TY  - BOOK
AU  - Amira Gaber Mahmoud Ahmed Elsharkawey
AU  - Manal Abdelwahed , 
AU  - Mona Taher , 
TI  - Automated grading of facial paralysis using the kinect v2 / 
PY  - 2016///
CY  - Cairo : 
PB  - Amira Gaber Mahmoud Ahmed Elsharkawey , 
KW  - Facial Paralysis
KW  - Grading Systems
KW  - Kinect v2
N1  - Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering; Issued also as CD
N2  - This thesis describes the research, design, implementation, and testing of an automated quantitative grading system used for Facial Paralysis (FP) assessment. This system has three assessment modules; resting symmetry assessment, voluntary movement assessment, and traditional scales assessment. The system is based on the Kinect v2 hardware and the accompanying software SDK 2.0 in extracting the real time facial landmark points without the need to place markers on the subject{u2019}s face. The system can be used for grading facial asymmetry based on detecting the positions and movements of certain selected facial landmarks. The initial method of grading resting symmetry depending on the ratio between distances in both sides has limitations. Several modifications were added to overcome the limitations and increase the accuracy. The modified grading method was tested on normal persons and the results were promising. The system has significant advantages over the existing grading scales. It is fast, easy to use, low cost, quantitative, and automated and hence it is suitable to be used as a clinical tool
UR  - http://172.23.153.220/th.pdf
ER  -