ASSIST: Evaluating the usability and performance of an indoor navigation assistant for blind and visually impaired people

References

• Abdolrahmani, A., Easley, W., Williams, M., Branham, S., & Hurst, A. (2017). Embracing errors: Examining how context of use impacts blind individuals’ acceptance of navigation aid errors. In Proc. 2017 CHI Conf. Human Factors in Computing System (pp. 4158–4169). Denver, CO,
   Google Scholar
• Ahmetovic, D., Gleason, C., Ruan, C., Kitani, K., Takagi, H., & Asakawa, C. (2016). NavCog: A navigational cognitive assistant for the blind. Proc. 18th Int. Conf. on Human-Computer Interaction with Mobile Devices and Services - MobileHCI ’16. New York, NY.
   Google Scholar
• Ahmetovic, D., Guerreiro, J., Ohn-Bar, E., Kitani, K. M., & Asakawa, C. (2019). Impact of expertise on interaction preferences for navigation assistance of visually impaired individuals. In Proc. 16th Web for All: Personalization-Personalizing the Web. San Francisco, CA.
   Google Scholar
• Bohonos, S., Lee, A., Malik, A., Thai, C., & Manduchi, R. (2007). Universal real-time navigational assistance (URNA): An urban Bluetooth beacon for the blind. Proc.1st ACM SIGMOBILE Int. Workshop on Systems and Networking Support for Healthcare and Assisted Living Environments - HealthNet ’07. San Juan, Puerto Rico.
   Google Scholar
• Caraiman, S., Morar, A., Owczarek, M., Burlacu, A., Rzeszotarski, D., Botezatu, N., Herghelegiu, P., Moldoveanu, F., Strumillo, P., & Moldoveanu, A. (2017). Computer Vision for the Visually Impaired: The Sound of Vision System. 2017 IEEE Int. Conf. on Computer Vision Workshops (ICCVW) (pp. 1480–1489). Venice, Italy.
   Google Scholar
• Chang, Y., Chen, J., Franklin, T., Zhang, L., Ruci, A., Tang, H., & Zhu, Z. (2020, August 11- 13). Multimodal Information Integration for Indoor Navigation Using a Smartphone. IRI2020 - The 21st IEEE International Conference on Information Reuse and Integration for Data Science. Taking place virtually.
   Google Scholar
• Chang, Y. J., Chu, Y. Y., Chen, C. N., & Wang, T. Y. (2008). Mobile computing for indoor wayfinding based on Bluetooth sensors for individuals with cognitive impairments. 2008 3rd Int. Symposium on Wireless Pervasive Computing. Santorini, Greece.
   Google Scholar
• Cheraghi, S. A., Almadan, A., & Namboodiri, V. (2019b). CityGuide: A Seamless Indoor-Outdoor Wayfinding System for People With Vision Impairments. In 21st Int. ACM SIGACCESS Conf. Computers and Accessibility, 542–544. Pittsburgh PA.
   Google Scholar
• Cheraghi, S. A., Namboodiri, V., & Walker, L. (2017). GuideBeacon: Beacon-based indoor wayfinding for the blind, visually impaired, and disoriented. In IEEE Int. Conf. Pervasive Computing and Communications (PerCom) (pp. 121–130). Kailua-Kona, Alabama.
   Google Scholar
• Cheraghi, S. A., Sharma, A., Namboodiri, V., & Arsal, G. (2019a). SafeExit4AII: An Inclusive Indoor Emergency Evacuation System for People With Disabilities. In Proc. 16th Web For All: Personalization-Personalizing the Web. San Francisco, CA.
   Google Scholar
• Chumkamon, S., Tuvaphanthaphiphat, P., & Keeratiwintakorn, P. (2008). A blind navigation system using RFID for indoor environments. 2008 5th Int. Conf. on Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology. Krabi, Thailand.
   Google Scholar
• Ganz, A., Schafer, J., Gandhi, S., Puleo, E., Wilson, C., & Robertson, M. (2012). PERCEPT indoor navigation system for the blind and visually impaired: Architecture and experimentation. International Journal of Telemedicine and Applications, 2012, 1–12. https://doi.org/https://doi.org/10.1155/2012/894869
   Google Scholar
• Jeamwatthanachai, W., Wald, M., & WillsIndoor, G. (2019). Navigation by blind people: Behaviors and challenges in unfamiliar spaces and buildings. British Journal of Visual Impairment, 37(2), 140–153. https://doi.org/https://doi.org/10.1177/0264619619833723
   Web of Science ®Google Scholar
• Karkar, A., & Al-Máadeed, S. (2018). Mobile Assistive Technologies for Visual Impaired Users: A Survey. 2018 Int. Conf. on Computer and Applications (ICCA) (pp. 427–433). Beirut, Lebanon.
   Google Scholar
• Kunhoth, J., Karkar, A., Al-Maadeed, S., & Al-Attiyah, A. (2019). Comparative analysis of computer-vision and BLE technology based indoor navigation systems for people with visual impairments. International Journal of Health Geographics, 18(1), 29. https://doi.org/https://doi.org/10.1186/s12942-019-0193-9
   PubMed Web of Science ®Google Scholar
• Li, B., Munoz, P., Rong, X., Xiao, J., Tian, Y., & Arditi, A. (2016). ISANA: Wearable context-aware indoor assistive navigation with obstacle avoidance for the blind. In G. Hua G, & H. Jégou (Eds.), Lecture Notes in Computer Science (Vol. 9914). Springer.
   Google Scholar
• Miao, M., Spindler, M., & Weber, G. (2011). Requirements of indoor navigation system from blind users. In A. Holzinger & K. M. Simonic (Eds.), Information Quality in e-Health. USAB 2011. Lecture Notes in Computer Science (Vol. 7058, pp. 673–679). Springer.
   Google Scholar
• Molina, E., Khoo, W. L., Palmer, F., Ai, L., Ro, T., & Zhu, Z. (2015). Vista Wearable: Seeing through whole-body touch without contact. 12th IEEE International Conference on Ubiquitous Intelligence and Computing. Beijing, China.
   Google Scholar
• Mulloni, A., Wagner, D., Barakonyi, I., & Schmalstieg, D. (2009). Indoor positioning and navigation with camera phones. IEEE Pervasive Computing, 8(2), 22–31. https://doi.org/https://doi.org/10.1109/MPRV.2009.30
   Web of Science ®Google Scholar
• Murata, M., Ahmetovic, D., Sato, D., Takagi, H., Kitani, K. M., & Asakawa, C. (2019). Smartphone-based localization for blind navigation in building-scale indoor environments. Pervasive and Mobile Computing, 57(2018), 14–32. https://doi.org/https://doi.org/10.1016/j.pmcj.2019.04.003
   Web of Science ®Google Scholar
• Nair, V., Budhai, M., Olmschenk, G., Seiple, W. H., & Zhu, Z. (2018b). Personalized indoor navigation via multimodal sensors and high-level semantic information, Sixth International Workshop on Assistive Computer Vision and Robotics (ACVR). Munich, Germany.
   Google Scholar
• Nair, V., Tsangouri, C., Xiao, B., Olmschenk, G., Seiple, W. H., & Zhu, Z. (2018a). A hybrid indoor positioning system for the blind and visually impaired using Bluetooth and Google Tango. Journal on Technology & Persons with Disabilities, 6, 61–81. http://hdl.handle.net/10211.3/202986
   Google Scholar
• Ozdenizci, B., Ok, K., Coskun, V., & Aydin, M. N. (2011). Development of an indoor navigation system using NFC technology. 2011 Fourth Int. Conf. on Information and Computing. Phuket Island, Thailand.
   Google Scholar
• PANYNJ. (2018). Request for Information - Robots and Artificial Intelligence for The Port Authority of NY & NJ (RFI-52870), Good and Service Opportunities. The Port Authority of NY & NJ. https://www.panynj.gov/content/dam/port-authority/pdfs/bid-proposal/RFIDOC_52870.pdf
   Google Scholar
• Real, S., & Araujo, A. (2019). Navigation Systems for the Blind and Visually Impaired: Past Work, Challenges, and Open Problems. Sensors, 19(15), 3404. https://doi.org/https://doi.org/10.3390/s19153404
   PubMed Web of Science ®Google Scholar
• Remmen, B. M., & Toft, T. J. (2015, May). Blind Path [Bachelor Thesis, The Faculty of Informatics and e-Learning]. Sør-Trøndelag University College. (pp. 1–36).
   Google Scholar
• Ruiz, A. R. J., Granja, F. S., Honorato, J. C. P., & Rosas, J. I. G. (2012). Accurate pedestrian indoor navigation by tightly coupling foot-mounted IMU and RFID measurements. IEEE Transactions on Instrumentation and Measurement, 61(1), 178–189. https://doi.org/https://doi.org/10.1109/TIM.2011.2159317
   Web of Science ®Google Scholar
• Sato, D., Oh, U., Guerreiro, J., Ahmetovic, D., Naito, K., Takagi, H., Kitani, K. M., & Asakawa, C. (2019). NavCog3 in the wild: Large-scale blind indoor navigation assistant with semantic features. ACM Transactions on Accessible Computing, 12(3), 1–30. https://doi.org/https://doi.org/10.1145/3340319
   Web of Science ®Google Scholar
• Tang, H., Tsering, N., Hu, F., & Zhu, Z. (2016). Automatic pre-journey indoor map generation using AutoCAD floor plan. Journal on Technology & Persons with Disabilities, 4. https://hdl.handle.net/10211.3/180125
   Google Scholar
• Wold, W. Z., & Padøy, S. H. (2016). Indoor Navigation for the Visually Impaired - A Systematic Literature Review (Specialization Project). Department of Computer and Information Science. Faculty of Information Technology, Mathematics and Electrical Engineering, Norwegian University of Science and Technology. https://folk.idi.ntnu.no/krogstie/project-reports/2016/padoy/FordypningsProsjekt.pdf
   Google Scholar
• World Health Organization. (2019). Blindness and vision impairment. w.who.int/mediacentre/factsheets/fs282/en/
   Google Scholar
• Yoon, C., Louie, R., Ryan, J., Vu, M., Bang, H., Derksen, W., & Ruvolo, P. (2019, October). Leveraging Augmented Reality to Create Apps for People with Visual Disabilities: A Case Study in Indoor Navigation. In 21st Int. ACM SIGACCESS Conf. on Computers and Accessibility (pp. 210–221). Pittsburgh, PA.
   Google Scholar