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Grasp Behavior Analysis Using Muscle and Postural Hand Synergies for Smartphones

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Abstract

Smartphones are currently among the most common handheld devices. Previous studies on such handheld touchscreen devices focused on thumb operations or reach zones by measuring individual muscle or joint angles. However, they were limited to thumb operations and did not consider grasping. In this study, we investigated the grasp types of touchscreen devices and other objects included in an existing grasp taxonomy. To this end, principal component analysis and latent profile analysis clustering were used for extracting and grouping muscle and postural synergies. Fourteen healthy subjects performed up to 15 hand grasps, including that with a smartphone. Electromyography (EMG) data were measured on six muscles in the forearm and the hand, and joint angles were measured for 22 joints in the hand. The first two muscle synergies from the EMG data and the first three postural synergies from the kinematic data were found to account for over 60% of the overall grasping. In terms of the synergies, the grasp for handheld touchscreen devices showed unique characteristics in terms of muscle and postural synergies compared to other objects. The obtained results may aid in understanding of grasping behaviors for handheld touchscreen devices in various applications.

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References

  1. Wolniewicz, C. A., Tiamiyu, M. F., Weeks, J. W., & Elhai, J. D. (2018). Problematic smartphone use and relations with negative affect, fear of missing out, and fear of negative and positive evaluation. Psychiatry Research, 262, 618–623. https://doi.org/10.1016/j.psychres.2017.09.058.

    Article  Google Scholar 

  2. Trudeau, M. B., Asakawa, D. S., Jindrich, D. L., & Dennerlein, J. T. (2016). Two-handed grip on a mobile phone affords greater thumb motor performance, decreased variability, and a more extended thumb posture than a one-handed grip. Applied Ergonomics, 52, 24–28. https://doi.org/10.1016/j.apergo.2015.06.025.

    Article  Google Scholar 

  3. Xiong, J., & Muraki, S. (2016). Effects of age, thumb length and screen size on thumb movement coverage on smartphone touchscreens. International Journal of Industrial Ergonomics, 53, 140–148. https://doi.org/10.1016/j.ergon.2015.11.004.

    Article  Google Scholar 

  4. Xiong, J., & Muraki, S. (2014). An ergonomics study of thumb movements on smartphone touch screen. Ergonomics, 57(6), 943–955. https://doi.org/10.1080/00140139.2014.904007.

    Article  Google Scholar 

  5. İnal, E. E., Demİrcİ, K., Çetİntürk, A., Akgönül, M., & Savaş, S. (2015). Effects of smartphone overuse on hand function, pinch strength, and the median nerve. Muscle and Nerve, 52(2), 183–188. https://doi.org/10.1002/mus.24695.

    Article  Google Scholar 

  6. Xie, Y., Szeto, G. P. Y., Dai, J., & Madeleine, P. (2016). A comparison of muscle activity in using touchscreen smartphone among young people with and without chronic neck-shoulder pain. Ergonomics, 59(1), 61–72. https://doi.org/10.1080/00140139.2015.1056237.

    Article  Google Scholar 

  7. Lee, S., et al. (2019). Determining ergonomic smartphone forms with high grip comfort and attractive design. Human Factors, 61(1), 90–104. https://doi.org/10.1177/0018720818792758.

    Article  Google Scholar 

  8. Feix, T., Romero, J., Schmiedmayer, H.-B., Dollar, A. M., & Kragic, D. (2016). The GRASP taxonomy of human grasp types. IEEE Transactions on Human-Machine System, 46(1), 66–77. https://doi.org/10.1109/THMS.2015.2470657.

    Article  Google Scholar 

  9. Jarque-Bou, N. J., Scano, A., Atzori, M., & Müller, H. (2019). Kinematic synergies of hand grasps: A comprehensive study on a large publicly available dataset. Journal of neuroengineering and rehabilitation, 16(1), 1–14. https://doi.org/10.1186/s12984-019-0536-6.

    Article  Google Scholar 

  10. Kim, H., Lee, J., & Kim, J. (2019). Muscle synergy analysis for stroke during two degrees of freedom reaching task on horizontal plane. Internation Journal of Precision Engineering Manufacturing. https://doi.org/10.1007/s12541-019-00251-5.

    Article  Google Scholar 

  11. Scano, A., Chiavenna, A., Tosatti, L. M., Müller, H., & Atzori, M. (2018). Muscle synergy analysis of a hand-grasp dataset: A limited subset of motor modules may underlie a large variety of grasps. Frontiers in Neurorobotics, 12, 1–14. https://doi.org/10.3389/fnbot.2018.00057.

    Article  Google Scholar 

  12. Cutkosky, M. R. (1989). On grasp choice, grasp models, and the design of hands for manufacturing tasks. IEEE Transactions on Robotics Automation, 5(3), 269–279. https://doi.org/10.1109/70.34763.

    Article  Google Scholar 

  13. Kim, K., Park, J. H., Kim, G. H., & Son, K. (2011). A comparative evaluation about force and fatigue on thumb according to input type for repetitive use of mobile phone. Journal of Biomedical Engineering Research, 32(4), 312–318. https://doi.org/10.9718/JBER.2011.32.4.312.

    Article  Google Scholar 

  14. Kwon, S., Bahn, S., Ahn, S. H., Lee, Y., & Yun, M. H. (2016). A study on the relationships among hand muscles and form factors of large-screen curved mobile devices. International Journal of Industrial Ergonomics, 56, 17–24. https://doi.org/10.1016/j.ergon.2016.07.003.

    Article  Google Scholar 

  15. Pereira, A., Miller, T., Huang, Y.-M., Odell, D., & Rempel, D. (2013). Holding a tablet computer with one hand: effect of tablet design features on biomechanics and subjective usability among users with small hands. Ergonomics, 56(9), 1363–1375. https://doi.org/10.1080/00140139.2013.820844.

    Article  Google Scholar 

  16. Ko, P.-H., Hwang, Y.-H., & Liang, H.-W. (2016). Influence of smartphone use styles on typing performance and biomechanical exposure. Ergonomics, 59(6), 821–828. https://doi.org/10.1080/00140139.2015.1088075.

    Article  Google Scholar 

  17. Kietrys, D. M., Gerg, M. J., Dropkin, J., & Gold, J. E. (2015). Mobile input device type, texting style and screen size influence upper extremity and trapezius muscle activity, and cervical posture while texting. Applied Ergonomics, 50, 98–104. https://doi.org/10.1016/j.apergo.2015.03.003.

    Article  Google Scholar 

  18. Choi, J. H., et al. (2017). Virtual coupling triggering for interaction force reduction of haptic free-motion using surface EMG. International Journal of Precision Engineering Manufacturing, 18(7), 1013–1020. https://doi.org/10.1007/s12541-017-0119-z.

    Article  Google Scholar 

  19. Ryu, J., Son, J., Kim, S., Kim, J., Ahn, S., & Kim, Y. (2018). Determination of optimal riding positions using muscle co-contraction on upper extremity during manual standing wheelchair propulsion. International Journal of Precision Engineering Manufacturing, 19(4), 577–586. https://doi.org/10.1007/s12541-018-0070-7.

    Article  Google Scholar 

  20. Jang, G., Kim, J., Choi, Y., & Yim, J. (2014). Human shoulder motion extraction using EMG signals. International Journal of Precision Engineering Manufacturing, 15(10), 2185–2192. https://doi.org/10.1007/s12541-014-0580-x.

    Article  Google Scholar 

  21. Kim, S., et al. (2019). Development of an armband emg module and a pattern recognition algorithm for the 5-finger myoelectric hand prosthesis. International Journal of Precision Engineering Manufacturing. https://doi.org/10.1007/s12541-019-00195-w.

    Article  Google Scholar 

  22. Buchner, H. J., Hines, M. J., & Hemami, H. (1988). A dynamic model for finger interphalangeal coordination. Journal of Biomechanics, 21(6), 459–468. https://doi.org/10.1016/0021-9290(88)90238-2.

    Article  Google Scholar 

  23. Schieber, M. H., & Santello, M. (2004). Hand function: peripheral and central constraints on performance. Journal of Applied Physiology, 96(6), 2293–2300. https://doi.org/10.1152/japplphysiol.01063.2003.

    Article  Google Scholar 

  24. Na, Y., & Kim, J. (2017). Dynamic elbow flexion force estimation through a muscle twitch model and sEMG in a fatigue condition. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(9), 1431–1439. https://doi.org/10.1109/TNSRE.2016.2628373.

    Article  Google Scholar 

  25. Cram, J. R. (2011). Cram’s introduction to surface electromyography. Burlington: Jones & Bartlett Learning.

    Google Scholar 

  26. d’Avella, A., Saltiel, P., & Bizzi, E. (2003). Combinations of muscle synergies in the construction of a natural motor behavior. Nature Neuroscience, 6(3), 300–3008. https://doi.org/10.1038/nn1010.

    Article  Google Scholar 

  27. Weiss, E. J., & Flanders, M. (2004). Muscular and postural synergies of the human hand. Journal of Neurophysiology, 92(1), 523–535. https://doi.org/10.1152/jn.01265.2003.

    Article  Google Scholar 

  28. Castellini, C., & van der Smagt, P. (2013). Evidence of muscle synergies during human grasping. Biological Cybernetics, 107(2), 233–245. https://doi.org/10.1007/s00422-013-0548-4.

    Article  Google Scholar 

  29. Sheskin, D. J. (2007). Handbook of parametric and nonparametric statistical procedures (Vol. 4). Boca Raton: Chapman & Hall/CRC.

    MATH  Google Scholar 

  30. Seo, N. J., & Armstrong, T. J. (2008). Investigation of grip force, normal force, contact area, hand size, and handle size for cylindrical handles. Human Factors, 50(5), 734–744. https://doi.org/10.1518/001872008X354192.

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by Sookmyung Women’s University Research Grants (1-1903-2014). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1G1A110030311).

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Correspondence to Youngjin Na or Myung Hwan Yun.

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Ahn, S.H., Kwon, S., Na, Y. et al. Grasp Behavior Analysis Using Muscle and Postural Hand Synergies for Smartphones. Int. J. Precis. Eng. Manuf. 22, 697–707 (2021). https://doi.org/10.1007/s12541-020-00467-w

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