Developing reminder application based on prospective memory influencers

• Main Author: Tan, Valerie Ying Qi
• Other Authors: Miao Chun Yan
• Format: Final Year Project
• Language: English
• Published: 2015
• Subjects: DRNTU::Engineering::Computer science and engineering::Computer applications::Social and behavioral sciences; DRNTU::Social sciences::Psychology::Consciousness and cognition
• Online Access: http://hdl.handle.net/10356/62677
• Institution: Nanyang Technological University

This final year project aims to develop an Android mobile phone application that provides reminders at the right time to users. The three main concerns are 1. how many reminders should be given for a task, 2. how should the reminder be delivered, and when the reminder should be fired. To address the above concerns, this report includes review on several research papers that studied how various factors influence prospective memory task performance (remembering to perform a task in the future). A computational model is then built based on the review done to give a prediction on how well one will perform for the prospective memory task. This prediction is then used to determine how many times and when the reminders are fired. To address how reminder should be fired, the environment where the user is at, based on preset recording of one’s weekly routine, is used to determine if there should be an audio tone for the notification. The computational model uses the Fuzzy Cognitive Map as a basis, and many values are arbitrarily determined. The purpose of having the computational model is for future user studies and research, from which the concept and weight values in the fuzzy cognitive map can be determined more accurately. This report also includes key processes involving the use of the mobile application, some screenshots are added to provide examples of how the application can be used. Recommendations for future improvements to this research and application is also elaborated towards the end of the report.