The primary purpose of this study is to develop Heart Beat, a mobile assistant that aims to reveal to the user a possible heart attack or stroke risk within ten years. This paper outlines the analysis, design, and development of Heart Beat, including a brief description of the different functionalities and user interfaces. Heart Beat uses risk factors, which include some demographics data, laboratory results, lifestyle information, and medical history, to forecast a possible cardiovascular disease (CVD). This application is a response to the World Heart Federation’s recommendation of developing a CVD detector in order to enable more timely diagnosis. The application covers two diseases only: heart attack and stroke. Basically, it promotes CVD awareness and lifestyle enhancement through the risk factor assessment and the activities recommendation features, respectively. In addition, gamification elements such as coins and rewards were integrated into the application to ensure user engagement. In terms of software quality, Heart Beat achieved a 90% operability, 93% learnability, 90% consistency, 100% completeness, and 100% assurance scores.
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