GSM and Arduino Based Vital Sign Monitoring System

Austin, Rachel N.; Lobo, Fiona; Rajaguru, Swarnalatha

doi:10.2174/1874120702115010078

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…The signal’s flatness concerning the normal distribution is assessed using kurtosis. A positive number for kurtosis often denotes a signal that is leptokurtic, which is flatter than the normal distribution, whereas a negative value denotes a signal that is platykurtic, which is less flat than the normal distribution [ 26 ]. The implemented equation for kurtosis is the following:

where x is a random variable having n observations.…”

Section: Methodsmentioning

confidence: 99%

System and Method for Driver Drowsiness Detection Using Behavioral and Sensor-Based Physiological Measures

Bajaj

Kumar

Kaushal

et al. 2023

Sensors

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The amount of road accidents caused by driver drowsiness is one of the world’s major challenges. These accidents lead to numerous fatal and non-fatal injuries which impose substantial financial strain on individuals and governments every year. As a result, it is critical to prevent catastrophic accidents and reduce the financial burden on society caused by driver drowsiness. The research community has primarily focused on two approaches to identify driver drowsiness during the last decade: intrusive and non-intrusive. The intrusive approach includes physiological measures, and the non-intrusive approach includes vehicle-based and behavioral measures. In an intrusive approach, sensors are used to detect driver drowsiness by placing them on the driver’s body, whereas in a non-intrusive approach, a camera is used for drowsiness detection by identifying yawning patterns, eyelid movement and head inclination. Noticeably, most research has been conducted in driver drowsiness detection methods using only single measures that failed to produce good outcomes. Furthermore, these measures were only functional in certain conditions. This paper proposes a model that combines the two approaches, non-intrusive and intrusive, to detect driver drowsiness. Behavioral measures as a non-intrusive approach and sensor-based physiological measures as an intrusive approach are combined to detect driver drowsiness. The proposed hybrid model uses AI-based Multi-Task Cascaded Convolutional Neural Networks (MTCNN) as a behavioral measure to recognize the driver’s facial features, and the Galvanic Skin Response (GSR) sensor as a physiological measure to collect the skin conductance of the driver that helps to increase the overall accuracy. Furthermore, the model’s efficacy has been computed in a simulated environment. The outcome shows that the proposed hybrid model is capable of identifying the transition from awake to a drowsy state in the driver in all conditions with the efficacy of 91%.

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where x is a random variable having n observations.…”

Section: Methodsmentioning

confidence: 99%

System and Method for Driver Drowsiness Detection Using Behavioral and Sensor-Based Physiological Measures

Bajaj

Kumar

Kaushal

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…In a previous study, Anggi Zafia made a prototype of an Inpatient Vital Monitoring Device using a Wireless Sensor as a Physical Distancing Effort for handling Covid 19 using Zigbee [8]. A similar study was also conducted by Fahmi Farisandi and Ahmad Fatkudin on Portable Patient Diagnostics equipped with Normal/Abnormal Indicators [9]. The device analyzed the rate of change of BPM and changes in the patient's body temperature.…”

Section: Introductionmentioning

confidence: 99%

IOT-Based Human Vital Sign Monitoring Tool Using Telegram Notifications (BPM and Respiration Rate Parameters)

Tetraputra,

Kholiq

2023

j.teknokes

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Vital signs play a crucial role in monitoring the progress of adult or pediatric patients during hospitalization, as they enable prompt detection of delayed recovery or adverse events. Vital signs are measured to obtain fundamental indicators of the patient's health status. The measurement of vital signs, including blood pressure, temperature, pulse, and respiratory rate, is the most common intervention in hospital medicine. Advanced monitoring systems combine clinical and technological aspects to deliver innovative healthcare outcomes. Remote patient monitoring systems are increasingly becoming the cornerstone of healthcare delivery, replacing traditional manual recording with computer and smartphone-based electronic recording as a versatile and innovative health monitoring system. This study aims to design a Vital Sign Monitoring Parameter BPM and RR tool with Notifications via the IoT-Based Telegram application. The tool enables the monitoring of vital signs, particularly BPM and RR, regardless of the patient's location and at any given time. This allows doctors, health workers, and patients to stay informed about their health condition. Real-time display of vital sign data is available through the TFT LCD screen, and the data from the screen can be accessed via Telegram. The Telegram application will send notifications in the event of abnormal patient conditions. MAX30100, a digital sensor for detecting breathing rate and heart rate, is utilized in this research. Furthermore, the data obtained shows errors that are within the allowable limits for each parameter. The difference between the heart rate readings and the respiratory rate values on the device and the patient monitor is 1.14% for heart rate and 0.84% for respiratory rate. This study indicates that it is time to monitor vital signs that can be seen remotely and have a system that is an inexpensive and easy-to-operate device for health workers without interfering with activities of daily living.

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“…The Pulse sensor used to measure the heart rate is done with module Arduino Uno and pro mini for ECG and PPG graphs [9]. Vital signs and pulse rate are Continuous heart rate and body temperature monitoring system designed using Arduino and its application [11]. Persons' physical characteristics are measured using sensors and broadcasted through ZigBee to PC [12].…”

Section: Introductionmentioning

confidence: 99%

Design and Demonstration of Arduino based Low Cost Pulse Oximeter

Vananth,

Rajalakshmi,

Sathya

2023

IJRITCC

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One of the main reasons for the pushback of the pandemic in India was the awareness that developed in people during the crisis. The adapting mindset of the Indian populace helped turn the tides. The Pulse Oximeter proved to be an important tool that helped in identifying the affected, to get timely healthcare. A very simple information was shared among people that the BPM (heart rate in beats per minute) should be around 60 - 100 (resting) for an average adult and the SpO2, i.e., oxygen saturation must be above 95% for all age groups. Just this was able to counter an entire wave of the Pandemic with the help of early detections, timely isolations, immediate health care and much more. However, access to this was not available to everyone due to the high prices of these devices. This project aims to build a simple monitor module with an Arduino Nano board which can determine the Blood Oxygen level and Heart rate of a person by using the MAX30102 sensor.

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GSM and Arduino Based Vital Sign Monitoring System

Cited by 7 publications

References 11 publications

System and Method for Driver Drowsiness Detection Using Behavioral and Sensor-Based Physiological Measures

System and Method for Driver Drowsiness Detection Using Behavioral and Sensor-Based Physiological Measures

IOT-Based Human Vital Sign Monitoring Tool Using Telegram Notifications (BPM and Respiration Rate Parameters)

Design and Demonstration of Arduino based Low Cost Pulse Oximeter

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