IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Design and development of fall detector using fall accelerationeSAT Journals
Abstract Fall of patients and aged people may become fatal if unnoticed in time. The concept is to have a fall detection system which sends alarm to the concerned people or to the doctor, at the time of eventuality. To minimize fall and its related injuries continuous surveillance of subjects who are diseased and prone to fall is necessary. The article discusses the design and development of a prototype of an electronic gadget which is used to detect fall among elderly and the patients who are prone to it. In this article, the body posture is derived from change of acceleration in three axes, which is measured using triaxial accelerometer (adxl335). The sensor is placed on the lumbar region to study the tilt angle. The acceleration values in each axis are compared twice with threshold and also a delay of 20 secs between two comparisons, to reduce the false alarms. Values of the threshold voltage are selected by experimental methods. The algorithm is executed by microcontroller (PIC16F877A). The location of fall is determined by GPS receiver, which is programmed to track the subject continuously. On detection of fall, the device sends a text message through GSM modem, and communicates it to computer through ZigBee transceivers. The device can also be switched to only alarm if text message is not required. The prototype developed is tested on many subjects and also on volunteers who simulated fall. Out of 50 trials 96% of accuracy is achieved with zero false alarms for daily activities like jogging, skipping, walking on stairs, and picking up objects. Index Terms: Fall Detector, Medical Alarming System, Personal Emergency Response System, triaxial accelerometer, microcontroller
An Ill-identified Classification to Predict Cardiac Disease Using Data Cluste...ijdmtaiir
The health care industry contains large amount of
health care data with hidden information. This information is
useful for making effective decision. For getting appropriate
result from the hidden information computer based data mining
techniques are used. Previously Neural Network (NN) is
widely used for predicting cardiac disease. In this paper, a
Cardiac Disease Prediction System (CDPS) is developed by
using data clustering. The CDPS system uses 15 parameters to
predict the disease, for example BP, Obesity, cholesterol, etc.
This 15 attributes like sex, age, weight are given as the input.
In this paper by using the patient’s medical record, an illdefined classification is used at the early stage of the patient to
diagnose the cardiac disease. Based on the result the patients
are advised to keep the sensor to predict them.
A Review Paper on Design of GPS and GSM Based Intelligent Ambulance MonitoringIJERA Editor
Proposed paper presents design of such a monitoring system for emergency patient transportation employing ARM 7 processor module. The system will be useful for monitoring ambulance location using Google map. It also include biomedical sensors to monitor heart bit rate and temperature of patient through SMS. The front end application at the monitoring system is developed using visual basic software in Personal Computers. It can display location of ambulance and status of heart bit rate and temperature of patient. After receiving SMS hospital can prepare their staff for proper treatment of coming patient.
Design and development of fall detector using fall accelerationeSAT Journals
Abstract Fall of patients and aged people may become fatal if unnoticed in time. The concept is to have a fall detection system which sends alarm to the concerned people or to the doctor, at the time of eventuality. To minimize fall and its related injuries continuous surveillance of subjects who are diseased and prone to fall is necessary. The article discusses the design and development of a prototype of an electronic gadget which is used to detect fall among elderly and the patients who are prone to it. In this article, the body posture is derived from change of acceleration in three axes, which is measured using triaxial accelerometer (adxl335). The sensor is placed on the lumbar region to study the tilt angle. The acceleration values in each axis are compared twice with threshold and also a delay of 20 secs between two comparisons, to reduce the false alarms. Values of the threshold voltage are selected by experimental methods. The algorithm is executed by microcontroller (PIC16F877A). The location of fall is determined by GPS receiver, which is programmed to track the subject continuously. On detection of fall, the device sends a text message through GSM modem, and communicates it to computer through ZigBee transceivers. The device can also be switched to only alarm if text message is not required. The prototype developed is tested on many subjects and also on volunteers who simulated fall. Out of 50 trials 96% of accuracy is achieved with zero false alarms for daily activities like jogging, skipping, walking on stairs, and picking up objects. Index Terms: Fall Detector, Medical Alarming System, Personal Emergency Response System, triaxial accelerometer, microcontroller
An Ill-identified Classification to Predict Cardiac Disease Using Data Cluste...ijdmtaiir
The health care industry contains large amount of
health care data with hidden information. This information is
useful for making effective decision. For getting appropriate
result from the hidden information computer based data mining
techniques are used. Previously Neural Network (NN) is
widely used for predicting cardiac disease. In this paper, a
Cardiac Disease Prediction System (CDPS) is developed by
using data clustering. The CDPS system uses 15 parameters to
predict the disease, for example BP, Obesity, cholesterol, etc.
This 15 attributes like sex, age, weight are given as the input.
In this paper by using the patient’s medical record, an illdefined classification is used at the early stage of the patient to
diagnose the cardiac disease. Based on the result the patients
are advised to keep the sensor to predict them.
A Review Paper on Design of GPS and GSM Based Intelligent Ambulance MonitoringIJERA Editor
Proposed paper presents design of such a monitoring system for emergency patient transportation employing ARM 7 processor module. The system will be useful for monitoring ambulance location using Google map. It also include biomedical sensors to monitor heart bit rate and temperature of patient through SMS. The front end application at the monitoring system is developed using visual basic software in Personal Computers. It can display location of ambulance and status of heart bit rate and temperature of patient. After receiving SMS hospital can prepare their staff for proper treatment of coming patient.
An Experimental Study of Diabetes Disease Prediction System Using Classificat...IOSRjournaljce
Data mining means to the process of collecting, searching through, and analyzing a large amount of data in a database. Classification in one of the well-known data mining techniques for analyzing the performance of Naive Bayes, Random Forest, and Naïve Bayes tree (NB-Tree) classifier during the classification to improve precision, recall, f-measure, and accuracy. These three algorithms, of Naive Bayes, Random Forest, and NB-Tree are useful and efficient, has been tested in the medical dataset for diabetes disease and solving classification problem in data mining. In this paper, we compare the three different algorithms, and results indicate the Naive Bayes algorithms are able to achieve high accuracy rate along with minimum error rate when compared to other algorithms.
An Approach for Disease Data Classification Using Fuzzy Support Vector MachineIOSRJECE
: Data Mining has great scope in the field of medicine. In this article we introduced one new fuzzy approach for prediction of hepatitis disease. Many researchers have proposed the use of K-nearest neighbor (KNN) for diabetes disease prediction. Some have proposed a different approach by using K-means clustering for reprocessing and then using KNN for classification. In our approach Naive Bayes classifier is used to clean the data. Finally, the classification is done using Fuzzy SVM algorithm. Hepatitis diseases data set is used to test our method. We are able to obtain model more precise than any others available in the literature. The Fuzzy SVM approach produced better result than KNN with Fuzzy c-meansand Fuzzy KNN with Fuzzy c-means. Theintroduction of Fuzzy Support Vector Machine algorithm certainly has a positive effect on the outcome of hepatitis disease. This fuzzy SVM model led to remarkable increase in classification accuracy
Development of a Home-based Wrist Rehabilitation System IJECEIAES
There are several factors that may result to wrist injuries such as athlete injuries and stroke. Most of the patients are unable to undergo rehabilitation at healthcare providers due to cost and logistic constraint. To solve this problem, this project proposes a home-based wrist rehabilitation system. The goal is to create a wrist rehabilitation device that incorporates an interactive computer game so that patients can use it at home without assistance. The main structure of the device is developed using 3D printer. The device is connected to a computer, where the device provides exercises for the wrist, as the user completes a computer game which requires moving a ball to four target positions. Data from an InvenSense MPU-6050 accelerometer is used to measure wrist movements. The accelerometer values are read and used to control a mouse cursor for the computer game. The pattern of wrist movements can be recorded periodically and displayed back as sample run for analysis purposes. In this paper, the usefulness of the proposed system is demonstrated through preliminary experiment of a subject using the device to complete a wrist exercise task based on the developed computer game. The result shows the usefulness of the proposed system.
K-Nearest Neighbours based diagnosis of hyperglycemiaijtsrd
AI or artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction. As a result, Artificial Intelligence is gaining Importance in science and engineering fields. The use of Artificial Intelligence in medical diagnosis too is becoming increasingly common and has been used widely in the diagnosis of cancers, tumors, hepatitis, lung diseases, etc... The main aim of this paper is to build an Artificial Intelligent System that after analysis of certain parameters can predict that whether a person is diabetic or not. Diabetes is the name used to describe a metabolic condition of having higher than normal blood sugar levels. Diabetes is becoming increasingly more common throughout the world, due to increased obesity - which can lead to metabolic syndrome or pre-diabetes leading to higher incidences of type 2 diabetes. Authors have identified 10 parameters that play an important role in diabetes and prepared a rich database of training data which served as the backbone of the prediction algorithm. Keeping in view this training data authors developed a system that uses the artificial neural networks algorithm to serve the purpose. These are capable of predicting new observations (on specific variables) from previous observations (on the same or other variables) after executing a process of so-called learning from existing training data (Haykin 1998).The results indicate that the performance of KNN method when compared with the medical diagnosis system was found to be 91%. This system can be used to assist medical programs especially in geographically remote areas where expert human diagnosis not possible with an advantage of minimal expenses and faster results. Abid Sarwar"K-Nearest Neighbours based diagnosis of hyperglycemia" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd7046.pdf http://www.ijtsrd.com/computer-science/artificial-intelligence/7046/k-nearest-neighbours-based-diagnosis-of-hyperglycemia/abid-sarwar
This presentation consist detail information about various data mining algorithm. In this presentation dataset of gladnular disorder has been used and performed operations on that using WEKA tool
Real-time Heart Pulse Monitoring Technique Using Wireless Sensor Network and ...IJECEIAES
Wireless Sensor Networks (WSNs) for healthcare have emerged in the recent years. Wireless technology has been developed and used widely for different medical fields. This technology provides healthcare services for patients, especially who suffer from chronic diseases. Services such as catering continuous medical monitoring and get rid of disturbance caused by the sensor of instruments. Sensors are connected to a patient by wires and become bed-bound that less from the mobility of the patient. In this paper, proposed a real-time heart pulse monitoring system via conducted an electronic circuit architecture to measure Heart Pulse (HP) for patients and display heart pulse measuring via smartphone and computer over the network in real-time settings. In HP measuring application standpoint, using sensor technology to observe heart pulse by bringing the fingerprint to the sensor via used Arduino microcontroller with Ethernet shield to connect heart pulse circuit to the internet and send results to the web server and receive it anywhere. The proposed system provided the usability by the user (userfriendly) not only by the specialist. Also, it offered speed andresults accuracy, the highest availability with the user on an ongoing basis, and few cost.
Heart Disease Prediction using Machine Learning Algorithmijtsrd
Nowadays, Heart disease has become dangerous to a human being, it effects very badly to human body. If anyone is suffering from heart disease, then it leads to blood clotting. Heart disease prediction is very difficult task to predict in the field of medical science. Affiliation has predicted that 12 million people fail horrendously every year as a result of heart disease. In this paper, we propose a k Nearest Neighbors Algorithm KNN way to deal with improve the exactness of heart determination. We show that k Nearest Neighbors Algorithm KNN have better accuracy than random forest algorithm for viewing heart disease. The k Nearest Neighbors Algorithm give more precise and exact outcome . We have taken 13 attributes in the dataset and a target attribute, by applying machine learning we achieved 84 accuracy in the heart disease detection. Ravi Kumar Singh | Dr. A Rengarajan "Heart Disease Prediction using Machine Learning Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38358.pdf Paper Url: https://www.ijtsrd.com/computer-science/other/38358/heart-disease-prediction-using-machine-learning-algorithm/ravi-kumar-singh
Linkage Detection of Features that Cause Stroke using Feyn Qlattice Machine L...PurwonoPurwono4
Stroke is a disease caused by brain tissue damage because of blockage in the
cerebrovascular system that disrupts body sensory and motoric systems
Stroke disease is one of the highest death cause in the world. Data collection
from Electronic Health Records (EHR) is increasing and has been included
in the health service big data. It can be processed and analyzed using machine
learning to determine the risk group of stroke disease. Machine learning can
be used as a predictor of stroke causes, while the predictor clarifies the
influence of each cause factor of the disease. Our contribution in this research
is to evaluate Feyn Qlattice machine learning models to detect the influence
of stroke disease's main cause features. We attempt to obtain a correlation
between features of the stroke disease, especially on the gender as a feature,
whether any other features can influence the gender feature. This research
utilizes 4908 data of the disease predictor using the Feyn Qlattice model. The
result implies that gender highly impacts age and hypertension on stroke
disease causes. Autorun in Feyn Qlattice model was run with ten epochs,
resulting in 17596 test models at 57s. Query string parameter that was focused
on age and hypertension features resulted in 1245 models at 4s. An increase
of accuracy was found in training metrics from 0.723 to 0.732 and in testing
metrics from 0.695 to 0.708. Evaluation results showed that the model is
reasonably good as a predictor of stroke disease, indicated with blue lines of
AUC in training and testing metrics close to ROC's left side peak curve.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Hci and its effective use in design and development of good user interfaceeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
An Experimental Study of Diabetes Disease Prediction System Using Classificat...IOSRjournaljce
Data mining means to the process of collecting, searching through, and analyzing a large amount of data in a database. Classification in one of the well-known data mining techniques for analyzing the performance of Naive Bayes, Random Forest, and Naïve Bayes tree (NB-Tree) classifier during the classification to improve precision, recall, f-measure, and accuracy. These three algorithms, of Naive Bayes, Random Forest, and NB-Tree are useful and efficient, has been tested in the medical dataset for diabetes disease and solving classification problem in data mining. In this paper, we compare the three different algorithms, and results indicate the Naive Bayes algorithms are able to achieve high accuracy rate along with minimum error rate when compared to other algorithms.
An Approach for Disease Data Classification Using Fuzzy Support Vector MachineIOSRJECE
: Data Mining has great scope in the field of medicine. In this article we introduced one new fuzzy approach for prediction of hepatitis disease. Many researchers have proposed the use of K-nearest neighbor (KNN) for diabetes disease prediction. Some have proposed a different approach by using K-means clustering for reprocessing and then using KNN for classification. In our approach Naive Bayes classifier is used to clean the data. Finally, the classification is done using Fuzzy SVM algorithm. Hepatitis diseases data set is used to test our method. We are able to obtain model more precise than any others available in the literature. The Fuzzy SVM approach produced better result than KNN with Fuzzy c-meansand Fuzzy KNN with Fuzzy c-means. Theintroduction of Fuzzy Support Vector Machine algorithm certainly has a positive effect on the outcome of hepatitis disease. This fuzzy SVM model led to remarkable increase in classification accuracy
Development of a Home-based Wrist Rehabilitation System IJECEIAES
There are several factors that may result to wrist injuries such as athlete injuries and stroke. Most of the patients are unable to undergo rehabilitation at healthcare providers due to cost and logistic constraint. To solve this problem, this project proposes a home-based wrist rehabilitation system. The goal is to create a wrist rehabilitation device that incorporates an interactive computer game so that patients can use it at home without assistance. The main structure of the device is developed using 3D printer. The device is connected to a computer, where the device provides exercises for the wrist, as the user completes a computer game which requires moving a ball to four target positions. Data from an InvenSense MPU-6050 accelerometer is used to measure wrist movements. The accelerometer values are read and used to control a mouse cursor for the computer game. The pattern of wrist movements can be recorded periodically and displayed back as sample run for analysis purposes. In this paper, the usefulness of the proposed system is demonstrated through preliminary experiment of a subject using the device to complete a wrist exercise task based on the developed computer game. The result shows the usefulness of the proposed system.
K-Nearest Neighbours based diagnosis of hyperglycemiaijtsrd
AI or artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction. As a result, Artificial Intelligence is gaining Importance in science and engineering fields. The use of Artificial Intelligence in medical diagnosis too is becoming increasingly common and has been used widely in the diagnosis of cancers, tumors, hepatitis, lung diseases, etc... The main aim of this paper is to build an Artificial Intelligent System that after analysis of certain parameters can predict that whether a person is diabetic or not. Diabetes is the name used to describe a metabolic condition of having higher than normal blood sugar levels. Diabetes is becoming increasingly more common throughout the world, due to increased obesity - which can lead to metabolic syndrome or pre-diabetes leading to higher incidences of type 2 diabetes. Authors have identified 10 parameters that play an important role in diabetes and prepared a rich database of training data which served as the backbone of the prediction algorithm. Keeping in view this training data authors developed a system that uses the artificial neural networks algorithm to serve the purpose. These are capable of predicting new observations (on specific variables) from previous observations (on the same or other variables) after executing a process of so-called learning from existing training data (Haykin 1998).The results indicate that the performance of KNN method when compared with the medical diagnosis system was found to be 91%. This system can be used to assist medical programs especially in geographically remote areas where expert human diagnosis not possible with an advantage of minimal expenses and faster results. Abid Sarwar"K-Nearest Neighbours based diagnosis of hyperglycemia" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd7046.pdf http://www.ijtsrd.com/computer-science/artificial-intelligence/7046/k-nearest-neighbours-based-diagnosis-of-hyperglycemia/abid-sarwar
This presentation consist detail information about various data mining algorithm. In this presentation dataset of gladnular disorder has been used and performed operations on that using WEKA tool
Real-time Heart Pulse Monitoring Technique Using Wireless Sensor Network and ...IJECEIAES
Wireless Sensor Networks (WSNs) for healthcare have emerged in the recent years. Wireless technology has been developed and used widely for different medical fields. This technology provides healthcare services for patients, especially who suffer from chronic diseases. Services such as catering continuous medical monitoring and get rid of disturbance caused by the sensor of instruments. Sensors are connected to a patient by wires and become bed-bound that less from the mobility of the patient. In this paper, proposed a real-time heart pulse monitoring system via conducted an electronic circuit architecture to measure Heart Pulse (HP) for patients and display heart pulse measuring via smartphone and computer over the network in real-time settings. In HP measuring application standpoint, using sensor technology to observe heart pulse by bringing the fingerprint to the sensor via used Arduino microcontroller with Ethernet shield to connect heart pulse circuit to the internet and send results to the web server and receive it anywhere. The proposed system provided the usability by the user (userfriendly) not only by the specialist. Also, it offered speed andresults accuracy, the highest availability with the user on an ongoing basis, and few cost.
Heart Disease Prediction using Machine Learning Algorithmijtsrd
Nowadays, Heart disease has become dangerous to a human being, it effects very badly to human body. If anyone is suffering from heart disease, then it leads to blood clotting. Heart disease prediction is very difficult task to predict in the field of medical science. Affiliation has predicted that 12 million people fail horrendously every year as a result of heart disease. In this paper, we propose a k Nearest Neighbors Algorithm KNN way to deal with improve the exactness of heart determination. We show that k Nearest Neighbors Algorithm KNN have better accuracy than random forest algorithm for viewing heart disease. The k Nearest Neighbors Algorithm give more precise and exact outcome . We have taken 13 attributes in the dataset and a target attribute, by applying machine learning we achieved 84 accuracy in the heart disease detection. Ravi Kumar Singh | Dr. A Rengarajan "Heart Disease Prediction using Machine Learning Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38358.pdf Paper Url: https://www.ijtsrd.com/computer-science/other/38358/heart-disease-prediction-using-machine-learning-algorithm/ravi-kumar-singh
Linkage Detection of Features that Cause Stroke using Feyn Qlattice Machine L...PurwonoPurwono4
Stroke is a disease caused by brain tissue damage because of blockage in the
cerebrovascular system that disrupts body sensory and motoric systems
Stroke disease is one of the highest death cause in the world. Data collection
from Electronic Health Records (EHR) is increasing and has been included
in the health service big data. It can be processed and analyzed using machine
learning to determine the risk group of stroke disease. Machine learning can
be used as a predictor of stroke causes, while the predictor clarifies the
influence of each cause factor of the disease. Our contribution in this research
is to evaluate Feyn Qlattice machine learning models to detect the influence
of stroke disease's main cause features. We attempt to obtain a correlation
between features of the stroke disease, especially on the gender as a feature,
whether any other features can influence the gender feature. This research
utilizes 4908 data of the disease predictor using the Feyn Qlattice model. The
result implies that gender highly impacts age and hypertension on stroke
disease causes. Autorun in Feyn Qlattice model was run with ten epochs,
resulting in 17596 test models at 57s. Query string parameter that was focused
on age and hypertension features resulted in 1245 models at 4s. An increase
of accuracy was found in training metrics from 0.723 to 0.732 and in testing
metrics from 0.695 to 0.708. Evaluation results showed that the model is
reasonably good as a predictor of stroke disease, indicated with blue lines of
AUC in training and testing metrics close to ROC's left side peak curve.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Hci and its effective use in design and development of good user interfaceeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Combined Defence Services Examination (II) - 2014Performance analysis of swcn...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Design and implementation of labview based scada for textile millseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Study of flooding based d do s attacks and their effect using deter testbedeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Building extraction from remote sensing imageries by data fusion techniqueseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Power quality improvement of grid interconnected distribution system using fs...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Aiding visually challenged individual for object detection and navigation usi...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Tiled bitmap algorithm and forensic analysis of data tampering (an evolutiona...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Nanoparticle based charge trapping memory device applying mos technology a co...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Internet of things based fall detection and heart rate monitoring system for...IJECEIAES
Falls cause the maximum number of injuries, deaths, and hospitalizations due to injury for senior citizens worldwide. So, fall detection is essential in the health care of senior citizens. Present methods lack either accuracy or comfortability. The design of fall detection and heart rate monitoring system for senior citizens has been presented in this paper. The hardware interface includes wearable monitoring devices based on a tri-axial accelerometer and Bluetooth module that makes a wireless connection by software interface (mobile application) to the caregiver. Global positioning system (GPS) can also track the location of the elder. For detecting falls accurately, an effective fall detection algorithm is developed and used. The performance parameters of the fall detection system are accuracy (97.6%), sensitivity (92.8%), and specificity (100%). A pulse sensor is used for monitoring the heart rate of the elder. The device is put on the hips to increase comfortability. Whenever the elder's fall is detected, the device can send information on fall data and heart rate with location to the respective caregiver successfully. So, this device can minimize the injury and health cost of a fallen person as a victim can get help within a short time.
An Enhanced & Effective Fall Detection System for Elderly Person Monitoring u...IJRES Journal
Various fall-detection solutions have been previously proposed to create a reliable surveillance system for elderly people with high requirements on accuracy, sensitivity and specificity. In this paper, an enhanced fall detection system is proposed for elderly person monitoring that is based on smart sensors worn on the body and operating through consumer home networks. With treble thresholds, accidental falls can be detected in the home healthcare environment. By utilizing information gathered from an accelerometer, cardiotachometer and smart sensors, the impacts of falls can be logged and distinguished from normal daily activities. The proposed system have to be analyzed in a prototype system as detailed in this paper. From a test group of 30 healthy participants, it was found that the proposed fall detection system can achieve a high detection accuracy of 97.5%, while the sensitivity and specificity are 96.8% and 98.1% respectively. Therefore, this system can reliably be developed and deployed into a consumer product for use as an elderly person monitoring device with high accuracy and a low false positive rate.
Fibrillation Detection using Accelerometer and Gyroscope of a Smartphoneijtsrd
Using the smartphone as an answer for the identification of Atrial Fibrillation (AFib), which uses the built-in accelerometer and gyroscope sensors (Inertial Measurement Unit, IMU) of the smartphone for detection? Contingent upon the patients circumstance, it is conceivable to utilize the created cell phone application either routinely or at times for making an estimation of the subject with no outer sensors is required. From that point forward, the application decides if the patient experiences AFib or not. Arun Pranav K. R | Elavarasan C"Fibrillation Detection using Accelerometer and Gyroscope of a Smartphone" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11074.pdf http://www.ijtsrd.com/computer-science/other/11074/fibrillation-detection-using-accelerometer-and-gyroscope-of-a-smartphone/arun-pranav-k-r
Zigbee based smart fall detection and notification system with wearable senso...eSAT Journals
Abstract Fall is one of the serious health issues among elderly population in Malaysia. In the event of a fall, a strong impact may be inflicted on the elderly causing severe injuries or even death. Another research by the National Institutes of Health found that 67% of elderly who fall and fail to seek help within 72 hours are unlikely to survive. Current Personal Emergency Respond System (PERS) often employs the use of a manual emergency button. However this approach may not be useful if the fall victim become unconscious or even not be able to move to reach the emergency button. In addition, such as this approach also requires more time and inadequate to notify and seek for immediate help. This paper attempts to design and implement a smart fall detection system for real time notification known as e-SAFE. This system will automatically detect a fall and notifies the incident instantly to internal and external correspondence. The e-SAFE equipped with a wearable accelerometer sensor, microcontroller, ZigBee transceiver module and Global System for Mobile communications (GSM) device. The in-house correspondence will be notifies though the ZigBee technology, meanwhile the external correspondence will be notified through GSM. Once a fall has been detected by e-SAFE system, a Short Message Service (SMS) and an E-mail will be sent to predefined contacts which is stored in the system. This system will provide a path toward independent living for the elderly while keeping them save. Index Terms: Emergency Respond, Wearable Accelerometer Sensor, ZigBee, GSM, SMS, E-mail.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
EdgeFall: a promising cloud-edge-end architecture for elderly fall careIJECEIAES
Elder citizens face sudden fall, which can lead to injuries of both destructive and non-virulent. These sudden falls are later more precarious than diseases like heart attack, blood sugar, blood pressure because these can be untreated for a lengthy time which can lead to death. Elder citizen who experiences a precipitous fall, carry out their communal life narrowed. Therefore, a shrewd and adequate anti-fallen system is required for aiding elderly health care, specifically to those who live individually. So, it can identify and anticipate a precipitous fall through appropriate human activity recognition. In this study, we have suggested an end-edge-cloud based wearable EdgeFall architecture for elderly care. We have performed simulation setups to clarify the query of why we need such a strategy, and its validity. We have achieved maximum 91.87% accuracy with 1.6% false alarm rate (FAR). These empirical results indicate the superiority of using tightly couple multiple information for recognizing human activity. We can accomplish a low FAR with an enhanced accuracy. We can observe that our proposed end-edge-cloud based architecture can reduce the execution time to millisecond range (ms) of 14.16 to 15.74. This work serves as the starting mark for future related research activities.
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Design and development of fall detector using fall
1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 09 | Sep-2013, Available @ http://www.ijret.org 57
DESIGN AND DEVELOPMENT OF FALL DETECTOR USING FALL
ACCELERATION
Sudarshan B G1
, Raveendra Hegde2
, Prasanna Kumar S C3
, Satyanarayana B S4
1
Assistant Professor, 3
Professor and Head, 4
Principal, Dept. of Instrumentation Technology, RVCE, Bangalore,
Karnataka, India,
sudharshanbg@gmail.com, prasannakumar@rvce.edu.in, principal@rvce.edu.in
Abstract
Fall of patients and aged people may become fatal if unnoticed in time. The concept is to have a fall detection system which sends
alarm to the concerned people or to the doctor, at the time of eventuality. To minimize fall and its related injuries continuous
surveillance of subjects who are diseased and prone to fall is necessary. The article discusses the design and development of a
prototype of an electronic gadget which is used to detect fall among elderly and the patients who are prone to it. In this article, the
body posture is derived from change of acceleration in three axes, which is measured using triaxial accelerometer (adxl335). The
sensor is placed on the lumbar region to study the tilt angle. The acceleration values in each axis are compared twice with threshold
and also a delay of 20 secs between two comparisons, to reduce the false alarms. Values of the threshold voltage are selected by
experimental methods. The algorithm is executed by microcontroller (PIC16F877A). The location of fall is determined by GPS
receiver, which is programmed to track the subject continuously. On detection of fall, the device sends a text message through GSM
modem, and communicates it to computer through ZigBee transceivers. The device can also be switched to only alarm if text message
is not required. The prototype developed is tested on many subjects and also on volunteers who simulated fall. Out of 50 trials 96% of
accuracy is achieved with zero false alarms for daily activities like jogging, skipping, walking on stairs, and picking up objects.
Index Terms: Fall Detector, Medical Alarming System, Personal Emergency Response System, triaxial accelerometer,
microcontroller
-----------------------------------------------------------------------***-----------------------------------------------------------------------
1. INTRODUCTION
Fall is a clinical feature of many diseases such as Parkinson’s
disease, ectopic of heart, vestibulocochlear defects etc. Falls
occur even at home and also in hospitals. Increase in number
of patients results in difficulties of manual monitoring by the
hospital staff, which leave the patients vulnerable to fall. With
the advent of modernization and western culture, the nuclear
families are on rise. This has led to single aged people living
alone with geriatric problems. Falls are usually fatal due to
head injuries and also because of not being treated in time.
Falls not only cause physical, but also psychological trauma.
People with history of fall are more prone to such attacks. The
falls result in sustained psychological effects such as fear,
increasing dependence [1]. Importance of preventing
complications of fall lies in early detection and prevention of
fall. According to survey done by Centres for Disease Control
and Prevention (CDC), 33% of aged people fall every year [2].
The old-age dependency ratio (the number of people 65 and
over relative to those between 15 and 64) is projected to
increase from value of 22% in 2010 to 37% by 2050 [3]. Fall
related injuries are not only social burden but also economic
aspect. Based on data from a survey done in US in the year
2000, total annual estimated costs were between $16 billion
and $19 billion for nonfatal fall-related injuries and
approximately $170 million dollars [4]. Fall-related death
rates in the United States increased between 1999 and 2004,
from 29 to 41 per 100,000 population [4]. In Indian population
such a statistics is not available. A low cost personal
emergency response system can also be used by fireman and
mountaineers who are at the risk of fall and its related injuries.
With the above mentioned factors such as medical and
economic issues, lies the importance in design and
development of a fall detector.
Efforts to detect fall among elderly is being done over several
years. Detailed literature review gives us four types of
approaches to detect fall, namely: wearable sensor, ambient
sensor, combination of wearable and ambient sensor and
image processing. The body wearable method is found
economical and suitable for both indoor and outdoor
scenarios. S.Y.Sim et al. [1] tried to place accelerometer in
shoe and experiments shown that the algorithm is sensitive
(81.5%) when the sensor is placed in tongue of shoe. Wen-
Chang Cheng et al. [5] used chest or waist worn triaxial
accelerometer to derive body posture. Cascade Ada-Boost
support vector machine is employed to classify fall from other
activities with high accuracy (more than 98%). A new
approach by placing the sensors on garment is done by Khalil
2. IJRET: International Journal of Research in Engineering and Technology
__________________________________________________________________________________________
Volume: 02 Issue: 09 | Sep-2013, Available @
Niazmand et al. [6]; it can be worn without any discomfort.
The algorithm achieved sensitivity of 97.5% and specificity of
96.92%. The combination of accelerometer and gyroscope is
placed on thigh and chest region and the algorithm employed
succeeded to give 92% accuracy [7]. A new algorithm was
proposed by Ravi Narasimhan [8]. Data is acquired by triaxial
accelerometer and threshold window is computed by
experimental values. The specificity of 100% and sensitivity
of 99% was achieved by placing the accelerometer on torso
and by applying algorithm. Many researchers worked to
develop fall detecting system using built
accelerometer of mobile phone. Frank Sposaro et al.[9]
developed an application for android phone. It asks the user to
communicate when a fall is detected, messages are sent to
social contacts if not replied. The emergency alarm is raised if
both fail. Yi He et al. [10] considered smart phone as a waist
worn device and developed an algorithm to
(multimedia message service) to pre-selected contacts and the
location is determined by GPS coordinate and Google map.
The proposed method in this article is to detect falls which
include only change of plane of human body due to various
reasons such as geriatric problems and its associated diseases
like Parkinson’s disease, ectopics of heart, vestibulocochlear
defects etc.Derived human body posture is compared to
predefined threshold values to separate fall from daily
activities. Repeated readings of sensor response for different
tilt angles give threshold values. Since, change of plane of
body and sudden changes in acceleration are involved in fall;
triaxial accelerometer is a suitable sensor. The changes of
acceleration in 3 axes are monitored continuously. False
alarms are reduced by deriving posture twice separated by 20
second delay.
The section 2 of the paper describes methodology to detect
fall. Selection of threshold voltage is discussed in section 3.
The suitable anatomical position to place the device is
explained in section 4. Results of experiments are given in
section 5. The paper is concluded in the section 6.
2. METHODOLOGY TO DETECT FALL
The technique of detecting fall relies on deriving human body
posture with a suitable sensor placed at appropriate anatomical
position and an effective algorithm which precisely distinguish
daily activities and fall. Since, change of plane of body and
sudden changes in acceleration are involved in fall; triaxial
accelerometer is a suitable sensor. The changes of acceleration
in 3 axes are monitored continuously. When the changes in
acceleration fall in the window of threshold v
decided as fall.
Research in Engineering and Technology eISSN: 2319
__________________________________________________________________________________________
2013, Available @ http://www.ijret.org
Niazmand et al. [6]; it can be worn without any discomfort.
The algorithm achieved sensitivity of 97.5% and specificity of
96.92%. The combination of accelerometer and gyroscope is
nd the algorithm employed
succeeded to give 92% accuracy [7]. A new algorithm was
proposed by Ravi Narasimhan [8]. Data is acquired by triaxial
accelerometer and threshold window is computed by
experimental values. The specificity of 100% and sensitivity
f 99% was achieved by placing the accelerometer on torso
and by applying algorithm. Many researchers worked to
develop fall detecting system using built-in tri-axial
accelerometer of mobile phone. Frank Sposaro et al.[9]
d phone. It asks the user to
communicate when a fall is detected, messages are sent to
social contacts if not replied. The emergency alarm is raised if
both fail. Yi He et al. [10] considered smart phone as a waist
worn device and developed an algorithm to send MMS
selected contacts and the
location is determined by GPS coordinate and Google map.
The proposed method in this article is to detect falls which
include only change of plane of human body due to various
such as geriatric problems and its associated diseases
like Parkinson’s disease, ectopics of heart, vestibulocochlear
defects etc.Derived human body posture is compared to
predefined threshold values to separate fall from daily
gs of sensor response for different
tilt angles give threshold values. Since, change of plane of
body and sudden changes in acceleration are involved in fall;
triaxial accelerometer is a suitable sensor. The changes of
continuously. False
alarms are reduced by deriving posture twice separated by 20
The section 2 of the paper describes methodology to detect
fall. Selection of threshold voltage is discussed in section 3.
lace the device is
explained in section 4. Results of experiments are given in
section 5. The paper is concluded in the section 6.
METHODOLOGY TO DETECT FALL
The technique of detecting fall relies on deriving human body
laced at appropriate anatomical
position and an effective algorithm which precisely distinguish
daily activities and fall. Since, change of plane of body and
sudden changes in acceleration are involved in fall; triaxial
The changes of acceleration
in 3 axes are monitored continuously. When the changes in
acceleration fall in the window of threshold values, it is
Fig -1: Block Diagram of fall detector
The block diagram (Fig
input, the controller, communication protocols and output
devices. The input consists of acceleration values and GPS
data. The transmitter pin of GPS is connected to the receiver
(UART) of microcontroller. Location data is read serially byte
by byte which gives the information of longitude and latitude.
The triaxial accelerometer sensor (adxl335) is used to derive
body posture of the subject. Acceleration and angle
information of three axes is produced as three analog signals
which vary with body posture. Acceleration value generated in
each axis is read through separate pins, selecting one analog
input at a time. Analog signals generated by the sensor are
digitized by analog to digital converter of the microcontroller
(PIC16F877A). The digitized v
predefined threshold values. Human body posture is derived
twice; between two posture readings a delay of 20 seconds is
introduced. The delay time helps to reduce false alarms.
ZigBee transceiver pair (Tarang F4) is used for
communication between the microcontroller and the computer
and indicators. An alert message is sent to a hospital phone
number when a fall is detected. The GSM modem used is SIM
300 V_7.03. ZigBee transceiver and GSM modem are
connected to RS232 port of mi
switch. The system can be switched send either SMS alert or
just a ZigBee alert to the indicators (LED and beeper). This
facility avoids sending unnecessary SMS while patient i
home with family members.
The microcontroller board, the ZigBee transceiver and the
GSM modem are powered up by a single DC source of 12V,
2A. The sensor board and GPS device use 5V generated by
built in voltage regulator of microcontroller board
eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
58
Block Diagram of fall detector
Fig -1) possesses four main sections,
input, the controller, communication protocols and output
devices. The input consists of acceleration values and GPS
data. The transmitter pin of GPS is connected to the receiver
(UART) of microcontroller. Location data is read serially byte
yte which gives the information of longitude and latitude.
The triaxial accelerometer sensor (adxl335) is used to derive
body posture of the subject. Acceleration and angle
information of three axes is produced as three analog signals
posture. Acceleration value generated in
each axis is read through separate pins, selecting one analog
input at a time. Analog signals generated by the sensor are
digitized by analog to digital converter of the microcontroller
(PIC16F877A). The digitized values are compared to
predefined threshold values. Human body posture is derived
twice; between two posture readings a delay of 20 seconds is
introduced. The delay time helps to reduce false alarms.
ZigBee transceiver pair (Tarang F4) is used for
communication between the microcontroller and the computer
and indicators. An alert message is sent to a hospital phone
number when a fall is detected. The GSM modem used is SIM
300 V_7.03. ZigBee transceiver and GSM modem are
connected to RS232 port of microcontroller board via a
switch. The system can be switched send either SMS alert or
just a ZigBee alert to the indicators (LED and beeper). This
facility avoids sending unnecessary SMS while patient is at
home with family members.
oard, the ZigBee transceiver and the
GSM modem are powered up by a single DC source of 12V,
2A. The sensor board and GPS device use 5V generated by
built in voltage regulator of microcontroller board.
3. IJRET: International Journal of Research in Engineering and Technology
__________________________________________________________________________________________
Volume: 02 Issue: 09 | Sep-2013, Available @
2.1 Flow Chart for the Algorithm
The Fig -2 depicts the detailed flow of program. The
microcontroller is programmed to monitor and track the
subject continuously. The initialization part includes
configuring analog to digital converter and Universal
Asynchronous Synchronous Receiver Transmitter (UART).
To remove false alarms induced by fall like activities the
acceleration values are measured and compared two times.
Between two measurements and comparisons, a delay
seconds is introduced. The flow chart shows two modes of
operation, mode1: send text message to pre
numbers, mode2: send only alarming signal to the indicators.
Mode 2 is used when the patient is alone and the device is
switched to mode 1 when family members are around.
Fig -2: Flow chart for implemented algorithm
Research in Engineering and Technology eISSN: 2319
__________________________________________________________________________________________
2013, Available @ http://www.ijret.org
the detailed flow of program. The
microcontroller is programmed to monitor and track the
initialization part includes
configuring analog to digital converter and Universal
Asynchronous Synchronous Receiver Transmitter (UART).
emove false alarms induced by fall like activities the
acceleration values are measured and compared two times.
Between two measurements and comparisons, a delay of 20
The flow chart shows two modes of
sage to pre-stored phone
numbers, mode2: send only alarming signal to the indicators.
Mode 2 is used when the patient is alone and the device is
switched to mode 1 when family members are around.
Flow chart for implemented algorithm
2.2 Algorithm
Step1. Initialize serial communication ports of microcontroller
Step2. Configure ADC and analog input channel
Step3. Initialize GPS and GSM modules.
Step4. Receive analog inputs from sensor.
Step5. Receive location information from GPS.
Step6. Compare the digital values of sensor signal with
predefined thresholds. If acceleration is greater than the
threshold go to step7, else go to step4.
Step7. Wait for time t and again read acceleration values.
Compare with same threshold again.
Step8. Is fall detected? If yes go to step9, go to step4 if not.
Step9. Send text message to stored numbers, send alarming
signal to indicators if the operating mode1. Send only
alarming signals to the indicators if mode2
3. SELECTION OF THRESHOLD VOLTAGE
The threshold voltage is selected by readings of sensor
responses for different tilted positions.
outputs for different fall scenarios. It is observed that for
different types of falls.
Fig -3: Readings of triaxial accelerometer
eISSN: 2319-1163 | pISSN: 2321-7308
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59
Step1. Initialize serial communication ports of microcontroller
Step2. Configure ADC and analog input channel
Step3. Initialize GPS and GSM modules.
Step4. Receive analog inputs from sensor.
Step5. Receive location information from GPS.
Step6. Compare the digital values of sensor signal with
predefined thresholds. If acceleration is greater than the
threshold go to step7, else go to step4.
Step7. Wait for time t and again read acceleration values.
Compare with same threshold again.
tep8. Is fall detected? If yes go to step9, go to step4 if not.
Step9. Send text message to stored numbers, send alarming
signal to indicators if the operating mode1. Send only
alarming signals to the indicators if mode2.
3. SELECTION OF THRESHOLD VOLTAGE
The threshold voltage is selected by readings of sensor
responses for different tilted positions. Fig -3 shows sensor
outputs for different fall scenarios. It is observed that for
Readings of triaxial accelerometer
4. IJRET: International Journal of Research in Engineering and Technology
__________________________________________________________________________________________
Volume: 02 Issue: 09 | Sep-2013, Available @
Backward fall is indicated by Z axis, forward and right side
fall is indicated by Y axis values, and Z axis indicates left side
fall. From the observation of sensor responses, 1.96V, 1.63V,
1.98V are considered as threshold values for X, Y, Z axes
respectively.
4. PLACEMENT OF THE DEVICE ON HUMAN
BODY
Anatomical position of the device influences the accuracy and
specificity to a great extent. If the detection algorithm depends
mainly on the body posture and tilt, then torso is more suitable
place [11]. Stefano Abbate et al. [11] listed different possible
anatomical positions to derive various postures (table 1).
Table -1: Different positions of sensor corresponding derived
posture
Sensor position Identified posture
Chest (standing or sitting), (bending or lying)
Waist (bending or standing or sitting), (lying)
Chest + Thigh bending, lying, standing, sitting
Since algorithm of the project depends on thresholds of tilt, it
is suitable to select waist portion to place the device. If the
device is placed just below stomach, obesity of the subject
may induce some tilt. To avoid this, lumbar vertebrae is
appropriate position to place the device as shown in the
Fig -4: Placement of the device.
Research in Engineering and Technology eISSN: 2319
__________________________________________________________________________________________
2013, Available @ http://www.ijret.org
Backward fall is indicated by Z axis, forward and right side
fall is indicated by Y axis values, and Z axis indicates left side
fall. From the observation of sensor responses, 1.96V, 1.63V,
1.98V are considered as threshold values for X, Y, Z axes
OF THE DEVICE ON HUMAN
Anatomical position of the device influences the accuracy and
specificity to a great extent. If the detection algorithm depends
mainly on the body posture and tilt, then torso is more suitable
Stefano Abbate et al. [11] listed different possible
anatomical positions to derive various postures (table 1).
Different positions of sensor corresponding derived
(bending or lying)
(bending or standing or sitting), (lying)
bending, lying, standing, sitting
Since algorithm of the project depends on thresholds of tilt, it
is suitable to select waist portion to place the device. If the
device is placed just below stomach, obesity of the subject
may induce some tilt. To avoid this, lumbar vertebrae is
e position to place the device as shown in the Fig -4.
Placement of the device.
5. RESULTS AND DISCUSSIONS
The components are enclosed in a plastic box and tied in the
waist region as shown in
five volunteers (healthy adult males) in the PG research lab
and RVCE health center. Each subject is made to fall on bench
and bed, and many fall like activities (skipping, jogging,
picking objects from the floor and walking on staircase). The
following figure shows one of the subjects simulating fall.
Fig -5: One of the volunteers simulating fall
Out of fifty trials (ten trials each subject) only two events are
not detected. The trials included forward fall, falling sideways
and backward fall. The missed
subjects knelt down slowly and leaned forward without giving
any jerk. Since most of the falls not likely to happen this way,
the missed detections do not have significance. The fall
simulating activities like jogging, skipping,
and picking objects did not create any false alarms. The
outcome of the experiments is listed in the table 2. As we see
from the table the accuracy is 96%.
Table -2: Analysis of prototype testing
Subject
Number of
trials
1 10
2 10
3 10
4 10
5 10
The snapshots of assembly of components are shown in the
Fig -6.
eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
60
5. RESULTS AND DISCUSSIONS
The components are enclosed in a plastic box and tied in the
waist region as shown in Fig -5. The prototype is tested on
volunteers (healthy adult males) in the PG research lab
and RVCE health center. Each subject is made to fall on bench
and bed, and many fall like activities (skipping, jogging,
picking objects from the floor and walking on staircase). The
shows one of the subjects simulating fall.
of the volunteers simulating fall
Out of fifty trials (ten trials each subject) only two events are
not detected. The trials included forward fall, falling sideways
and backward fall. The missed detection happened when the
subjects knelt down slowly and leaned forward without giving
any jerk. Since most of the falls not likely to happen this way,
the missed detections do not have significance. The fall
simulating activities like jogging, skipping, walking on stairs
and picking objects did not create any false alarms. The
outcome of the experiments is listed in the table 2. As we see
from the table the accuracy is 96%.
Analysis of prototype testing
Number of
detections
Number of
false alarms
9 0
10 0
10 0
9 0
10 0
The snapshots of assembly of components are shown in the
5. IJRET: International Journal of Research in Engineering and Technology
__________________________________________________________________________________________
Volume: 02 Issue: 09 | Sep-2013, Available @
Fig-6: Assembly of components
CONCLUSIONS
In this research paper, we had achieved our primary goal
creating a working prototype able to recognize both dangerous
posture and falls from non-falls, with wireless communication
to the indicators and computer. Looking at the underlying
detection process, our fall detection system improves on
previous systems and designs by giving zero false alarms,
bearing low cost, and with new anatomical position for the
sensor. We incorporated hybrid fall detection algorithm
derived from existing algorithms, and interfaced the GPS
receiver successfully to locate fall. The accuracy is 96%.
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Research in Engineering and Technology eISSN: 2319
__________________________________________________________________________________________
2013, Available @ http://www.ijret.org
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