Smart homecare technologies for the visually impaired: recent advances

References

• World Health Organization. Visual impairment and blindness. Available from: http://www.who.int/mediacentre/factsheets/fs282/en/. Accessed October 12, 2014.
   Google Scholar
• Bujacz M, Baranski P, Moranski M, Strumillo P, Materka A. Remote mobility and navigation aid for the visually disabled. In: Sharkey PM, Lopes-dos-Santos P, Weiss PL, Brooks AL, editors. Proceedings of the Seventh Conference on Disability, Virtual Reality and Associated Technologies with ArtAbilitation. Maia, Portugal, September 8–11, 2008.
   Google Scholar
• Velázquez R. Wearable assistive devices for the blind. In: Lay-Ekuakille A, Mukhopadhyay SC, editors. Wearable and Autonomous Biomedical Devices and Systems for Smart Environment: Issues and Characterization. Lecture Notes in Electrical Engineering Series Volume 75. Berlin, Germany: Springer; 2010.
   Google Scholar
• Farcy R, Bellik Y. Comparison of various interface modalities for a locomotion assistance device. In: Miesenberger K, Klaus J, Zagler W, editors. Computers Helping People with Special Needs. Berlin, Germany: Springer; 2002.
   Google Scholar
• Andò B, Ascia A. Navigation aids for the visually impaired: from artificial codification to natural sensing. IEEE Instrum Meas Mag. 2007;10:44–51.
   Web of Science ®Google Scholar
• Andò B, Baglio S, La Malfa S, Marletta V.. Innovative smart sensing solutions for the visually impaired. In: Pereira J, editor. Handbook of Research on Personal Autonomy Technologies and Disability Informatics. Hershey, PA, USA: Medical Information Science Reference; 2011.
   Google Scholar
• Andò B, Graziani S. Multisensor strategies to assist blind people: a clear-path indicator. IEEE Trans Instrum Meas. 2009;58:2488–2494.
   Web of Science ®Google Scholar
• Andò B. A smart multisensor approach to assist blind people in specific urban navigation tasks. IEEE Trans Neural Syst Rehabil Eng. 2008;16:592–594.
   Web of Science ®Google Scholar
• Kay L. A sonar aid to enhance spatial perception of the blind: engineering design and evaluation. Radio and Electronic Engineer. 1974;44:605–627.
   Google Scholar
• The Miniguide mobility aid [webpage on the Internet]. Adelaide: GDP Research. Available from http://www.gdp-research.com.au/minig_1.htm. Accessed November 13, 2014.
   Google Scholar
• Villanueva J, Farcy R. Optical device indicating a safe free path to blind people. IEEE Trans Instrum Meas. 2012;61:170–177.
   Web of Science ®Google Scholar
• Scalise L, Primiani VM, Russo P, et al. Experimental investigation of electromagnetic obstacle detection for visually impaired users: a comparison with ultrasonic sensing. IEEE Trans Instrum Meas. 2012;61:3047–3057.
   Web of Science ®Google Scholar
• Gemperle F, Ota N, Siewiorek D. Design of a wearable tactile display. Presented at the Fifth International Symposium on Wearable Computers, October 8–9, 2001, Zurich, Switzerland.
   Google Scholar
• Meijer P. An experimental system for auditory image representations. IEEE Trans Biomed Eng. 1992;39:112–121.
   PubMed Web of Science ®Google Scholar
• Velazquez R, Fontaine E, Pissaloux E. Coding the environment in tactile maps for real-time guidance of the visually impaired. Presented at the IEEE International Symposium on Micro-NanoMechatronics and Human Science, November 5–8, 2006, Nagoya, Japan.
   Google Scholar
• Andò B. Sensors that provide security for people with depressed receptors. IEEE Mag Instrum Meas. 2006;9:58–63.
   Web of Science ®Google Scholar
• Andò B, Baglio S, Lombardo CO, Marletta V, Pergolizzi EA, Pistorio A. (2013) RESIMA: A New WSN Based Paradigm to Assist Weak People in Indoor Environment. IEEE International Workshop on Measurements and Networking Proceedings (M&N); 7-8 October, 2013; Napoli. 206-209.
   Google Scholar
• Andò B, Baglio S, Lombardo C. RESIMA: an assistive paradigm to support weak people in indoor environments. IEEE Trans Instrum Meas. 2014;63:2522–2528.
   Web of Science ®Google Scholar
• Andò B, Savalli N. CANBUS networked sensors use in orientation tools for the visually impaired wired versus wireless technology. IEEE Trans Instrum Meas. 2008;11:49–52.
   Google Scholar
• Chen W, Chen R, Chen Y, Kuusniemi H, Wang J. An effective Pedestrian Dead Reckoning algorithm using a unified heading error model. Position Location and Navigation Symposium, 2010. Available from: http://ieeexplore.ieee.org/xpl/abstractAuthors.jsp?tp=&arnumber=5507300&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F5492941%2F5507125%2F05507300.pdf%3Farnumber%3D5507300. Accessed October 11, 2014.
   Google Scholar
• Kaniewski P, Kazubek J. Integrated system for heading determination. Acta Phys Pol A. 2009;116:325–330.
   Web of Science ®Google Scholar
• Yan L, Qiang W, Junbin L, Wark T. MCMC-based indoor localization with a smart phone and sparse WiFi access points. Presented at the Annual IEEE International Conference on Pervasive Computing and Communications, March 19–23, 2012, Lugano, Switzerland.
   Google Scholar
• Kim JW, Jang HJ, Hwang DH, Park C. A step, stride and heading determination for the pedestrian navigation system. Journal of Global Positioning Systems. 2004;3:273–279.
   Google Scholar
• Goyal P, Ribeiro VJ, Saran H, Kumar A. Strap-down Pedestrian Dead-Reckoning system. Presented at the 2011 International Conference on Indoor Positioning and Indoor Navigation, September 21–23, 2011, Guimaraes, Portugal.
   Google Scholar
• Chi-Chung L, Chen-Pin C, Yu-Chee T, Sheng-An C, Lun-Chia K. A Walking Velocity Update technique for pedestrian dead-reckoning applications. Available from: http://people.cs.nctu.edu.tw/~yctseng/papers.pub/sensor58.walking-update-pimrc-2011.pdf. Accessed October 12, 2014.
   Google Scholar
• Jimenez AR, Seco F, Prieto JC, Guevara J. Indoor pedestrian navigation using an INS/EKF framework for yaw drift reduction and a foot-mounted IMU. Presented at the Seventh Workshop on Positioning Navigation and Communication, March 11–12, 2010, Dresden, Germany.
   Google Scholar
• Tacconi C, Mellone S, Chiari L. Smartphone-based applications for investigating falls and mobility. Presented at the Fifth International Conference on Pervasive Computing Technologies for Healthcare, May 23–26, 2011, Dublin, Ireland.
   Google Scholar
• Trehard G, Boukallel M, Lamy-Perbal S. Indoor pedestrian localisation solution based on anemometry sensor integration with a smartphone. Presented at the 2012 International Conference Indoor Positioning and Indoor Navigation, November 13–15, 2012, Montbeliard, France.
   Google Scholar
• Gadeke T, Schmid J, Zahnlecker M, Stork W, Muller-Glaser KD. Smartphone pedestrian navigation by foot-IMU sensor fusion. Presented at the Conference on Ubiquitous Positioning, Indoor Navigation, and Location Based Service, October 3–4, 2012, Helsinki, Finland.
   Google Scholar
• Wakuda Y, Asano S, Koshizuka N, Sakamura K. Ubiquitous sensor-based pedestrian dead-reckoning for LBS applications. Presented at the 2012 International Symposium on Micro-NanoMechatronics and Human Science, November 4–7, 2012, Nagoya, Japan.
   Google Scholar
• Andò B, Baglio S, Lombardo CO, Marletta V. An advanced tracking solution fully based on native sensing features of smartphone. Presented at the IEEE Sensors Applications Symposium, February 18–20, 2014.
   Google Scholar
• Andò B, Baglio S, La Malfa S, Marletta V. A sensing architecture for mutual user-environment awareness case of study: a mobility aid for the visually impaired. IEEE Sensors Journal. 2011;11-3:634–640.
   Web of Science ®Google Scholar
• Suryadevara NK, Mukhopadhyay SC. Wireless sensor network based home monitoring system for wellness determination of elderly. IEEE Sensors Journal. 2012;12-6:1965–1972.
   Web of Science ®Google Scholar
• Rescio G, Leone A, Siciliano P. Supervised expert system for wearable MEMS accelerometer-based fall detector. Journal of Sensors. 2013;2013:1–11.
   Web of Science ®Google Scholar
• Panahandeh G, Mohammadiha N, Leijon A, Handel P. Chest-mounted inertial measurement unit for pedestrian motion classification using continuous hidden Markov model. Presented at the 2012 IEEE International Instrumentation and Measurement Technology Conference, November 16–21, 2012, New Orleans, LA, USA.
   Google Scholar
• Kang JM, Yoo T, Kim HC. A wrist-worn integrated health monitoring instrument with a tele-reporting device for telemedicine and telecare. IEEE Trans Instrum Meas. 2006;55:1655–1661.
   Web of Science ®Google Scholar
• Dunkel J, Bruns R, Stipkovic S. Event-based smartphone sensor processing for ambient assisted living. Presented at the IEEE Eleventh International Symposium on Autonomous Decentralized Systems, March 6–8, 2013, Mexico City, Mexico.
   Google Scholar
• Franco C, Fleury A, Gumery PY, Diot B, Demongeot J, Vuillerme N. iBalance-ABF: a smartphone-based audio-biofeedback balance system. IEEE Trans Biomed Eng. 2013;60:211–215.
   Web of Science ®Google Scholar
• Ketabdar H, Lyra M. System and methodology for using mobile phones in live remote monitoring of physical activities. Presented at the 2010 IEEE International Symposium on Technology and Society, June 7–9, 2010, Wollongong, Australia.
   Google Scholar
• Quang Viet V, Lee G, Choi D. Fall detection based on movement and smart phone technology. Presented at the 2012 IEEE International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future, February 27, 2012 to March 1, 2012, Ho Chi Minh City, Vietnam.
   Google Scholar
• He Y, Li Y, Bao S-D. Fall detection by built-in tri-accelerometer of smartphone. Presented at the 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics, January 2–7, 2012, Hong Kong, People’s Republic of China.
   Google Scholar
• Fahim M, Fatima I, Sungyoung L, Young-Koo L. Daily life activity tracking application for smart homes using android smartphone. Presented at the 14th International Conference on Advanced Communication Technology, February 19–22, 2012, Phoenix Park, South Korea.
   Google Scholar
• Andò B, Baglio S, Lombardo CO, Marletta V, Pergolizzi EA, Pistorio A. An event polarized paradigm for ADL detection in AAL context. Presented at the 2014 IEEE International Instrumentation and Measurement Technology Conference, May 12–14, 2014, Montevideo, Uruguay.
   Google Scholar
• Loftin RB. Multisensory perception: beyond the visual in visualization. Computing in Science and Engineering. 2003;5:56–58.
   Web of Science ®Google Scholar
• Gibson JJ. The senses considered as perceptual systems. Boston: Houghton Mifflin; 1966.
   Google Scholar
• Varalakshmi BD, Thriveni J, Venugopal KR, Patnaik LM. Haptics: state of the art survey. International Journal of Computer Science Issues. 2012;9:234–244.
   Google Scholar
• Panëels S, Roberts JC. Review of designs for haptic data visualization. IEEE Trans Haptics. 2010;3:119–137.
   PubMed Web of Science ®Google Scholar
• Moustakas K, Nikolakis G, Kostopoulos K, Tzovaras D, Strintzis MG. Haptic rendering of visual data for the visually impaired. IEEE MultiMedia. 2007;14:62–72.
   Web of Science ®Google Scholar
• Schloerb DW, Lahav O, Desloge JG, Srinivasan MA. BlindAid: virtual environment system for self-reliant trip planning and orientation and mobility training. Paper presented at the 2010 IEEE Haptics Symposium, March 20–26, 2010, Waltham, MA, USA.
   Google Scholar
• Akhter S, Mirsalahuddin J, Marquina FB, Islam S, Sareen S. A smartphone-based haptic vision substitution system for the blind. Presented at the IEEE 37th Annual Northeast Bioengineering Conference, April 1–3, 2011, Troy, NY, USA.
   Google Scholar
• Horvath S, Galeotti J, Bing W, Klatzky R, Siegel M, Stetten G. FingerSight: Fingertip haptic sensing of the visual environment. IEEE J Transl Eng Health Med. 2014;2:1–9.
   Google Scholar
• Hayward V, Astley OR, Cruz-Hernandez M, Grant D, Robles-De-La-Torre G. Haptic interfaces and devices. Sensor Review. 2004;24:16–29.
   Google Scholar
• Cassidy B, Cockton G, Coventry L. A haptic ATM interface to assist visually impaired users. Presented at the 15th International ACM SIGACCESS Conference on Computers and Accessibility, October 21–23, 2013, Bellevue, WA, USA.
   Google Scholar
• Yoshino K, Shinoda H. Contactless touch interface supporting blind touch interaction by aerial tactile stimulation. Presented at the 2014 IEEE Haptics Symposium, February 20–23, 2014, Houston, TX, USA.
   Google Scholar
• Patomäki S, Raisamo R, Salo J, Pasto V, Hippula A. Experiences on haptic interfaces for visually impaired young children. Presented at the Sixth International Conference on Multimodal Interfaces, October 13–15, 2004, State College, PA, USA.
   Google Scholar
• Andò B, Baglio S, Pitrone N. A contactless haptic cane for blind people. Presented at the 12th IMEKO TC1-TC7 Joint Symposium on Man, Science and Measurement, September 3–5, 2008, Annecy, France.
   Google Scholar