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Orasa Patsadu. Abnormal corner of mouth fall detection of stroke patient using camera. (). King Mongkut's University of Technology North Bangkok. Central Library. : , .
Abnormal corner of mouth fall detection of stroke patient using camera
Name: Piya Thirapanmethee
Organization :
Rajamangala University of Technology Krungthep. Faculty of Science and Technology
Name: Jirayu Tancharoen
Organization :
Rajamangala University of Technology Krungthep. Faculty of Science and Technology
Name: Khananat Sae-Tang
Organization :
Rajamangala University of Technology Krungthep. Faculty of Science and Technology
Name: Nilubon Bootchai
Organization :
Rajamangala University of Technology Krungthep. Faculty of Science and Technology
Name: Sirion Nutphadung
Organization :
Rajamangala University of Technology Krungthep. Faculty of Science and Technology
Name: Orasa Patsadu
Organization :
Rajamangala University of Technology Krungthep. Faculty of Science and Technology
Email :
orasa.p@mail.rmutk.ac.th
LCSH:
Machine Learning
LCSH:
Cerebrovascular disease
LCSH:
Image processing
LCSH:
Medical care
Abstract:
This paper proposes method to detect abnormal corner of mouth fall in stroke patient using camera. There are four steps of our proposed method. First, sample subjects face is captured. Next, face image is extracted for coordinate using image processing to obtain all coordinates. Then, appropriate coordinates are selected to compute degree of mouth corner (left and right). Finally, Multilayer Perceptron and Decision Tree are used to build model. From our experiment, the result shows that our proposed method for abnormality detection of corner of mouth fall in stroke patient using Decision Tree and Multilayer Perceptron achieve accuracy of 97.06% and 96.66%, respectively. From comparison of performance, Decision Tree achieves higher accuracy than Multilayer Perceptron. So, Decision Tree model is used to develop the prototype system for abnormality detection of corner of mouth fall in stroke patient. When the system detects abnormal corner of mouth fall in stroke patient, the system will send immediate notification to caregiver. Therefore, our proposed system could be the primary assistance, especially, in case the caregiver is not with the patient. So, caregiver can perceive symptoms and can make decisions in timely manner to refer a patient for further treatment.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Modified:
2023-10-09
Issued:
2023-10-09
บทความ/Article
application/pdf
BibliograpyCitation :
In King Mongkut's University of Technology North Bangkok. Faculty of Information Technology and Digital Innovation. The 19th International Conference on Computing and Information Technology (IC2IT 2023) (pp.27-39). Bangkok : King Mongkut's University of Technology North Bangkok
eng
©copyrights King Mongkut's University of Technology North Bangkok
RightsAccess:
ใช้เวลา
0.042628 วินาที
Piya Thirapanmethee
| Title | Contributor | Type |
|---|---|---|
| Abnormal corner of mouth fall detection of stroke patient using camera
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Piya Thirapanmethee;Jirayu Tancharoen;Khananat Sae-Tang;Nilubon Bootchai;Sirion Nutphadung ;Orasa Patsadu | บทความ/Article |
Jirayu Tancharoen
| Title | Contributor | Type |
|---|---|---|
| Abnormal corner of mouth fall detection of stroke patient using camera
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Piya Thirapanmethee;Jirayu Tancharoen;Khananat Sae-Tang;Nilubon Bootchai;Sirion Nutphadung ;Orasa Patsadu | บทความ/Article |
Khananat Sae-Tang
| Title | Contributor | Type |
|---|---|---|
| Abnormal corner of mouth fall detection of stroke patient using camera
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Piya Thirapanmethee;Jirayu Tancharoen;Khananat Sae-Tang;Nilubon Bootchai;Sirion Nutphadung ;Orasa Patsadu | บทความ/Article |
Nilubon Bootchai
| Title | Contributor | Type |
|---|---|---|
| Abnormal corner of mouth fall detection of stroke patient using camera
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Piya Thirapanmethee;Jirayu Tancharoen;Khananat Sae-Tang;Nilubon Bootchai;Sirion Nutphadung ;Orasa Patsadu | บทความ/Article |
Sirion Nutphadung
| Title | Contributor | Type |
|---|---|---|
| Abnormal corner of mouth fall detection of stroke patient using camera
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Piya Thirapanmethee;Jirayu Tancharoen;Khananat Sae-Tang;Nilubon Bootchai;Sirion Nutphadung ;Orasa Patsadu | บทความ/Article |
Orasa Patsadu
| Title | Contributor | Type |
|---|---|---|
| The development of game to develop the cognitive skill for autistic children via virtual reality
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Orasa Patsadu.;Yanee Muchchimwong.;Nattaburud Narudkun. | บทความ/Article | |
| Abnormal gait pattern recognition of stroke patient in initial stage using smartphone and hybrid classification methods
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Orasa Patsadu.;Kittipat Thepmee.;Kantapong Phuengliam.;Monrada Sirimongkol. | บทความ/Article | |
| Abnormal corner of mouth fall detection of stroke patient using camera
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Piya Thirapanmethee;Jirayu Tancharoen;Khananat Sae-Tang;Nilubon Bootchai;Sirion Nutphadung ;Orasa Patsadu | บทความ/Article | |
| A comparison of classification methods of hypothyroid disease prediction
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Kulchaya Pongsawaeng.;Ausron Binmaduereh.;Panuphong Jenrotphondet.;Orasa Patsadu. | บทความ/Article |