Computer Vision System for Facial Palsy Detection
Facial palsy (FP) is a disorder that affects the seventh facial nerve, which makes the patient unable to control facial movements and expressions with other vital activities. It affects one side of the face, and it is usually diagnosed by the asymmetry of the two sides of the face through visual in...
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| Language: | English |
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middle technical university
2023-03-01
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| Series: | Journal of Techniques |
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| Online Access: | https://journal.mtu.edu.iq/index.php/MTU/article/view/1133 |
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| author | Ali Saber Amsalam Ali Al-Naji Ammar Yahya Daeef Javaan Chahl |
| author_facet | Ali Saber Amsalam Ali Al-Naji Ammar Yahya Daeef Javaan Chahl |
| author_sort | Ali Saber Amsalam |
| collection | DOAJ |
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Facial palsy (FP) is a disorder that affects the seventh facial nerve, which makes the patient unable to control facial movements and expressions with other vital activities. It affects one side of the face, and it is usually diagnosed by the asymmetry of the two sides of the face through visual inspection by a doctor. However, the visual inspection is human-based, which is prone to errors because the doctor is exposed to omission due to fatigue and work stress. Therefore, it is important to develop a new method for detecting FP through artificial intelligence and use a more accurate computerized system to reduce the effort and cost of patients and increase the accuracy of diagnosis. This work aims to establish a safe, useful and high-accuracy diagnostic system for FP that can be used by the patient and proposes to detect FP using a digital camera and deep learning techniques automatically. The system could be used by the patient himself at home without needing to visit the hospital. The proposed system trained 570 images, including 200 images of FP palsy. The proposed FP system achieved an accuracy of 98%. This confirms the effectiveness of the proposed system and makes it an efficient medical examination tool for detecting FP.
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| format | Article |
| id | doaj-art-bced081d16b6487296fe8f2415190ac3 |
| institution | Kabale University |
| issn | 1818-653X 2708-8383 |
| language | English |
| publishDate | 2023-03-01 |
| publisher | middle technical university |
| record_format | Article |
| series | Journal of Techniques |
| spelling | doaj-art-bced081d16b6487296fe8f2415190ac32025-01-19T11:01:56Zengmiddle technical universityJournal of Techniques1818-653X2708-83832023-03-015110.51173/jt.v5i1.1133Computer Vision System for Facial Palsy DetectionAli Saber Amsalam0Ali Al-Naji1Ammar Yahya Daeef2Javaan Chahl 3Electrical Engineering Technical College, Middle Technical University, Baghdad, Iraq.School of Engineering, University of South Australia, Adelaide, AustraliaTechnical Institute for Administration, Middle Technical University, Baghdad, IraqSchool of Engineering, University of South Australia, Mawson Lakes, SA 5095, Australia Facial palsy (FP) is a disorder that affects the seventh facial nerve, which makes the patient unable to control facial movements and expressions with other vital activities. It affects one side of the face, and it is usually diagnosed by the asymmetry of the two sides of the face through visual inspection by a doctor. However, the visual inspection is human-based, which is prone to errors because the doctor is exposed to omission due to fatigue and work stress. Therefore, it is important to develop a new method for detecting FP through artificial intelligence and use a more accurate computerized system to reduce the effort and cost of patients and increase the accuracy of diagnosis. This work aims to establish a safe, useful and high-accuracy diagnostic system for FP that can be used by the patient and proposes to detect FP using a digital camera and deep learning techniques automatically. The system could be used by the patient himself at home without needing to visit the hospital. The proposed system trained 570 images, including 200 images of FP palsy. The proposed FP system achieved an accuracy of 98%. This confirms the effectiveness of the proposed system and makes it an efficient medical examination tool for detecting FP. https://journal.mtu.edu.iq/index.php/MTU/article/view/1133Non-Contact Palsy DetectionComputer VisionDeep LearningDigital Camera |
| spellingShingle | Ali Saber Amsalam Ali Al-Naji Ammar Yahya Daeef Javaan Chahl Computer Vision System for Facial Palsy Detection Journal of Techniques Non-Contact Palsy Detection Computer Vision Deep Learning Digital Camera |
| title | Computer Vision System for Facial Palsy Detection |
| title_full | Computer Vision System for Facial Palsy Detection |
| title_fullStr | Computer Vision System for Facial Palsy Detection |
| title_full_unstemmed | Computer Vision System for Facial Palsy Detection |
| title_short | Computer Vision System for Facial Palsy Detection |
| title_sort | computer vision system for facial palsy detection |
| topic | Non-Contact Palsy Detection Computer Vision Deep Learning Digital Camera |
| url | https://journal.mtu.edu.iq/index.php/MTU/article/view/1133 |
| work_keys_str_mv | AT alisaberamsalam computervisionsystemforfacialpalsydetection AT alialnaji computervisionsystemforfacialpalsydetection AT ammaryahyadaeef computervisionsystemforfacialpalsydetection AT javaanchahl computervisionsystemforfacialpalsydetection |