Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual Impairment
For people with vision impairment, various daily tasks, such as independent navigation, information access, and context awareness, may be challenging. Although several smart devices have been developed to assist blind people, most of these devices focus exclusively on navigation assistance and obsta...
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| Format: | Article |
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MDPI AG
2025-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/11/5887 |
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| author | Huu-Huy Ngo Hung Linh Le Feng-Cheng Lin |
| author_facet | Huu-Huy Ngo Hung Linh Le Feng-Cheng Lin |
| author_sort | Huu-Huy Ngo |
| collection | DOAJ |
| description | For people with vision impairment, various daily tasks, such as independent navigation, information access, and context awareness, may be challenging. Although several smart devices have been developed to assist blind people, most of these devices focus exclusively on navigation assistance and obstacle avoidance. In this study, we developed a portable system for not only obstacle avoidance but also identifying people and their emotions. The core of the developed system is a powerful and portable edge computing device that implements various deep learning algorithms for images captured from a webcam. The user can easily select a function by using a remote control device, and the system vocally reports the results to the user. The developed system has three primary functions: detecting the names and emotions of known people; detecting the age, gender, and emotion of unknown people; and detecting objects. To validate the performance of the developed system, a prototype was constructed and tested. The results reveal that the developed system has high accuracy and responsiveness and is therefore suitable for practical applications as a navigation and social assistive device for people with visual impairment. |
| format | Article |
| id | doaj-art-1ab0eefbe70e4dcf9ff55766b234b6a8 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-1ab0eefbe70e4dcf9ff55766b234b6a82025-08-20T03:46:47ZengMDPI AGApplied Sciences2076-34172025-05-011511588710.3390/app15115887Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual ImpairmentHuu-Huy Ngo0Hung Linh Le1Feng-Cheng Lin2Faculty of Information Technology, Thai Nguyen University of Information and Communication Technology, Thai Nguyen 24000, VietnamFaculty of Engineering and Technology, Thai Nguyen University of Information and Communication Technology, Thai Nguyen 24000, VietnamDepartment of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, TaiwanFor people with vision impairment, various daily tasks, such as independent navigation, information access, and context awareness, may be challenging. Although several smart devices have been developed to assist blind people, most of these devices focus exclusively on navigation assistance and obstacle avoidance. In this study, we developed a portable system for not only obstacle avoidance but also identifying people and their emotions. The core of the developed system is a powerful and portable edge computing device that implements various deep learning algorithms for images captured from a webcam. The user can easily select a function by using a remote control device, and the system vocally reports the results to the user. The developed system has three primary functions: detecting the names and emotions of known people; detecting the age, gender, and emotion of unknown people; and detecting objects. To validate the performance of the developed system, a prototype was constructed and tested. The results reveal that the developed system has high accuracy and responsiveness and is therefore suitable for practical applications as a navigation and social assistive device for people with visual impairment.https://www.mdpi.com/2076-3417/15/11/5887age classificationemotion classificationface recognitiongender classificationobject detection |
| spellingShingle | Huu-Huy Ngo Hung Linh Le Feng-Cheng Lin Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual Impairment Applied Sciences age classification emotion classification face recognition gender classification object detection |
| title | Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual Impairment |
| title_full | Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual Impairment |
| title_fullStr | Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual Impairment |
| title_full_unstemmed | Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual Impairment |
| title_short | Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual Impairment |
| title_sort | deep learning based cognitive assistance embedded systems for people with visual impairment |
| topic | age classification emotion classification face recognition gender classification object detection |
| url | https://www.mdpi.com/2076-3417/15/11/5887 |
| work_keys_str_mv | AT huuhuyngo deeplearningbasedcognitiveassistanceembeddedsystemsforpeoplewithvisualimpairment AT hunglinhle deeplearningbasedcognitiveassistanceembeddedsystemsforpeoplewithvisualimpairment AT fengchenglin deeplearningbasedcognitiveassistanceembeddedsystemsforpeoplewithvisualimpairment |