Research Papers - Dept of Information Technology

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/593

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Has files: YesSubject: search.filters.subject.Mobile Application

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    Mobile Application for Mental Health Using Machine Learning
    (IEEE, 2022-12-09) Mendis, E.S; Kasthuriarachchi, L.W; Samarasinha, H.P.K.L; Kasthuriarachchi, S; Rajapaksa, S
    In present era, mental health has become one of the most neglected, yet critically important, factors of our overall well-being. A large number of people are affected by various types of mental illnesses and mental health disorders. Stress, anxiety, and depression are the most common disorders among children and adolescents in Sri Lanka, and their prevalence has increased over the years, likely to require immediate medical attention. In today’s world, mobile phones and applications play an important role in everyone’s life. With the rapid growth of mental illness, mental health-focused apps and websites have gradually increased globally in recent years. This study aims to develop a mobile application that will primarily serve Sri Lankans with mental health problems, helping them identify their levels of stress, anxiety, and depression (ADS) and receiving advice on how to deal with them. This app’s main objective is to support those who are dealing with mental illnesses and raise awareness of them locally using machine learning and image processing techniques. It does this by serving as a constant reminder of how crucial mental health is and how much of an impact it has on daily life. The GSE Scale, DASS 21 scale has been used to find the users’ mental health illness and the severity of each mental health illness such and Anxiety depression and stress. These methods are put to our mobile application using machine learning techniques such as Decision tree and Random Forest classifiers and uses image processing technologies, CNN machine learning algorithm to offer a variety of activities for reliving stress, depression, and anxiety,
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    A Mobile Application to Predict and Manage High Blood Pressure and Personalized Recommendations
    (IEEE, 2019-12-05) Rajapaksha, S. K; Abhayarathne, W. J. A; Kumari, S. G. K; De Silva, M. V. L. U; Wijesuriya, W. M. S. M
    The purpose of this investigation is to present a mobile application using AI expert and how to predict and manage high blood pressure and provide personalized recommendations to lower it. Basically, the system interprets the inadequate and inappropriate intake of food is known to cause various health issues and diseases. Due to the diversity of food components and a large number of dietary sources, it is challenging to perform a real-time selection of diet patterns that must fulfill one's nutrition needs and with considering your health issues and diseases. In this research, to address this issue to present an android based system, called Smart Blood Pressure Recommendation app. The purpose of this system is to allow patients to have an easy way to monitor their health and to see how their blood pressure has changed over time. This offer advice or suggestions, without having to schedule an appointment. As the system continues to gather data from a patient, it begins to offer advice its own if it finds that the patient's current conditions fit a certain condition or pattern. To generate a recommendation, it refers to an Ontology based data model. The data model gains information about its knowledge by doctors and nutritionists that can be used by AI expert. This research helps users to identify their previous record charts of blood pressure, reliable alarms for user blood pressure medication, popup notifications, build health diary and also share log data processing through the AI expert.