A5081457071- ECG Monitoring and Analysis
- Phonocardiography and Auscultation Techniques
- Non-Invasive Vital Sign Monitoring
- Music and Audio Processing
- Assistive Technology in Communication and Mobility
- EEG and Brain-Computer Interfaces
- Muscle activation and electromyography studies
- Gaze Tracking and Assistive Technology
- Cardiac Imaging and Diagnostics
University of Kuala Lumpur
2014-2020
<span>This paper presents the classification of EMG signal for multiple hand gestures based on neural network. In this study, Electromyography is used to measure muscle cell’s electrical activities which commonly represented in a function time. Every has their own signals, was produced every movement. Surface electromyography (sEMG) as non-invasive technique acquiring signal. The development sensors’ detection and measuring have been improved become more precise while maintaining small...
<p><em>Heart sound analysis has been a popular topic of studies since few decades ago. Most the are done in PC platform embedding complex algorithm into simple small device such as microcontroller board seems to be very difficult due limited processing speed and memory. This study classifies normal abnormal heart signal from four categories Heart Valve Disease. An automated system that consists segmentation, feature extraction classification is developed hardware platforms. A...
Heart sound segmentation was very important as it is one of the most steps in heart analysis. This paper describes how signal segmented into cycles based on pattern peak intervals. The major this project include detecting significant peaks, determining intervals consistency level and finally removing unwanted well recovering missing peak. 908 out 1089 from 62 set normal abnormal signals are successfully detected by system.
This paper describes an offline PC based system to classify normal and abnormal heart sound signals from audio files. The reads the selected signal, automatically segments into samples, extract feature of each samples using cross-correlation method hierarchical multilayer perceptron network. Matlab GUI is used create interface in platform. gives high percentage screening specificity (96.3%), sensitivity (92.59%) accuracy (94.44%).
This paper presents a proposed prototype model on the development of wireless EMG control system application in medical telemetry world. The area acquiring signal that has been focused is at muscle activity arm. current problems and motivations relation to described as eliminate presently implemented complex wired system. objective this design low cost portable by developing simple using miniaturized wheelchair model. Hence, promoting model, can be real for penetrating market rehabilitation...