dc.contributor.authorXu, Minghan
dc.date.accessioned2015-05-29T02:47:05Z
dc.date.available2015-05-29T02:47:05Z
dc.date.copyright2015en_US
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/10356/64646
dc.description.abstractPersonal well-being is the comprehensive integration of mental state and physical health. Its conventional methods of measurement rely on survey and questionnaire that are ineffective and challenging for long-term monitoring. The usual approach is to examine the components of well-being separately and integrated intelligence is sometimes missing. As an interdisciplinary subject, its advancement can leverage on the development of sensing technology. By replacing the paper-based evaluation questionnaire, a real-time tracking system that integrates personal physical activity and environmental quality was proposed in this project. Hence the evaluation of personal well-being stretches from single dimension, which is the fitness aspect, to multidimensions that combine both fitness and environmental factors. The objective of this project is to research, suggest and prototype a system that not only provides tracking service to some of the key areas of personal well-being, but also helps users understand themselves and their interaction with the surrounding environment. Extensive and crossdisciplinary literature studies have been conducted to understand the movement tracking mechanism, established well-being benchmark, recommended physical activity level and suggested environmental indices. A solution was proposed from the research outcomes and a prototype was assembled, tested and evaluated. At the end of this project, future research areas have been identified to provide directions for the next batch of researchers or students who continue working on this project.en_US
dc.format.extent90 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleMethodologies for personalized well-being assessment system using multi-modal sensorsen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorZhong Wende (EEE)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeELECTRICAL and ELECTRONIC ENGINEERINGen_US
dc.contributor.organizationInstitute of Infocomm Research (I2R)en_US


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