Dr. R. Vajubunnisa Begum

EDUCATION

BE ECE, M. E (EEE)
PGDCA, MCA, Ph.D.

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Computer Science, Artificial Intelligence, Computer Science Applications

Scopus Publications

A Comparative Study on Performance Measures of Smart Monitoring System
R. Vajubunnisa Begum, K. Sushita, H. Jasmin, and N. Shanmugasundaram
IEEE
The Intelligent techniques are required to track patients' physiological data remotely and effectively. Individuals who are at high risk after surgery require a high degree of care. The primary goal is to assess a research model that employs a machine learning technique and deep learning algorithm to investigate clinical data using a Convolutional Neural Network Model. It is constructed in three sections. The goal of the ssytem is to provide a full monitoring and analysis platform powered by the MATLAB IDE that can be used to build patient observing systems all in one place. The current technique of checking patients in hospitals binds them to their beds and may be uncomfortable for patients to wear. The designed framework incorporates integrated sensors such as a skin temperature sensor.


Integrated Platform for Patient Abnormality Detection through GEM enabled Deep Transnet
R. Vajubunnisa Begum and K. Dharmarajan
IEEE
A patient monitoring system is necessary to monitor patient data remotely and precisely, at all times. It is necessary to give a high degree of care to individuals who are at high risk following post-surgical situations. Recent patient monitoring systems are being used for further diagnostic analyses and treatments that are open sourced and might benefit people all around the world. The system's goal is to provide a comprehensive monitoring and analysis platform that provides a one-stop solution for patient monitoring systems. The major goal is to develop a model utilizing Gaussian Expectation Maximization (GEM) enabled Deep Transnet (GEDT) algorithm, for effective detection of patient abnormality. Various physiological parameters are considered for analysis. The data acquired for ECG analysis is compared to the MIT BIH dataset from Physio Net. The standard values for heart rate, temperature, pressure, and oxygen saturation are used. Real-time testing is suggested, with volunteers helping to evaluate the gear. Only a subset of real-time values is used to collect training data. 70% are utilized for training, 15% for testing, and 15% for validation.


POSTGRESQL based monitoring and controlling the parameters for patients
A. Arunraja, R.Vajubunnisa Begum, Chandra Kumar Dixit, and Binny. S
IEEE
Generally, due to pandemic it is extremely difficult to consult with doctors and nurses. The availability of physicians at hospitals is extremely challenging; this is not a concern for patients; rather, the needs of patients must be monitored. In the event of illness monitoring, it is necessary to regulate and provide medications in accordance with the regular consult. In the suggested work, a web application must be developed. The developed web application is used to find the symptoms and the need to express their symptoms and difficult issues. Web applications process their symptoms issues and check their symptoms that have the values given to user. It also checks the temperature rate and heartbeat rate in real time by using the hardware implementation in Arduino and checks whether it is normal. It will provide a facility for all the patients to get appointment through this site. The doctor interface is planned to develop thereby it will maintain which doctor is available and which doctor not. It will reveal all the personal information of physicians, such as their addresses, phone numbers, specializations, and qualifications. All parametric values are read and it feedback the values with high accuracy to everyone, and the values are error-free, with a focus on accuracy. The values and parametric reading will be sent to patients for their satisfaction


Cloud-Scope: A Modern Patient Monitoring and Analysis System
R. Vajubunnisa Begum and K. Dharmarajan
IEEE
The current technique for checking patients in hospitals keeps patients attached to their beds and can be awkward for patients to wear. The quantity of medical caretakers in the labour force is additionally expected to decrease by 2020, causing strain in a climate where overabundance pressure can prompt stress mishaps happening to patients. The objective of this project was to deliver a remote patient monitoring and future analysis framework that could permit patients to be versatile in their current circumstance. The created framework incorporates a heartbeat oximeter to gauge blood oxygen fixation and the patient's heartbeat, just as a temperature sensor to monitor the patient's temperature. Other physiological boundaries, for example, internal heat level, breath rate, and anomalous heart beat through Heart rate sensor and so forth these physiological boundaries are level changed over and communicated through UART directly fetched to the cloud. The objective of the proposed module is to screen the boundaries adequately through Thing Speak IOT platform and dependent on basic qualities, the ready framework is created to give alert on crisis conditions. The patient monitoring system designed here not only used for monitoring purpose also developed a software module to control the limitations and data collected from the patients are further fetched to analyse the critical happenings based on the pattern of abnormality.

RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

PATENT PUBLICATION:
Title: CLOUD-SCOPE: A MODERN PATIENT MONITORING AND ANALYSIS
SYSTEM, APPLICATION NO. 202241033667, Filed Date: 13/062022,
Published Date:17/06/2022.