Human Guidance: Suggesting Walking Pace Under Manual and Cognitive Load

  • Tommaso Lisini BaldiEmail author
  • Gianluca Paolocci
  • Domenico Prattichizzo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10894)


This paper presents a comparison between two different approaches to control human walking cadence, with the further aim to assess if the users can synchronize to the suggested rhythm with low efforts while performing other tasks. Elastic haptic bands are used to suggest walking-pace during an exercise aimed at reproducing real industrial or human-robot cooperation task. The proposed system consists of two wearable interfaces for providing timing information to the users, and a pressure sensor to estimate the real gait pattern, thus resulting in a combination of walking-state monitoring and vibro-tactile stimuli to regulate the walking pace. Vibrational stimuli with a constant presentation interval are alternately and repeatedly given to the right and left side of the human body, in accordance with the desired walking cadence. We tested two different interface placements: wrists and ankles. The guidance system has been evaluated under mental and manual workload using an additional task: balancing a small sphere in the center of a flat surface. Experimental results revealed that subjects prefer the ankle position for what concerns wearability, comfort and easiness in task execution. Examples of the proposed approach in daily use are training and coaching in sports, rehabilitation, and human-robot cooperation and interaction.


Walking Speed Walking Cadence Vibro-tactile Stimuli Human-robot Cooperation Haptic Interface 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Adame, M.R., Yu, J., Moller, K., Seemann, E.: A wearable navigation aid for blind people using a vibrotactile information transfer system. In: Proceedings International Conference on Complex Medical Engineering, pp. 13–18 (2013)Google Scholar
  2. 2.
    Aggravi, M., Scheggi, S., Prattichizzo, D.: Evaluation of a predictive approach in steering the human locomotion via haptic feedback. In: Proceedings IEEE/RSJ International Conference Intelligent Robots and Systems, Hamburg, Germany (2015)Google Scholar
  3. 3.
    Bosman, S., Groenendaal, B., Findlater, J.W., Visser, T., de Graaf, M., Markopoulos, P.: GentleGuide: an exploration of haptic output for indoors pedestrian guidance. In: Chittaro, L. (ed.) Mobile HCI 2003. LNCS, vol. 2795, pp. 358–362. Springer, Heidelberg (2003). Scholar
  4. 4.
    Cosgun, A., Sisbot, E., Christensen, H.: Guidance for human navigation using a vibro-tactile belt interface and robot-like motion planning. In: Proceedings IEEE International Conference on Robotics and Automation, ICRA. pp. 6350–6355 (2014)Google Scholar
  5. 5.
    Danion, F., Varraine, E., Bonnard, M., Pailhous, J.: Stride variability in human gait: the effect of stride frequency and stride length. Gait & Posture 18(1), 69–77 (2003)CrossRefGoogle Scholar
  6. 6.
    Delcomyn, F.: Neural basis of rhythmic behavior in animals. Science 210(4469), 492–498 (1980)CrossRefGoogle Scholar
  7. 7.
    Georgiou, T., Holland, S., van der Linden, J.: A blended user centred design study for wearable haptic gait rehabilitation following hemiparetic stroke. Pervasive (2015)Google Scholar
  8. 8.
    Karuei, I., MacLean, K.E.: Susceptibility to periodic vibrotactile guidance of human cadence. In: Haptics Symposium (HAPTICS), 2014 IEEE, pp. 141–146. IEEE (2014)Google Scholar
  9. 9.
    Laurent, M., Pailhous, J.: A note on modulation of gait in man: effects of constraining stride length and frequency. Hum. Mov. Sci. 5(4), 333–343 (1986)CrossRefGoogle Scholar
  10. 10.
    Lindeman, R., Sibert, J., Mendez-Mendez, R., Patil, S., Phifer, D.: Effectiveness of directional vibrotactile cuing on a building-clearing task. In: Proceedings SIGCHI Conference on Human Factors in Computing Systems, pp. 271–280 (2005)Google Scholar
  11. 11.
    Lisini Baldi, T., Scheggi, S., Aggravii, M., Prattichizzo, D.: Haptic guidance in dynamic environments using optimal reciprocal collision avoidance. IEEE Rob. Autom. Lett. (0) (2017)Google Scholar
  12. 12.
    Lund, A.: Measuring usability with the use questionnaire. STC usability SIG newsletter (2001)Google Scholar
  13. 13.
    MacLean, K.E.: Putting haptics into the ambience. IEEE Trans. Haptics 2(3), 123–135 (2009)CrossRefGoogle Scholar
  14. 14.
    Miyake, Y., Miyagawa, T.: Internal observation and co-generative interface. In: 1999 IEEE International Conference on Systems, Man, and Cybernetics, IEEE SMC 1999 Conference Proceedings, vol. 1, pp. 229–237. IEEE (1999)Google Scholar
  15. 15.
    Philippson, M.: L’autonomie et la centralisation dans le système nerveux des animaux: étude de physiologie expérimentale et comparée. Falk (1905)Google Scholar
  16. 16.
    Riener, A.: Sensor-Actuator Supported Implicit Interaction in Driver Assistance Systems. Springer, Wiesbaden (2010). Scholar
  17. 17.
    Scheggi, S., Aggravi, M., Prattichizzo, D.: Cooperative navigation for mixed human-robot teams using haptic feedback. IEEE Trans. Hum. Mach. Syst. 47(4), 462–473 (2017)CrossRefGoogle Scholar
  18. 18.
    Scheggi, S., Aggravi, M., Morbidi, F., Prattichizzo, D.: Cooperative human-robot haptic navigation. In: Proceedings IEEE International Conference on Robotics and Automation, ICRA, pp. 2693–2698 (2014)Google Scholar
  19. 19.
    Traylor, R., Tan, H.Z.: Development of a wearable haptic display for situation awareness in altered-gravity environment: some initial findings. In: 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, HAPTICS 2002, Proceedings, pp. 159–164. IEEE (2002)Google Scholar
  20. 20.
    Van Erp, J.B., Van Veen, H.A., Jansen, C., Dobbins, T.: Waypoint navigation with a vibrotactile waist belt. ACM Trans. Appl. Percept. (TAP) 2(2), 106–117 (2005)CrossRefGoogle Scholar
  21. 21.
    Watanabe, J., Ando, H.: Pace-sync shoes: intuitive walking-pace guidance based on cyclic vibro-tactile stimulation for the foot. Virtual Reality 14(3), 213–219 (2010)CrossRefGoogle Scholar
  22. 22.
    Wickens, C.D.: Multiple resources and mental workload. Hum. Factors 50(3), 449–455 (2008)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Tommaso Lisini Baldi
    • 1
    • 2
    Email author
  • Gianluca Paolocci
    • 1
    • 2
  • Domenico Prattichizzo
    • 1
    • 2
  1. 1.Department of Information Engineering and MathematicsUniversity of SienaSienaItaly
  2. 2.Department of Advanced RoboticsIstituto Italiano di TecnologiaGenovaItaly

Personalised recommendations