A hybrid approach to determine patients critical situation using expression & posture with convolutional neural network & Blazepose algorithm
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.
| Autores principales: | , , , , |
|---|---|
| Otros Autores: | |
| Formato: | Tesis |
| Lenguaje: | English |
| Publicado: |
Brac University
2024
|
| Materias: | |
| Acceso en línea: | http://hdl.handle.net/10361/23650 |
| id |
10361-23650 |
|---|---|
| record_format |
dspace |
| spelling |
10361-236502024-07-03T21:04:31Z A hybrid approach to determine patients critical situation using expression & posture with convolutional neural network & Blazepose algorithm Islam, Abrar Acanto, Orbin Ahmed Drishty, Mehzabin Islam Zaman, Samonty Ahmed, Jaber Rhaman, Md. Khalilur Department of Computer Science and Engineering, Brac University CNN BlazePose GHUM 3D Facial expression Posture sequence detection Critical situation detection Neural networks (Computer science) Computer algorithms This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 50-53). Patients are considered to be one of the most vulnerable persons. When it comes to critical patients their movements and behaviors need to be monitored constantly as simple negligences could result in severe consequences. It is almost impossible to monitor a patient 24/7 without making any slight error. Therefore, this paper will establish a simple but effective solution to this issue by creating a heuristic approach system that can detect a patient's facial expressions and postural movement to calculate the immediate conditions of patients with the assistance of deep learning algorithms. This is a hybrid approach as we have combined Convolutional Neural Network & BlazePose GHUM 3D to create a robust model which in our system can be used for image analysis in order to get precise monitoring results for critical situations by following specific sequences that would not have been possible without the hybrid model. Abrar Islam Orbin Ahmed Acanto Mehzabin Islam Drishty Samonty Zaman Jaber Ahmed B.Sc. in Computer Science 2024-07-03T05:13:31Z 2024-07-03T05:13:31Z 2022 2022-01 Thesis ID 17101217 ID 17201023 ID 18101315 ID 19201102 ID 19201131 http://hdl.handle.net/10361/23650 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 53 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
CNN BlazePose GHUM 3D Facial expression Posture sequence detection Critical situation detection Neural networks (Computer science) Computer algorithms |
| spellingShingle |
CNN BlazePose GHUM 3D Facial expression Posture sequence detection Critical situation detection Neural networks (Computer science) Computer algorithms Islam, Abrar Acanto, Orbin Ahmed Drishty, Mehzabin Islam Zaman, Samonty Ahmed, Jaber A hybrid approach to determine patients critical situation using expression & posture with convolutional neural network & Blazepose algorithm |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022. |
| author2 |
Rhaman, Md. Khalilur |
| author_facet |
Rhaman, Md. Khalilur Islam, Abrar Acanto, Orbin Ahmed Drishty, Mehzabin Islam Zaman, Samonty Ahmed, Jaber |
| format |
Thesis |
| author |
Islam, Abrar Acanto, Orbin Ahmed Drishty, Mehzabin Islam Zaman, Samonty Ahmed, Jaber |
| author_sort |
Islam, Abrar |
| title |
A hybrid approach to determine patients critical situation using expression & posture with convolutional neural network & Blazepose algorithm |
| title_short |
A hybrid approach to determine patients critical situation using expression & posture with convolutional neural network & Blazepose algorithm |
| title_full |
A hybrid approach to determine patients critical situation using expression & posture with convolutional neural network & Blazepose algorithm |
| title_fullStr |
A hybrid approach to determine patients critical situation using expression & posture with convolutional neural network & Blazepose algorithm |
| title_full_unstemmed |
A hybrid approach to determine patients critical situation using expression & posture with convolutional neural network & Blazepose algorithm |
| title_sort |
hybrid approach to determine patients critical situation using expression & posture with convolutional neural network & blazepose algorithm |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/23650 |
| work_keys_str_mv |
AT islamabrar ahybridapproachtodeterminepatientscriticalsituationusingexpressionposturewithconvolutionalneuralnetworkblazeposealgorithm AT acantoorbinahmed ahybridapproachtodeterminepatientscriticalsituationusingexpressionposturewithconvolutionalneuralnetworkblazeposealgorithm AT drishtymehzabinislam ahybridapproachtodeterminepatientscriticalsituationusingexpressionposturewithconvolutionalneuralnetworkblazeposealgorithm AT zamansamonty ahybridapproachtodeterminepatientscriticalsituationusingexpressionposturewithconvolutionalneuralnetworkblazeposealgorithm AT ahmedjaber ahybridapproachtodeterminepatientscriticalsituationusingexpressionposturewithconvolutionalneuralnetworkblazeposealgorithm AT islamabrar hybridapproachtodeterminepatientscriticalsituationusingexpressionposturewithconvolutionalneuralnetworkblazeposealgorithm AT acantoorbinahmed hybridapproachtodeterminepatientscriticalsituationusingexpressionposturewithconvolutionalneuralnetworkblazeposealgorithm AT drishtymehzabinislam hybridapproachtodeterminepatientscriticalsituationusingexpressionposturewithconvolutionalneuralnetworkblazeposealgorithm AT zamansamonty hybridapproachtodeterminepatientscriticalsituationusingexpressionposturewithconvolutionalneuralnetworkblazeposealgorithm AT ahmedjaber hybridapproachtodeterminepatientscriticalsituationusingexpressionposturewithconvolutionalneuralnetworkblazeposealgorithm |
| _version_ |
1814309237704097792 |