This study investigates and acts as a trial clinical outcome for human motion and behaviour analysis in consensus of health related quality of life in Malaysia. The proposed technique was developed to analyze and acce...This study investigates and acts as a trial clinical outcome for human motion and behaviour analysis in consensus of health related quality of life in Malaysia. The proposed technique was developed to analyze and access the quality of human motion that can be used in hospitals, clinics and human motion researches. It aims to establish how to?widespread the quality of life effects of human motion. Reliability and validity are needed to facilitate subject outcomes. An experiment was set up in a laboratory environment with conjunction of analyzing human motion and its behaviour. Five classifiers and algorithms were used to recognize and classify the motion patterns. The proposed PCA-K-Means clustering took 0.058 seconds for classification process. Resubstitution error for the proposed technique was 0.002 and achieved 94.67% of true positive for total confusion matrix of the classification accuracy. The proposed clustering algorithm achieved higher speed of processing, higher accuracy of performance and reliable cross validation error.展开更多
The paper presents the microwave signal processing method using MATLAB based on the result of microwave imaging system simulation developed using Computer Simulation Technology (CST). The simulation system contains a ...The paper presents the microwave signal processing method using MATLAB based on the result of microwave imaging system simulation developed using Computer Simulation Technology (CST). The simulation system contains a transmitting/receiving antenna, human brain and a tumor inside the brain model. The source signal, microwave signal operates from 1 to 10 GHz. The generated scattering parameters (S-parameters) are in frequency domain form. This paper describes in detail regarding the signal conversion from frequency domain to time domain through proposed Inverse Fast Fourier Transform (IFFT) method as well as the noise filtering process. Peaks detection process was performed in order to identify the time delay of the reflection points at different Y-axis展开更多
Gait analysis is a process of learning the motion of human and animal by using wearable sensor approach and vision approach. This analysis is mainly used in medical and sports field where the study of body parts is cr...Gait analysis is a process of learning the motion of human and animal by using wearable sensor approach and vision approach. This analysis is mainly used in medical and sports field where the study of body parts is crucial. 3-space sensor is a sensor consists of accelerometer, gyroscope sensor and compass sensor, built in one device. In this study, 3-space sensor is used to collect data of walking and jogging motion, of a test subject running on a treadmill. Angular velocity of the test subject’s arm and the angle of subject’s leaping motion are the two main components under investigation. Data are analyzed and processed with Principal of Component Analysis (PCA) technique. This method aims to combine and reduce the number of variables of the raw data. The Quiver function is used in order to generate feature vectors for both motions. Furthermore, the output of the process was used to create a system that can recognize human motion on any given data. The system is highly able to differentiate both of the motions.展开更多
文摘This study investigates and acts as a trial clinical outcome for human motion and behaviour analysis in consensus of health related quality of life in Malaysia. The proposed technique was developed to analyze and access the quality of human motion that can be used in hospitals, clinics and human motion researches. It aims to establish how to?widespread the quality of life effects of human motion. Reliability and validity are needed to facilitate subject outcomes. An experiment was set up in a laboratory environment with conjunction of analyzing human motion and its behaviour. Five classifiers and algorithms were used to recognize and classify the motion patterns. The proposed PCA-K-Means clustering took 0.058 seconds for classification process. Resubstitution error for the proposed technique was 0.002 and achieved 94.67% of true positive for total confusion matrix of the classification accuracy. The proposed clustering algorithm achieved higher speed of processing, higher accuracy of performance and reliable cross validation error.
文摘The paper presents the microwave signal processing method using MATLAB based on the result of microwave imaging system simulation developed using Computer Simulation Technology (CST). The simulation system contains a transmitting/receiving antenna, human brain and a tumor inside the brain model. The source signal, microwave signal operates from 1 to 10 GHz. The generated scattering parameters (S-parameters) are in frequency domain form. This paper describes in detail regarding the signal conversion from frequency domain to time domain through proposed Inverse Fast Fourier Transform (IFFT) method as well as the noise filtering process. Peaks detection process was performed in order to identify the time delay of the reflection points at different Y-axis
文摘Gait analysis is a process of learning the motion of human and animal by using wearable sensor approach and vision approach. This analysis is mainly used in medical and sports field where the study of body parts is crucial. 3-space sensor is a sensor consists of accelerometer, gyroscope sensor and compass sensor, built in one device. In this study, 3-space sensor is used to collect data of walking and jogging motion, of a test subject running on a treadmill. Angular velocity of the test subject’s arm and the angle of subject’s leaping motion are the two main components under investigation. Data are analyzed and processed with Principal of Component Analysis (PCA) technique. This method aims to combine and reduce the number of variables of the raw data. The Quiver function is used in order to generate feature vectors for both motions. Furthermore, the output of the process was used to create a system that can recognize human motion on any given data. The system is highly able to differentiate both of the motions.
