Master of Science Thesis Defense by: A.M. Esfar-E-Alam
When: Friday,
September 22, 2017
11:00 AM
-
1:00 PM
Where: Textiles Building 101E
Cost: free
Description: Topic: Cloud Based Wireless Health and Its Application of Sleep Monitoring
Location: College of Engineering Conference Room, Textiles Building (TXT), Room 101E
Abstract:
In this project, I developed a system combining Internet of Things (IOT) devices and cloud that can help us to achieve a sustainable ECG monitoring. The project also applied some techniques such as data analytics, noise reduction and feature extraction to processing ECG signal with the power of parallel processing in cloud environment. In addition, I also focus on detecting sleep behavior using video processing techniques. The sleep monitoring system could help find the pattern of people's sleep behavior and could provide some health suggestions. Sleep monitoring using video processing along with wireless sensors such as for ECG sensors can also reduce the overall system cost and help the detection of life threatening events during sleep. The effectiveness and efficiency of the proposed system are also demonstrated.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Advisor: Dr. Honggang Wang
Committee Members: Dr. Liudong Xing, Department of Electrical & Computer Engineering and Dr. Hua Fang, Department of Computer & Information Science
Location: College of Engineering Conference Room, Textiles Building (TXT), Room 101E
Abstract:
In this project, I developed a system combining Internet of Things (IOT) devices and cloud that can help us to achieve a sustainable ECG monitoring. The project also applied some techniques such as data analytics, noise reduction and feature extraction to processing ECG signal with the power of parallel processing in cloud environment. In addition, I also focus on detecting sleep behavior using video processing techniques. The sleep monitoring system could help find the pattern of people's sleep behavior and could provide some health suggestions. Sleep monitoring using video processing along with wireless sensors such as for ECG sensors can also reduce the overall system cost and help the detection of life threatening events during sleep. The effectiveness and efficiency of the proposed system are also demonstrated.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Advisor: Dr. Honggang Wang
Committee Members: Dr. Liudong Xing, Department of Electrical & Computer Engineering and Dr. Hua Fang, Department of Computer & Information Science
Contact:
ECE: Electrical & Computer Engineering Department 508.999.9164 http://www.umassd.edu/engineering/ece/
Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering