Interactive web based event management

Abstract

Aging population is an issue around the world currently and it is estimated that the proportion of elderly will increase rapidly in next few decades. Similarly, it was found that the number of people with Parkinson’s Disease (PD) will also increase, and may double in amount in 2030 as compared to 2005. This is a concern for the society, as portrayed by an increase in funding for research in both aging and PD. This project aims to develop a Web-based PD monitoring system for physiologists, doctors or nurses to monitor the PD patients’ progress on rehabilitation, or any further degradation of parkinsonism through detection of the motor symptoms in wellness games. PD is a progressive disorder that affects the motor system. Motor symptoms such as rest tremors are indicators of PD and can be detected through analyzing the coordinates data of the movements. A past experiment had used Kinect for detecting tremors. However, there is a limitation in the experiment where noise and background jittering had been detected as tremors or small movements. This project will address the limitation by recommending a model which filters away the noises and background jittering. Hence, this project proposes a Rest Tremor Detection Model, which takes into account the characteristics of rest tremors, and utilizes some mathematical methods such as autocorrelation to determine the occurrences of tremor and eliminate jittering. A Web Platform is designed and implemented to display patient’s profile, replay actions in gameplay, as well as incorporating the model to show the occurrences of rest tremors in gameplay. Through a focus group study conducted, the action replay feature was found to be useful as a tool for comparison to gauge the progression of PD in patients. Quantitative assessment can be done to examine the effectiveness of the system, and additional model for detecting other motor symptoms can be created and integrated to improve the proposed system’s capability.