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Title: Predicting health conditions with palm prints
Authors: Kwek, Jerome Jia Long
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
Issue Date: 2014
Abstract: Since ancient times, palmistry, or the study of the palm (and its prints), has been used in various ways and different fields, such as fortune telling, predicting into the future, and characterization in criminology. More interestingly, in recent years, prediction of illnesses in medical psychiatry has been discovered in modern-day palmistry, that various medical problems could be diagnosed based on different palm line formations. To some, palm reading may be just a mere superstition and treated as more of a curiosity, while to others, it can be a very different outlook of looking into one’s fortune, wealth and personal well-being. This is commonly seen in the Western versus Eastern culture. This project tries to understand the practice of palm reading in the traditional manner, as well as putting it into practice virtually through various approaches. The 2 (two) chosen health conditions that this project will be focusing on would be schizophrenia and intellectual disability. Several experiments with regards to research for this project were conducted with a palm print database collected Hong Kong Polytechnic University, Hong Kong. This is a research project which aims to analyse the chosen health conditions based on the available palm print database, and how they can be used in a real-world implementation. Based on the results of the analysis, a proof of concept application will be developed to predict the possibility (based on an input palm print image) of suffering from either of the health conditions. This report intents to provide the research process, analysis and findings as well as to serve as a development guide for future developers working on the continuation of this project.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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