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Title:	Respiration rate measurement using laser displacement sensor and empirical mode decomposition
Authors:	Elham Sadat Yahyavi (P55843)
Supervisor:	Mohd Alauddin Mohd Ali, Professor. Dr
Keywords:	sensor and empirical
Issue Date:	31-Mar-2014
Description:	In emergency departments, triage acts as a small window for acquiring the status of the patients. The main vital signs that are usually used to assess the patients are respiratory rate (RR), heart rate (HR), blood pressure (BP), temperature, saturated oxygen (SpO2) and pain score. The respiration rate measurement in emergency departments using conventional devices is inconvenient. These devices are required to be attached to the patient which will induce artificial measurements (self-awareness stress effects) and time-consuming. The physician obtains the respiration rate by visually counting the number of times the chest moves in a minute. Multiple studies have shown manual method is unreliable in acute care setting, especially on the general care floor. Furthermore, this may sometimes cause inconvenience for female patients. The main objective of this project is to design and develop a robust algorithm to extract the respiration rate from contactless optical signals using laser displacement sensor.Thirty two healthy subjects (19 males, 13 females) aged between 24 to 55 years old were participated in this study. A laser displacement sensor was used to detect the subject’s chest wall displacement due to respiration. The patients were asked to talk, cough and move their hand to simulate the motion artifacts. In this research, digital signal processing and data analysis have been done using Matlab (The Mathworks, Inc). Two methods were used to extract the respiration rate from the contactless optical signal namely band pass filter (BPF) and empirical mode decomposition (EMD). The reference in this study was the contact respiration rate measurement using respiration effort sensor (g.tec Medical Engineering GmbH). Data analysis showed that EMD is the best method to extract respiration rate from contactless optical signal with a correlation coefficient of 0.97 compared to BPF method which has correlation coefficient of 0.78. Then, an algorithm to derive a continuous respiration rate from contactless optical signal was developed. The effect of motion artifacts to the contactless optical signal derived respiration rate was also investigated. As a result, optical contactless respiration rate using EMD during hand movement has minimum error (RMSE) of 0.28 with correlation coefficient of 0.94 compared to contact respiration rate measurement. Furthermore, correlation analysis also showed that the maximum error (RMSE=0.56) of contactless method is during coughing (correlation coefficient of 0.88). Finally, a device and algorithm have been developed which provides respiratory information of clinical significance from chest wall movement using contactless laser displacement sensor.,Master/Sarjana
Pages:	102
Publisher:	UKM, Bangi
Appears in Collections:	Faculty of Engineering and Built Environment / Fakulti Kejuruteraan dan Alam Bina

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