T-Space at The University of Toronto Libraries >
School of Graduate Studies - Theses >
Please use this identifier to cite or link to this item:
|Title: ||Cough Detection and Forecasting for Radiation Treatment of Lung Cancer|
|Authors: ||Qiu, Zigang Jimmy|
|Advisor: ||Kwong, Raymond H.|
|Department: ||Electrical and Computer Engineering|
|Keywords: ||cough detection|
gaussian mixture model
|Issue Date: ||6-Apr-2010|
|Abstract: ||In radiation therapy, a treatment plan is designed to make the delivery of radiation to a target more accurate, effective, and less damaging to surrounding healthy tissues. In lung sites, the tumor is affected by the patient’s respiratory motion. Despite tumor motion, current practice still uses a static delivery plan. Unexpected changes due to coughs and sneezes are not taken into account and as a result, the tumor is not treated accurately and healthy tissues are damaged.
In this thesis we detail a framework of using an accelerometer device to detect and forecast coughs. The accelerometer measurements are modeled as a ARMA process to make forecasts. We draw from studies in cough physiology and use amplitudes and durations of the forecasted breathing cycles as features to estimate parameters of Gaussian Mixture Models for cough and normal breathing classes. The system was tested on 10 volunteers, where each data set consisted of one 3-5 minute accelerometer measurements to train the system, and two 1-3 minute accelerometer measurements for testing.|
|Appears in Collections:||Master|
The Edward S. Rogers Sr. Department of Electrical & Computer Engineering - Master theses
This item is licensed under a Creative Commons License
Items in T-Space are protected by copyright, with all rights reserved, unless otherwise indicated.