German H. Flores
ABSTRACT
We introduce WeAllWalk, a data set of inertial sensor time series collected from blind walkers using a long cane or a guide dog. Blind participants walked through fairly long and complex indoor routes that included obstacles to be avoided and doors to be opened. Inertial data was recorded by two iPhone 6s carried by our participants in their pockets and carefully annotated. Ground truth heel strike times were measured by two small inertial sensor units clipped to the participants' shoes. We also show comparative examples of application of step counting and turn detection algorithms to selected data from WeAllWalk.
- Alzantot, M., & Youssef, M. (2012, April). UPTIME: Ubiquitous pedestrian tracking using mobile phones. In Wireless Communications and Networking Conference (WCNC), 2012 IEEE (pp. 3204--3209). IEEE.Google Scholar
- Angermann, M., Robertson, P., Kemptner, T., & Khide, M. (2010, September). A high precision reference data set for pedestrian navigation using foot-mounted inertial sensors. In Indoor Positioning and Indoor Navigation (IPIN), 2010 International Conference on (pp. 1--6). IEEE.Google ScholarCross Ref
- Apostolopoulos, I., Coming, D. S., & Folmer, E. (2015, April). Accuracy of pedometry on a head-mounted display. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 2153--2156). ACM. Google ScholarDigital Library
- Blasch, B. B., LaGrow, S. J., & De l'Aune, W. R. (1996). Three aspects of coverage provided by the long cane: Object, surface, and foot-placement preview. Journal of Visual Impairment and Blindness, 90, 295--30Google ScholarCross Ref
- Brajdic, A., & Harle, R. (2013, September). Walk detection and step counting on unconstrained smartphones. In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing (pp. 225--234). ACM. Data set available at www.cl.cam.ac.uk/~ab818/ubicomp2013.html Google ScholarDigital Library
- Chen, D., Feng, W., Zhao, Q., Hu, M., & Wang, T. (2012). An infrastructure-free indoor navigation system for blind people. Intelligent Robotics and Applications, 552--561. Google ScholarDigital Library
- Coughlan, J., Manduchi, R., & Shen, H. (2006, May). Cell phone-based wayfinding for the visually impaired. In 1st International Workshop on Mobile Vision.Google Scholar
- Dias, M. B., Steinfeld, A., & Dias, M. B. (2015). Future directions in indoor navigation technology for blind travelers. In Hassan A. Karimi (Ed.), Indoor Wayfinding and Navigation, CRC Press.Google Scholar
- Fallah, N., Apostolopoulos, I., Bekris, K., & Folmer, E. (2012, May). The user as a sensor: navigating users with visual impairments in indoor spaces using tactile landmarks. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 425--432). ACM. Google ScholarDigital Library
- Fallah, N., Apostolopoulos, I., Bekris, K., & Folmer, E. (2013). Indoor human navigation systems: A survey. Interacting with Computers.Google Scholar
- Flores, G. H., Manduchi, R., & Zenteno, E. D. (2014, November). Ariadne's thread: Robust turn detection for path back-tracing using the iPhone. In Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS), 2014 (pp. 133--140). IEEE.Google ScholarCross Ref
- Flores, J. Z., & Farcy, R. (2014). Indoor navigation system for the visually impaired using one inertial measurement unit (IMU) and barometer to guide in the subway stations and commercial centers. In Computers Helping People with Special Needs (pp. 411--418). Springer International Publishing.Google ScholarCross Ref
- Foster, R. C., Lanningham-Foster, L. M., Manohar, C., McCrady, S. K., Nysse, L. J., Kaufman, K. R., ... & Levine, J. A. (2005). Precision and accuracy of an ankle-worn accelerometer-based pedometer in step counting and energy expenditure. Preventive medicine, 41(3), 778--783.Google Scholar
- Graser, S. V., Vincent, W. J., & Pangrazi, R. P. (2007). Effects of placement, attachment, and weight classification on pedometer accuracy. J Phys Act Health 4, 359--69.Google ScholarCross Ref
- Horvat, M., Ray, C., Ramsey, V. K., Miszko, T., Keeney, R., & Blasch, B. B. (2003). Compensatory analysis and strategies for balance in individuals with visual impairments. Journal of Visual Impairment and Blindness, 97(11), 695--703.Google ScholarCross Ref
- Hub, A. (2008, July). Precise indoor and outdoor navigation for the blind and visually impaired using augmented maps and the TANIA system. In Proceedings of the 9th International Conference on Low Vision (pp. 2--5).Google Scholar
- International Conference on Indoor Positioning and Indoor Navigation (IPIN). ipin-conference.orgGoogle Scholar
- International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Services (UPINLBS). upinlbs.sjtu.edu.cnGoogle Scholar
- Jackson, R. (2013). In what pocket do you keep your phone? http://phandroid.com/2013/03/25/in-what-pocket-do-you-keep-your-phone-poll/Google Scholar
- Jayalath, S., Abhayasinghe, N., & Murray, I. (2013, October). A gyroscope based accurate pedometer algorithm. In International Conference on Indoor Positioning and Indoor Navigation (Vol. 28, p. 31st).Google Scholar
- Kalia, A. A., Legge, G. E., Roy, R., & Ogale, A. (2010). Assessment of indoor route-finding technology for people with visual impairment. Journal of visual impairment & blindness, 104(3), 135.Google ScholarCross Ref
- Košecká, J., Zhou, L., Barber, P., & Duric, Z. (2003, June). Qualitative image based localization in indoors environments. In Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on (Vol. 2, pp. II-3). IEEE.Google Scholar
- Ladetto, Q., & Merminod, B. (2002). In step with INS: Navigation for the blind, tracking emergency crews. Gps World, 13(10).Google Scholar
- Mannini, A., & Sabatini, A. M. (2011, August). A hidden Markov model-based technique for gait segmentation using a foot-mounted gyroscope. In Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE (pp. 4369--4373). IEEE.Google Scholar
- Marschollek, M., Goevercin, M., Wolf, K. H., Song, B., Gietzelt, M., Haux, R., & Steinhagen-Thiessen, E. (2008, August). A performance comparison of accelerometry-based step detection algorithms on a large, non-laboratory sample of healthy and mobility-impaired persons. In Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE (pp. 1319--1322). IEEE.Google Scholar
- Mason, S. J., Legge, G. E., & Kallie, C. S. (2005). Variability in the length and frequency of steps of sighted and visually impaired walkers. Journal of visual impairment & blindness, 99(12), 741.Google ScholarCross Ref
- Murphy Kelly, S. (2014). San Francisco Airport Tests Beacon Sensors to Guide Blind Travelers. http://mashable.com/2014/07/31/san-francisco-airport-beacons/Google Scholar
- Nakamura, K., Aono, Y., & Tadokoro, Y. (1997). A walking navigation system for the blind. Systems and computers in Japan, 28(13), 36--45.Google Scholar
- Ngo, T. T., Makihara, Y., Nagahara, H., Mukaigawa, Y., & Yagi, Y. (2014). The largest inertial sensor-based gait database and performance evaluation of gait-based personal authentication. Pattern Recognition, 47(1), 228--237. Data set available at www.am.sanken.osaka-u.ac.jp/BiometricDB/ Google ScholarDigital Library
- Pressl, B., & Wieser, M. (2006). A computer-based navigation system tailored to the needs of blind people. In Computers Helping People with Special Needs (pp. 1280--1286). Springer Berlin Heidelberg. Google ScholarDigital Library
- Riehle, T. H., Anderson, S. M., Lichter, P. A., Whalen, W. E., & Giudice, N. A. (2013, July). Indoor inertial waypoint navigation for the blind. In Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE (pp. 5187--5190). IEEE.Google ScholarCross Ref
- Sabatini, A. M., Martelloni, C., Scapellato, S., & Cavallo, F. (2005). Assessment of walking features from foot inertial sensing. Biomedical Engineering, IEEE Transactions on, 52(3), 486--494.Google ScholarCross Ref
- Schafer, R. W. (2011). What is a Savitzky-Golay filter? {lecture notes}. Signal Processing Magazine, IEEE, 28(4), 111--117.Google Scholar
- Scholkmann, F., Boss, J., & Wolf, M. (2012). An efficient algorithm for automatic peak detection in noisy periodic and quasi-periodic signals. Algorithms, 5(4), 588--603.Google ScholarCross Ref
- Yang, Z., Wu, C., Zhou, Z., Zhang, X., Wang, X., & Liu, Y. (2015). Mobility increases localizability: A survey on wireless indoor localization using inertial sensors. ACM Computing Surveys (CSUR), 47(3), 54. Google ScholarDigital Library
- Yang, C. C., & Hsu, Y. L. (2010). A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors, 10(8), 7772--7788.Google ScholarCross Ref
- Yang, Z., Wu, C., & Liu, Y. (2012, August). Locating in fingerprint space: wireless indoor localization with little human intervention. In Proceedings of the 18th annual international conference on Mobile computing and networking (pp. 269--280). ACM. Google ScholarDigital Library
- Yoneyama, M., Kurihara, Y., Watanabe, K., & Mitoma, H. (2014). Accelerometry-based gait analysis and its application to Parkinson's disease assessment-Part 1: Detection of stride event. Neural Systems and Rehabilitation Engineering, IEEE Transactions on, 22(3), 613--622.Google Scholar
Index Terms
- WeAllWalk: An Annotated Data Set of Inertial Sensor Time Series from Blind Walkers
Recommendations
WeAllWalk: An Annotated Dataset of Inertial Sensor Time Series from Blind Walkers
Special Issue of Papers from ASSETS 2016We introduce WeAllWalk, a dataset of inertial sensor time series collected from blind and sighted walkers using a long cane or a guide dog. Ten blind volunteers (seven using a long cane, one using a guide dog, and two alternating use of a long cane and ...
GaitTracker: 3D Skeletal Tracking for Gait Analysis Based on Inertial Measurement Units
Gait rehabilitation is a common method of postoperative recovery after the user sustains an injury or disability. However, traditional gait rehabilitations are usually performed under the supervision of rehabilitation specialists, which implies that the ...
Estimation of spatial-temporal gait parameters in level walking based on a single accelerometer
This paper investigates the ability of a single wireless inertial sensing device stuck on the lower trunk to provide spatial-temporal parameters during level walking. The 3-axial acceleration signals were filtered and the timing of the main gait events ...
Comments