A smart LED therapy device with an automatic facial acne vulgaris diagnosis based on deep learning and internet of things application
In low-level laser therapy, providing an optimal dosage and proposing a proper diagnosis before dermatological treatment are essential to reduce the side effects and potential dangers. In this article, a smart LED therapy system for automatic facial acne vulgaris diagnosis based on deep learning and...
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| Veröffentlicht in: | Computers in biology and medicine 2021-09, Vol.136, p.104610-104610, Article 104610 |
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| container_title | Computers in biology and medicine |
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| creator | Phan, Duc Tri Ta, Quoc Bao Huynh, Thanh Canh Vo, Tan Hung Nguyen, Cong Hoan Park, Sumin Choi, Jaeyeop Oh, Junghwan |
| description | In low-level laser therapy, providing an optimal dosage and proposing a proper diagnosis before dermatological treatment are essential to reduce the side effects and potential dangers. In this article, a smart LED therapy system for automatic facial acne vulgaris diagnosis based on deep learning and Internet of Things application is proposed. The main goals of this study were to (1) develop an LED therapy device with different power densities and LED grid control; (2) propose a deep learning model based on modified ResNet50 and YOLOv2 for an automatic acne diagnosis; and (3) develop a smartphone application for facial photography image capture and LED therapy parameter configuration. Furthermore, a healthcare Internet of Things (H-IoT) platform for the connectivity between smartphone apps, the cloud server, and the LED therapy device is proposed to improve the efficiency of the treatment process. Experiments were conducted on test data sets divided by a cross-validation method to verify the feasibility of the proposed LED therapy system with automatic facial acne detection. The obtained results evidenced the practical application of the proposed LED therapy system for automatic acne diagnosis and H-IoT-based solutions.
•Introducing a smart LED therapy system with a novel method for automatic facial acne vulgaris diagnosis.•An LED therapy device with different power densities and LED grid control is designed.•A deep learning model based on YOLOv2 is developed for an automatic acne diagnosis•A smartphone application is developed for facial photography image capture and LED therapy parameter configuration.•A healthcare Internet of Things (H-IoT) platform for the connectivity between smartphone apps, the cloud server, and the LED therapy device is introduced. |
| doi_str_mv | 10.1016/j.compbiomed.2021.104610 |
| format | Article |
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•Introducing a smart LED therapy system with a novel method for automatic facial acne vulgaris diagnosis.•An LED therapy device with different power densities and LED grid control is designed.•A deep learning model based on YOLOv2 is developed for an automatic acne diagnosis•A smartphone application is developed for facial photography image capture and LED therapy parameter configuration.•A healthcare Internet of Things (H-IoT) platform for the connectivity between smartphone apps, the cloud server, and the LED therapy device is introduced.</description><identifier>ISSN: 0010-4825</identifier><identifier>EISSN: 1879-0534</identifier><identifier>DOI: 10.1016/j.compbiomed.2021.104610</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Accuracy ; Acne ; Algorithms ; Automation ; Datasets ; Deep learning ; Dermatology ; Diagnosis ; Facial acne vulgaris diagnosis ; Internet ; Internet of medical things ; Internet of Things ; LED therapy Control ; LED therapy Device ; Light emitting diodes ; Light therapy ; Medical diagnosis ; Patient satisfaction ; Photography ; Sensors ; Side effects ; Smartphones ; Support vector machines</subject><ispartof>Computers in biology and medicine, 2021-09, Vol.136, p.104610-104610, Article 104610</ispartof><rights>2021</rights><rights>Copyright Elsevier Limited Sep 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c379t-445aae032a64a89ead3c3e216dece4f5350642ea09560788f1ed9876cc19bac53</citedby><cites>FETCH-LOGICAL-c379t-445aae032a64a89ead3c3e216dece4f5350642ea09560788f1ed9876cc19bac53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2570438510?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,777,781,3537,27905,27906,45976,64364,64366,64368,72218</link.rule.ids></links><search><creatorcontrib>Phan, Duc Tri</creatorcontrib><creatorcontrib>Ta, Quoc Bao</creatorcontrib><creatorcontrib>Huynh, Thanh Canh</creatorcontrib><creatorcontrib>Vo, Tan Hung</creatorcontrib><creatorcontrib>Nguyen, Cong Hoan</creatorcontrib><creatorcontrib>Park, Sumin</creatorcontrib><creatorcontrib>Choi, Jaeyeop</creatorcontrib><creatorcontrib>Oh, Junghwan</creatorcontrib><title>A smart LED therapy device with an automatic facial acne vulgaris diagnosis based on deep learning and internet of things application</title><title>Computers in biology and medicine</title><description>In low-level laser therapy, providing an optimal dosage and proposing a proper diagnosis before dermatological treatment are essential to reduce the side effects and potential dangers. In this article, a smart LED therapy system for automatic facial acne vulgaris diagnosis based on deep learning and Internet of Things application is proposed. The main goals of this study were to (1) develop an LED therapy device with different power densities and LED grid control; (2) propose a deep learning model based on modified ResNet50 and YOLOv2 for an automatic acne diagnosis; and (3) develop a smartphone application for facial photography image capture and LED therapy parameter configuration. Furthermore, a healthcare Internet of Things (H-IoT) platform for the connectivity between smartphone apps, the cloud server, and the LED therapy device is proposed to improve the efficiency of the treatment process. Experiments were conducted on test data sets divided by a cross-validation method to verify the feasibility of the proposed LED therapy system with automatic facial acne detection. The obtained results evidenced the practical application of the proposed LED therapy system for automatic acne diagnosis and H-IoT-based solutions.
•Introducing a smart LED therapy system with a novel method for automatic facial acne vulgaris diagnosis.•An LED therapy device with different power densities and LED grid control is designed.•A deep learning model based on YOLOv2 is developed for an automatic acne diagnosis•A smartphone application is developed for facial photography image capture and LED therapy parameter configuration.•A healthcare Internet of Things (H-IoT) platform for the connectivity between smartphone apps, the cloud server, and the LED therapy device is introduced.</description><subject>Accuracy</subject><subject>Acne</subject><subject>Algorithms</subject><subject>Automation</subject><subject>Datasets</subject><subject>Deep learning</subject><subject>Dermatology</subject><subject>Diagnosis</subject><subject>Facial acne vulgaris diagnosis</subject><subject>Internet</subject><subject>Internet of medical things</subject><subject>Internet of Things</subject><subject>LED therapy Control</subject><subject>LED therapy Device</subject><subject>Light emitting diodes</subject><subject>Light therapy</subject><subject>Medical diagnosis</subject><subject>Patient satisfaction</subject><subject>Photography</subject><subject>Sensors</subject><subject>Side effects</subject><subject>Smartphones</subject><subject>Support vector 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smart LED therapy device with an automatic facial acne vulgaris diagnosis based on deep learning and internet of things application</title><author>Phan, Duc Tri ; Ta, Quoc Bao ; Huynh, Thanh Canh ; Vo, Tan Hung ; Nguyen, Cong Hoan ; Park, Sumin ; Choi, Jaeyeop ; Oh, Junghwan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c379t-445aae032a64a89ead3c3e216dece4f5350642ea09560788f1ed9876cc19bac53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>Acne</topic><topic>Algorithms</topic><topic>Automation</topic><topic>Datasets</topic><topic>Deep learning</topic><topic>Dermatology</topic><topic>Diagnosis</topic><topic>Facial acne vulgaris diagnosis</topic><topic>Internet</topic><topic>Internet of medical things</topic><topic>Internet of Things</topic><topic>LED therapy Control</topic><topic>LED therapy Device</topic><topic>Light emitting 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Bao</au><au>Huynh, Thanh Canh</au><au>Vo, Tan Hung</au><au>Nguyen, Cong Hoan</au><au>Park, Sumin</au><au>Choi, Jaeyeop</au><au>Oh, Junghwan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A smart LED therapy device with an automatic facial acne vulgaris diagnosis based on deep learning and internet of things application</atitle><jtitle>Computers in biology and medicine</jtitle><date>2021-09</date><risdate>2021</risdate><volume>136</volume><spage>104610</spage><epage>104610</epage><pages>104610-104610</pages><artnum>104610</artnum><issn>0010-4825</issn><eissn>1879-0534</eissn><abstract>In low-level laser therapy, providing an optimal dosage and proposing a proper diagnosis before dermatological treatment are essential to reduce the side effects and potential dangers. In this article, a smart LED therapy system for automatic facial acne vulgaris diagnosis based on deep learning and Internet of Things application is proposed. The main goals of this study were to (1) develop an LED therapy device with different power densities and LED grid control; (2) propose a deep learning model based on modified ResNet50 and YOLOv2 for an automatic acne diagnosis; and (3) develop a smartphone application for facial photography image capture and LED therapy parameter configuration. Furthermore, a healthcare Internet of Things (H-IoT) platform for the connectivity between smartphone apps, the cloud server, and the LED therapy device is proposed to improve the efficiency of the treatment process. Experiments were conducted on test data sets divided by a cross-validation method to verify the feasibility of the proposed LED therapy system with automatic facial acne detection. The obtained results evidenced the practical application of the proposed LED therapy system for automatic acne diagnosis and H-IoT-based solutions.
•Introducing a smart LED therapy system with a novel method for automatic facial acne vulgaris diagnosis.•An LED therapy device with different power densities and LED grid control is designed.•A deep learning model based on YOLOv2 is developed for an automatic acne diagnosis•A smartphone application is developed for facial photography image capture and LED therapy parameter configuration.•A healthcare Internet of Things (H-IoT) platform for the connectivity between smartphone apps, the cloud server, and the LED therapy device is introduced.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.compbiomed.2021.104610</doi><tpages>1</tpages></addata></record> |
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| subjects | Accuracy Acne Algorithms Automation Datasets Deep learning Dermatology Diagnosis Facial acne vulgaris diagnosis Internet Internet of medical things Internet of Things LED therapy Control LED therapy Device Light emitting diodes Light therapy Medical diagnosis Patient satisfaction Photography Sensors Side effects Smartphones Support vector machines |
| title | A smart LED therapy device with an automatic facial acne vulgaris diagnosis based on deep learning and internet of things application |
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