Large-scale assessment of needs in low vision individuals using the Aira assistive technology

Brian J Nguyen,1,2 William S Chen,3 Allison J Chen,1 Andrew Utt,4 Emily Hill,4 Ryan Apgar,5 Daniel L Chao1,2 1Shiley Eye Institute, University of California San Diego, La Jolla, CA, USA; 2University of California San Diego, School of Medicine, La Jolla, CA, USA; 3Yale School of Medicine, New Haven,...

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Autores principales:	Nguyen BJ, Chen WS, Chen AJ, Utt A, Hill E, Apgar R, Chao DL
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2019
Materias:	wearable technology low vision assistive technology device design Ophthalmology RE1-994
Acceso en línea:	https://doaj.org/article/741a6517c51640fea5f9102a148ab7e1
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spelling	oai:doaj.org-article:741a6517c51640fea5f9102a148ab7e12021-12-02T04:09:53ZLarge-scale assessment of needs in low vision individuals using the Aira assistive technology1177-5483https://doaj.org/article/741a6517c51640fea5f9102a148ab7e12019-09-01T00:00:00Zhttps://www.dovepress.com/large-scale-assessment-of-needs-in-low-vision-individuals-using-the-ai-peer-reviewed-article-OPTHhttps://doaj.org/toc/1177-5483Brian J Nguyen,1,2 William S Chen,3 Allison J Chen,1 Andrew Utt,4 Emily Hill,4 Ryan Apgar,5 Daniel L Chao1,2 1Shiley Eye Institute, University of California San Diego, La Jolla, CA, USA; 2University of California San Diego, School of Medicine, La Jolla, CA, USA; 3Yale School of Medicine, New Haven, CT, USA; 4Aira Tech Corp, La Jolla, CA, USA; 5University of New England, College of Osteopathic Medicine, Biddeford, ME, USACorrespondence: Daniel L ChaoShiley Eye Institute, University of California San Diego, 9415 Campus Point Drive, La Jolla, CA 92093, USATel +1 858 534 6290Fax +1 619 543 1975Email d6chao@ucsd.eduPurpose: To systematically evaluate the needs of low vision individuals through call data obtained through the Aira assistive technology system.Patients and methods: Aira (Aira Tech Corporation, La Jolla, CA, USA) is an on-demand assistive wearable technology designed for individuals with low vision. The user wears glasses with an integrated front-facing video camera that connects with a remote human agent who assists the user with the specified task. Call types, temporal characteristics, and duration of call were compared by gender and vision status (low vision, light perception, and blind). Chi-square tests, t-tests, ANOVA, linear regression and Poisson regression analyses were performed.Results: 878 subscribers placed 10,022 total calls (4759 female, 5263 male) over 3 months. The most common categories were reading (35%), navigation (33%), and home management (16%). The distribution of categories (χ2=49.3, p<0.001), duration (t=−7.59, p<0.0001) and time of call (χ2=37.4, p<0.001) differed by gender. The distribution of categories (χ2=61, p<0.001), duration (F=13.7, p<0.0001), and time of call (χ2=36.9, p<0.001) differed by vision status. Blind [adjusted IRR=1.68 (95% CI: 1.56–1.79)] and light perception users [adjusted IRR=1.43 (95% CI: 1.32–1.53)] had increased usage compared to low vision users. Women had higher usage than men [adjusted IRR=1.09 (95% CI: 1.04–1.13)].Conclusion: To our knowledge, this is the first large-scale needs assessment of 878 low vision individuals over 10,022 calls. The most common categories were reading, navigation, and home management. Distribution of call types, duration, and time of call differed significantly by gender and vision status. Blind and light perception users had higher usage rates than those with low vision. Women had higher usage rates than men. This large-scale needs analysis of low vision individuals provides insight into utilization patterns across varying levels of vision loss and gender, which will guide future evolutions of assistive technology by tailoring future hardware and software upgrades.Keywords: wearable technology, low vision, assistive technology, device designNguyen BJChen WSChen AJUtt AHill EApgar RChao DLDove Medical Pressarticlewearable technologylow visionassistive technologydevice designOphthalmologyRE1-994ENClinical Ophthalmology, Vol Volume 13, Pp 1853-1868 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	wearable technology low vision assistive technology device design Ophthalmology RE1-994
spellingShingle	wearable technology low vision assistive technology device design Ophthalmology RE1-994 Nguyen BJ Chen WS Chen AJ Utt A Hill E Apgar R Chao DL Large-scale assessment of needs in low vision individuals using the Aira assistive technology
description	Brian J Nguyen,1,2 William S Chen,3 Allison J Chen,1 Andrew Utt,4 Emily Hill,4 Ryan Apgar,5 Daniel L Chao1,2 1Shiley Eye Institute, University of California San Diego, La Jolla, CA, USA; 2University of California San Diego, School of Medicine, La Jolla, CA, USA; 3Yale School of Medicine, New Haven, CT, USA; 4Aira Tech Corp, La Jolla, CA, USA; 5University of New England, College of Osteopathic Medicine, Biddeford, ME, USACorrespondence: Daniel L ChaoShiley Eye Institute, University of California San Diego, 9415 Campus Point Drive, La Jolla, CA 92093, USATel +1 858 534 6290Fax +1 619 543 1975Email d6chao@ucsd.eduPurpose: To systematically evaluate the needs of low vision individuals through call data obtained through the Aira assistive technology system.Patients and methods: Aira (Aira Tech Corporation, La Jolla, CA, USA) is an on-demand assistive wearable technology designed for individuals with low vision. The user wears glasses with an integrated front-facing video camera that connects with a remote human agent who assists the user with the specified task. Call types, temporal characteristics, and duration of call were compared by gender and vision status (low vision, light perception, and blind). Chi-square tests, t-tests, ANOVA, linear regression and Poisson regression analyses were performed.Results: 878 subscribers placed 10,022 total calls (4759 female, 5263 male) over 3 months. The most common categories were reading (35%), navigation (33%), and home management (16%). The distribution of categories (χ2=49.3, p<0.001), duration (t=−7.59, p<0.0001) and time of call (χ2=37.4, p<0.001) differed by gender. The distribution of categories (χ2=61, p<0.001), duration (F=13.7, p<0.0001), and time of call (χ2=36.9, p<0.001) differed by vision status. Blind [adjusted IRR=1.68 (95% CI: 1.56–1.79)] and light perception users [adjusted IRR=1.43 (95% CI: 1.32–1.53)] had increased usage compared to low vision users. Women had higher usage than men [adjusted IRR=1.09 (95% CI: 1.04–1.13)].Conclusion: To our knowledge, this is the first large-scale needs assessment of 878 low vision individuals over 10,022 calls. The most common categories were reading, navigation, and home management. Distribution of call types, duration, and time of call differed significantly by gender and vision status. Blind and light perception users had higher usage rates than those with low vision. Women had higher usage rates than men. This large-scale needs analysis of low vision individuals provides insight into utilization patterns across varying levels of vision loss and gender, which will guide future evolutions of assistive technology by tailoring future hardware and software upgrades.Keywords: wearable technology, low vision, assistive technology, device design
format	article
author	Nguyen BJ Chen WS Chen AJ Utt A Hill E Apgar R Chao DL
author_facet	Nguyen BJ Chen WS Chen AJ Utt A Hill E Apgar R Chao DL
author_sort	Nguyen BJ
title	Large-scale assessment of needs in low vision individuals using the Aira assistive technology
title_short	Large-scale assessment of needs in low vision individuals using the Aira assistive technology
title_full	Large-scale assessment of needs in low vision individuals using the Aira assistive technology
title_fullStr	Large-scale assessment of needs in low vision individuals using the Aira assistive technology
title_full_unstemmed	Large-scale assessment of needs in low vision individuals using the Aira assistive technology
title_sort	large-scale assessment of needs in low vision individuals using the aira assistive technology
publisher	Dove Medical Press
publishDate	2019
url	https://doaj.org/article/741a6517c51640fea5f9102a148ab7e1
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Large-scale assessment of needs in low vision individuals using the Aira assistive technology

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