Applying Machine Learning Techniques to Categorize and Reduce Stress in Human Beings

The number of individuals in the modernworld experience elevated stress level, which is non-specific response on the body and plays a significant toll on health, productivity at work, relationships and also effect overall well-being. Many individuals are not aware of the stress triggers and potential health problems caused by prolonged stress. In order to effectively combat stress and its ill effects on health, stress triggers and responses to stress must be recognized and managed in real time. In this paper, applications of machine learning techniques are suggested to categorize and reduce stress is explored. The idea of monitoring stress and reducingstress usesmethods like personalized music, wallpaper themes, favorite games or favorite food ordering and so on. Activities which reduce stress and their degree of reduction are monitored in real time and based on customized stress reduction portfolio is designed using machine learning algorithms

A mobile application to assist Non - Governmental Organizations (NGOs) in effective mornitoring and evaluation of projects in Kenya

Thesis Submitted in partial fulfillment of the requirements for the Degree of Science in Mobile Telecommunication and Innovation (MSc. MTI) at Strathmore UniversityNon-Governmental Organisations (NGOs) are constantly in the process of reviewing ways in which monitoring and evaluation can achieve greater consistency and effectiveness in judging the impact of a project as well as getting recommendations on how future interventions can be improved. Developing a reporting, monitoring and evaluation system is therefore a requirement due to the growing pressure for improving performance. This is also one of the requirements by the NGOs and donors to check on the effective use of the donor funds, impact and benefits brought by the projects. This dissertation seeks to examine the challenges faced by Kenyan community based NGOs, in tracking the performance of projects. It also establishes the extent to which technology is used in reporting, monitoring and evaluation of projects by NGOs. The design, development and testing of the functionalities in the capacity building mobile application to assist NGOs in effective reporting, monitoring and evaluation of projects is presented. The target population for this dissertation was 10 NGOs in Kenya who are well established. Purposive and snowball sampling was used to select a sample of 30 respondents from the 10 NGOs selected. Data was collected using face to face and phone interviews and analysed using cross case analysis to facilitate the development of capacity building mobile application. The study adopted feature driven development methodology for system modelling and development. This model describes specific, short phases of tasks which are accomplished separately. A mobile and web application was developed to assist NGOs in reporting, monitoring an evaluation of projects. The final prototype was tested to check if the requirements were met. Testing and validation was also conducted by both the developer and potential users of the application to ensure the code developed was workable

Android Based Health Monitoring

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A REVIEW PAPER ON PATIENT MONITORING SYSTEM

This paper presents the various development that has taken place in the field of patient monitoring system over the years . The paper describes the implementation of the system by using smart bio-sensors to detect and record the human physiological characteristics and interfacing these data to a computer with the system using wireless protocols to alarm the doctors about the health condition of the patient. The combination of these technologies will improve the quality of health care by making it more efficient and reducing costs and medical error

Correlation analysis of vital signs to monitor disease risks in ubiquitous healthcare system

Healthcare systems for chronic diseases demand continuous monitoring of physiological parameters or vital signs of the patients’ body. Through these vital signs’ information, healthcare experts attempt to diagnose the behavior of a disease. Identifying the relationship between these vital signs is still a big question for the research community. We have proposed a sophisticated way to identify the affiliations between vital signs of three specific diseases i.e., Sepsis, Sleep Apnea, and Intradialytic Hypotension (IDH) through Pearson statistical correlation analysis. Vital signs data of about 32 patients were taken for analysis. Experimental results show significant affiliations of vital signs of Sepsis and IDH with average correlation coefficient of 0.9 and 0.58, respectively. The stability of the mentioned correlation is about 75% and 90%, respectively

Design of Emergency Communication and Alerting System for High Risk Workers

Emergency Management System (EMS) is a system that communicates and alert for emergency medical care. Once it is activated by an incident that causes serious illness or injury to human workers. High Risk workers emergency communication system is equipment which is used for response on any emergency, the worker can alert the Rescuing people, and it will continuously monitor the workers blood pressure and Heart beat rate .If any violation occurs it will be observed by the equipment and it will alert the responsible persons by alarm and Emergency Messages. Using GSM modem, pressure sensor and Heartbeat sensor the equipment can observe the real-time health monitoring of the high risk workers. According to the alerting system we can shoot the first aid and control the accident severity rate. Thus, the proposed system makes the human’s life at workplace easier and more comfortable

Context Aware Mobile Application Architecture (CAMAA) for Health Care systems : standardization and abstraction of context aware layers

Context awareness was introduced recently in several fields in quotidian human activities. Among context aware applications, health care systems are the most important ones. Such applications, in order to perceive the context, rely on sensors which maybe physical or virtual. However, these applications lack of standardization in handling the context and the perceived sensors data. In this work, we propose a formal context aware application architecture model to deal with the context taking into account the scalability and interoperability as key features towards an abstraction of the context relatively to end user applications. As a proof of concept, we present also a case study and simulation explaining the operational aspect of this architecture in health care systems