig. 4. Measuring the Heart Rate

   BREATHING RATE

   As we blow normally into the spirometer the ball inside the unit start bouncing. This bouncing of the ball will give frequency to the sensor attached to the unit. The frequency of blown air will provide a movement that will be read by the sensor, this will be our capacity of breathing. The hardware will convert the analog signal into digital signal readings.

   Fig. 5. Measuring the Breathing Rate

   SKIN RESPONSE

   The Skin Response sensor defines the conductivity of the skin. It analyzes the moisture content of skin on the basis of which type of skin related problem can find out. Sweat glands under the skin work according to the temperature and environment on the skin surface.

   Fig. 6. Measuring Skin Sensitivity

   Above all readings are displayed in LCD screen as well as on Web App. This framework will convert the analog signal into digital signal readings. These readings will fetch into the web app with the help of a serial port. In the web app, the patient can monitor his or her readings and simultaneously can approach the doctor with the reference prescribed the suggestions of it.

   Fig. 7. Web App Display

6. REFERENCES

1. Ghany M A A E, Saleab M S, Toma R M, et al. Efficient wearable real-time vital signs monitoring system, IEEE International Conference Electronics, Circuits, and Systems. IEEE, 2015:217-220.

2. Luo J, Chen Y, Tang K, et al. Remote monitoring information systemand its applications based on the Internet of Things, BioMedical Information Engineering, 2009. FBIE 2009. International Conference on Future. IEEE, 2009:482-485.

3. Anzanpour A, Rahmani A M, Liljeberg P, et al. Internet ofThings Enabled In-Home Health Monitoring System Using Early Warning Score, ACM International Conference on Wireless Mobile Communication and Healthcare. ACM, 2015:174-177.

4. Li S L, Han Y, Li G, et al. Design and Implementation of Agricultral Greenhouse Environmental Monitoring System Based on Internet of Things. Applied Mechanics & Materials, 2011, 121- 126:2624-2629.

5. Liu Z, Tao W, Jiang L, et al. Design and application on electric vehicle real-time condition monitoring system by Internet of things technology, IEEE International Conference on Software Engineering and Service Science. IEEE, 2014:744-747.

6. Chen J, Chen F, Chen W. The healthy real-time monitoring system for bridge cluster based on 3G internet of things, Journal of Jinan University, 2013, 34(1):57-61.

7. Rainieri C, Fabbrocino G, Cosenza E. Near real-time tracking of dynamic properties for standalone structural health moni- toring systems, Mechanical Systems Signal Processing, 2011, 25(8):3010-3026.

8. Rathore M M, Ahmad A, Paul A, et al. Real-time Medical Emergency Response System: Exploiting IoT and Big Data for Public Health, Journal of Medical Systems, 2016, 40(12):283.

9. Liang, PoChou. Cost-effective design of real-time home healthcare telemonitoring based on mobile cloud computing, In- ternational Conference on Health Informatics. 2016:5-15.

10. https://www.semanticscholar.org/paper/Efficient-wearable-real- time-vital-signs-monitoring-El-Ghany-Saleab/02e40 dfe9b746fb96c0ea18ea7f025915ab45abd

11. https://www.researchgate.net/publication/309660119 Real_Time_Monitoring_of_Human_Body_Vital_Signs_using_ Bluetooth_and_WLAN

12. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2815