scholarly journals Smart Detection System for Falling of Human Body

2019 ◽  
Vol 8 (4) ◽  
pp. 8502-8505
Keyword(s):  
Pulse Rate ◽  
Human Body ◽  
Detection System ◽  
Medical Clinic ◽  
Internet Protocols ◽  
Temperature Pulse ◽  
Phone Number ◽  
Basic Parameters ◽  
Day By Day ◽  
Present Emergency

Present embedded technology revolving around IoT technology. An IoT referred as a communication of varies devices through Internet protocols. Day by day peoples lifestyle is changing according with the time, people In the event that you do not have the opportunity to treat yourself, this will prompt an expansion in the quantity of interminable and heart mutations. The present emergency clinic based wellbeing framework doesn't treat conditions requiring quick treatment, for example, coronary episodes. The objective presently is to move from medical clinic based treatment to quiet focused treatment. This venture proposes a wellbeing reconnaissance framework that screens the basic parameters of patients such as temperature, pulse rate, Patient position and location. If any abnormal situations are arrived then this system will informed to belonging doctor through registered Phone number and share location of patient.

scholarly journals ’N ondersoek na parameters van prognostiese belang by die hoofbeseerde pasiënt

Curationis ◽  
1981 ◽  
Vol 4 (1) ◽  
Author(s):  
Margot Hugo
Keyword(s):  
Blood Pressure ◽  
Pulse Rate ◽  
Prognostic Value ◽  
Head Injuries ◽  
Pupillary Response ◽  
Temperature Pulse ◽  
Type Of Injury

The increase in accidents and accompanying increase in severe head injuries, have led to research into various aspects of parameters of prognostic value in patients suffering from head injuries. The possible prognostic value of the observations undertaken by nurses was researched by the author. Some of the findings regarding temperature, pulse rate, blood pressure, ventilation, pupillary response and the type of injury are discussed in this article. The importance of accurate observations by nurses is stressed.

scholarly journals Detection of Malicious Servers for Preventing Client-Side Attacks

2021 ◽  
Vol 40 (1) ◽  
pp. 230-240
Author(s):  
Khuda Bux ◽  
Muhammad Yousaf ◽  
Akhtar Hussain Jalbani ◽  
Komal Batool
Keyword(s):  
Intrusion Detection System ◽  
Detection System ◽  
Social Engineering ◽  
The Internet ◽  
Malware Analysis ◽  
Passive Detection ◽  
Active Detection ◽  
Client Side ◽  
Current Systems ◽  
Day By Day

The number of client-side attacks is increasing day-by-day. These attacks are launched by using various methods like phishing, drive-by downloads, click-frauds, social engineering, scareware, and ransomware. To get more advantage with less exertion and time, the attackers are focus on the clients, rather than servers which are more secured as compared to the clients. This makes clients as an easy target for the attackers on the Internet. A number of systems/tools have been created by the security community with various functions for detection of client-side attacks. The discovery of malicious servers that launch the client side attacks can be characterized in two types. First to detect malicious servers with passive detection which is often signature based. Second to detect the malicious servers with active detection often with dynamic malware analysis. Current systems or tools have more focus on identifying malicious servers rather than preventing the clients from those malicious servers. In this paper, we have proposed a solution for the detection and prevention of malicious servers that use the Bro Intrusion Detection System (IDS) and VirusTotal API 2.0. The detected malicious link is then blocked at the gateway.

An image-based pulse rate detection system using an FPGA platform

2017 ◽  
Author(s):  
Yu-Chen Lin ◽  
Guan-You Lin ◽  
Jia-Wei Lin ◽  
Yi-Lin Tsai ◽  
Yuan-Hsiang Lin
Keyword(s):  
Pulse Rate ◽  
Detection System

The Temperature-Pulse Rate Curve of the Isolated Frog'S Heart (RANA TEMPORARIA)

1951 ◽  
Vol 28 (2) ◽  
pp. 141-164
Author(s):  
C. L. SMITH
Keyword(s):  
Temperature Coefficient ◽  
Pulse Rate ◽  
Anterior Pituitary ◽  
Complex Form ◽  
Type A ◽  
Ringer Solution ◽  
Rate Curve ◽  
Pituitary Hormone ◽  
Temperature Pulse ◽  
Type C

1. The form of the temperature-pulse rate curve of the isolated frog's heart, when perfused with Ringer solution containing adrenaline, has been determined over the range 7-17° C. for monthly samples of frogs over a whole year. Five different types of curve were obtained during this seasonal survey, namely types A, B, C, D and E. Of these types, A and C respectively correspond to the winter and summer temperature- pulse rate curves described by Barcroft & Izquierdo (1931), while the remaining three have not previously been described. Type E, which is a linear relation with a mean temperature coefficient (Q10) of 2.12, has been interpreted as being the least complex form, in which the action of temperature on the pulse-rate is not complicated by the action of other factors. 2. The addition of various extracts of the anterior pituitary gland to the medium perfusing type E hearts led to a disproportionate increase in pulse rate above 10° C, so that the observed temperature coefficient was increased and curves of type B or D were produced. The variation in the response obtained by various pituitary extracts has been attributed to quantitative differences. 3. The typical action of anterior pituitary extract was only obtained when the heart was perfused with Ringer solution containing adrenaline. This phenomenon has been explained by assuming that there is a synergistic action between adrenaline and an anterior pituitary hormone which is inhibited at temperatures below about 10°C. 4. Thyroxine was found to have no action on the type E heart perfused with Ringer containing adrenaline, but if an extract of anterior pituitary were also present, then the type E curve was changed into type C. This is in agreement with the work of Carter (1933). Experiments were also made which showed that previous injection of thyroxine into frogs kept in the cold changed type A (winter) into type C (summer) curves. 5. It was found that adrenaline could either increase, decrease, or have no effect on, the temperature coefficient of the isolated heart. A decrease in the temperature coefficient was only observed in cases where the hearts had been isolated from frogs with active thyroids and has been attributed to the experimental technique employed. The fact that an increase in temperature coefficient may or may not be caused by adrenaline, as well as the fact that type A or C curves have been obtained when hearts were perfused with adrenaline-free Ringer has been attributed to the persistence, in varying degree, of an active sympathetico-mimetic substance in the heart for at least several hours after isolation. 6. It has been shown that the type C temperature-pulse rate curve is the only one which can definitely be attributed to the presence of the thyroid hormone. The seasonal occurrence of this type of curve closely parallels the cycle of thyroid activity described by Sklower (1925) and Meisenheimer (1936).

scholarly journals Resonance-Based Microwave Technique for Body Implant Sensing

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4828
Author(s):  
Giselle González-López ◽  
Lluis Jofre Roca ◽  
Susana Amorós García de Valdecasas ◽  
Oriol Rodríguez-Leor ◽  
Carolina Gálvez-Montón ◽  
...  
Keyword(s):  
Human Body ◽  
Coronary Stents ◽  
Microwave Technique ◽  
Basic Parameters ◽  
Clinical Experiment ◽  
Implanted Device

There is an increasing need for safe and simple techniques for sensing devices and prostheses implanted inside the human body. Microwave wireless inspection may be an appropriate technique for it. The implanted device may have specific characteristics that allow to distinguish it from its environment. A new sensing technique based on the principle of differential resonance is proposed and its basic parameters are discussed. This technique allows to use the implant as a signal scattering device and to detect changes produced in the implant based on the corresponding change in its scattering signature. The technique is first tested with a canonic human phantom and then applied to a real in vivo clinical experiment to detect coronary stents implanted in swine animals.

scholarly journals IoT-Based Smart Health Monitoring System for COVID-19 Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Mohammad Monirujjaman Khan ◽  
Safia Mehnaz ◽  
Antu Shaha ◽  
Mohammed Nayem ◽  
Sami Bourouis
Keyword(s):  
Oxygen Saturation ◽  
Monitoring System ◽  
Pulse Rate ◽  
Health Monitoring ◽  
Liquid Crystal Display ◽  
Measured Temperature ◽  
Oxygen Saturation Level ◽  
Health Monitoring System ◽  
Temperature Pulse ◽  
Health Monitoring Systems

During the ongoing COVID-19 pandemic, Internet of Things- (IoT-) based health monitoring systems are potentially immensely beneficial for COVID-19 patients. This study presents an IoT-based system that is a real-time health monitoring system utilizing the measured values of body temperature, pulse rate, and oxygen saturation of the patients, which are the most important measurements required for critical care. This system has a liquid crystal display (LCD) that shows the measured temperature, pulse rate, and oxygen saturation level and can be easily synchronized with a mobile application for instant access. The proposed IoT-based method uses an Arduino Uno-based system, and it was tested and verified for five human test subjects. The results obtained from the system were promising: the data acquired from the system are stored very quickly. The results obtained from the system were found to be accurate when compared to other commercially available devices. IoT-based tools may potentially be valuable during the COVID-19 pandemic for saving people’s lives.

scholarly journals An Empirical Comparative Analysis Using Machine Learning Techniques for Liver Disease Prediction

2021 ◽  
Vol 16 (4) ◽  
pp. 1-12
Author(s):  
Mohammed Alghobiri ◽  
Hikmat Ullah Khan ◽  
Ahsan Mahmood
Keyword(s):  
Liver Disease ◽  
Human Body ◽  
Regression Models ◽  
Near Neighbor ◽  
The Body ◽  
Machine Learning Techniques ◽  
Logistic Regression Models ◽  
Learning Techniques ◽  
Tenfold Cross Validation ◽  
Day By Day

The human liver is one of the major organs in the body and liver disease can cause many problems in human live. Due to the increase in liver disease, various data mining techniques are proposed by the researchers to predict the liver disease. These techniques are improving day by day in order to predict and diagnose the liver disease in human. In this paper, real-world liver disease dataset is incorporated for diagnosing liver disease in human body. For this purpose, feature selection models are used to select a number of features that best are the most important feature to diagnose the liver disease. After selecting features and splitting data for training and testing, different classification algorithms in terms of naïve Bayes, supervised vector machine, decision tree, k near neighbor and logistic regression models to diagnose the liver disease in human body. The results are cross-validated by tenfold cross validation methods and achieve an accuracy as good as 93%.

scholarly journals Performance Assessment of Ml Techniques for Detecting Intrusions in the Network

2019 ◽  
Vol 8 (12) ◽  
pp. 4095-4100
Keyword(s):  
Network Security ◽  
Intrusion Detection System ◽  
Detection System ◽  
Development Stage ◽  
Technological Advancement ◽  
Security Technology ◽  
Comprehensive Survey ◽  
Learning Machine ◽  
Result Analysis ◽  
Day By Day

It has become crucial for the organizations, military and personal computer users to make the network security. Day by day, security has become a major issue with the increase of internet usage. The improvement in the security technology can be much understood from the security history. Network security is an immense field and it is in development stage. An immense amount of data is being generated every second due to technological advancement and reforms. Social networking and cloud computing are generating a huge amount of data every second. Every minute data is being captured in the computing world from the click of the mouse to video people tend to watch generating an immediate recommendation. Everything a user is doing on the internet is being captured in different ways for multiple intents. Now it all ends up monitoring the system and network and, securing lines and servers. This mechanism is called Intrusion Detection System(IDS). Hacker uses multiple numbers of ways to attack the system which can be detected through a number of algorithm and techniques. A comprehensive survey of some major techniques of machine learning implemented for detecting intrusions. Classification techniques are SVM, Random Forest algorithm, Extreme learning machine, and Decision Tree. NSL-KDD is the dataset used to get the higher rate of detection. The Result Analysis shows that, in terms of accuracy, this paper accomplishes better results when compared to any other related methods.

scholarly journals Mathematical Model Optimization Techniques under Unreliable Electromagnetic Field for ECG Waves

2021 ◽  
pp. 184-190
Keyword(s):  
Mathematical Model ◽  
Electromagnetic Field ◽  
Mobile Phone ◽  
Human Body ◽  
Human Heart ◽  
Optimization Techniques ◽  
Variation Of Parameters ◽  
Mathematical Expressions ◽  
Electrocardiogram Ecg ◽  
Day By Day

The electrocardiogram (ECG) has significant scientific importance for analyzing the majority of cardiovascular diseases. On one side the technologies are growing very fast, on the other side there is a need to check and balance their effect on human health. The activity of the heart ECG voltage vector is well explained by the modeling of the ECG wave. It is one of the essential tools to do so. In the proposed work we tried to elucidate a mathematical model for the ECG wave by presumptuous the human body as a cylindrical complex dielectric and conducting medium. The human heart is considered as a harmonic bio-signal generator positioned in this medium. Nowadays, technologies are enhancing in various aspects as the graph of mobile phone users increasing rapidly day by day. Essentially, it needed to understand its side effects on the human body and especially for the health of the human heart. The electrical equivalent of the heart can be used to develop a mathematical model for the human heart as per its functioning. The ECG parameters which are affecting due to the electromagnetic wave can be analyzed using a proposed mathematical model. If mathematical expressions are available relations can be formed and understand for each part of the human heart. As mobile phone and its, some component gives electromagnetic exposure to the human body. Hence there is a need to develop a model of the human heart using mathematical analysis. Hence, this paper proposes a mathematical model for ECG and variation of parameters due to electromagnetic field- based.

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