Detection of three visual impairments: Strabismus, blind spots, and blurry vision in rural areas using Raspberry PI by implementing hirschberg, visual field, and visual acuity tests

Paglinawan, Arnold C.; Sejera, Marianne M.; Paglinawan, Charmaine C.; Ancheta, Ryan Elbert H.; Guatato, Nicole Jan D.; Nava, Rey James H.; Sison, Kimberly P.

doi:10.1109/hnicem.2017.8269550

Cited by 8 publications

(3 citation statements)

References 11 publications

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“…In this case, several studies that employ image and gesture recognition, and voice detection describe the accuracy of the methods employed in them through several techniques and software tools such as Convolutional Neuronal Networks (CNNs), Support Vector Machines (SVMs), Haar cascade classifier, or Speeded Up Robust Features (SURF) method. For instance, ATs developed for visual disabilities report an accuracy between 63% and 95.1% utilizing CNNs and You Only Look Once (YOLO) [95], [121], 88% to 90% for SURF method [94], 90% for blob detection algorithm [122], 84% for Google Cloud Vision API [123], and 85% for Tesseract [124] which is a tool for OCR applications. Similarly, ATs for mobility disabilities using EEG and EMG signals report an accuracy between 80% employing both SVMs [125] and NeuroSky MindWave headset [92], 83% with the Receiver Operating Characteristic (ROC) [126], and 97.1% for detection of facial expressions through Viola-Jones algorithm [96].…”

Section: ) Research Topicsmentioning

confidence: 99%

“…To detect visual impairments, the authors in [122] explain a system to detect three types of visual impairments, namely, strabismus, blind spots, and blurry vision for rural areas, employing Raspberry Pi, and OpenCV with blob detection algorithm. The AT was tested in several trials (3)(4)(5) to identify the impairments of n=19 volunteers.…”

Section: Educational Devices and Materialsmentioning

confidence: 99%

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Low-Cost Assistive Technologies for Disabled People Using Open-Source Hardware and Software: A Systematic Literature Review

Ariza

Pearce

2022

IEEE Access

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Disabled People deal with a series of barriers that limit their inclusion, empowerment, wellbeing, and role in society with a special emphasis in low and medium-income countries. One of these barriers is concerning the accessibility and affordability of assistive technologies (ATs) that help to enhance the quality of life of these persons. In this context, this systematic literature review (SLR) analyzes and describes how free and open-source hardware (OSHW) and open software (OSS) are employed in the design, development, and deployment of low-cost ATs. In the SLR process, different ATs were analyzed for disabilities such as visual, mobility, upper body, prostheses, hearing & speaking, daily living, and participation in society. The ATs were designed with diverse OSHW and OSS technologies such as Arduino, Raspberry Pi, NVidia Jeston, OpenCV, YOLO, MobileNet, EEG and EMG signal conditioning devices, actuators, and sensors such as ultrasonic, LiDar, or flex. 809 studies were collected and analyzed from the database Web of Science, GitHub, and the specialized journals in OSHW HardwareX and the Journal of Open Hardware during the years 2013-2022. In the first part of the SLR, the bibliometric trends and topic clusters regarding the selected studies are described. Secondly, the ATs identified with open source technologies, e.g., sensor-based or computer vision-based, are described along with a complete state-ofart about these based on each disability recognized. Finally, the issues and challenges to this approach are explored including technical factors, documentation, government policies, and the inclusion of disabled people in open source co-creation. The purpose of this study is to inform practitioners, designers, or stakeholders about low-cost (frugal) ATs with OSHW and OSS, and thus promote their development, accessibility, and affordability, contributing to benefit the community of disabled people. INDEX TERMS Assistive technologies, disabled people, persons with disabilities, adaptive aids, open hardware, open-source hardware, open-source software, systematic literature review.

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Section: ) Research Topicsmentioning

confidence: 99%

Section: Educational Devices and Materialsmentioning

confidence: 99%

Low-Cost Assistive Technologies for Disabled People Using Open-Source Hardware and Software: A Systematic Literature Review

Ariza

Pearce

2022

IEEE Access

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“…IMAGE processes the control system and transfers intelligent traffic using Arduino was approved by Sathuluri et al The system used color sensors using camera sensors to implement objects [3]. Detection of three visual impairments, namely Strabismus, blind spots, and blurred vision in rural areas using Raspberry PI using Hirschberg test, visual fields, and visual acuity was supported by Paglinawan et al to activate three visual disturbances using a camera sensor that detects color, size, and shape [4]. The development of walking for the visually impaired started by Kamal et al The system used a camera that uses a microcontroller [5].…”

Section: Introductionmentioning

confidence: 99%

Information System Prototyping of Strawberry Maturity Stages using Arduino Uno and TCS3200

Juliano

Hendrawan

Ritzkal

2020

jrc

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Strawberry is one of the commodities of subtropical fruits growing in Indonesia. It has a high economic value, attractive appeal in a red and fresh sweet fruit. The color of a strawberry shows its maturity stages, and the strawberry maturity stages affect postharvest quality. The research aimed to design and implement a tool to approve and apply the maturity stages of strawberries using Arduino Uno and display the information on the web. The method included needs analysis and analysis of work, and the design consisted of hardware design and network design. The testing consisted of TCS3200 sensor testing, LCD testing, servo motor testing, and WEB testing. The results of this study found that when the strawberry fruit was declared mature by the TCS3200 sensor as the color detection sensor, the LCD would display the texts, and the servo would open. The system on the WEB would display the total information of the sorted strawberries.

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Development of Pupil Diameter Determination using Tiny-YOLO Algorithm

Caya¹,

Rapisura²,

Despabiladeras³

2022

2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environ

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Detection of three visual impairments: Strabismus, blind spots, and blurry vision in rural areas using Raspberry PI by implementing hirschberg, visual field, and visual acuity tests

Cited by 8 publications

References 11 publications

Low-Cost Assistive Technologies for Disabled People Using Open-Source Hardware and Software: A Systematic Literature Review

Low-Cost Assistive Technologies for Disabled People Using Open-Source Hardware and Software: A Systematic Literature Review

Information System Prototyping of Strawberry Maturity Stages using Arduino Uno and TCS3200

Development of Pupil Diameter Determination using Tiny-YOLO Algorithm

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