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An Exercise-Promoting System for Exercising While Doing Desk Work

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Part of the Lecture Notes in Computer Science book series (LNCS,volume 13326)

Abstract

Recently, the importance of exercise has been attracting attention. Exercise has positive effects on the body and mind. However, many people do not get enough exercise, and this trend has not improved over the years. One fundamental challenge why people do not have more opportunities to exercise is that they are too busy with work and household chores. Therefore, to develop an exercise habit, it is necessary to incorporate “exercising” into daily life, which can be done while working or doing housework. In this paper, through the design of a system to promote “doing exercise while working at a desk,” we propose both suggestion and feedback methods that conform to working at a desk and enable users to continue to exercise. As future work, we would like to improve the accuracy of the state judgment and the notification timing of the feedback method, thereby adapting the system to various work situations.

Keywords

  • Internet of Things (IoT)
  • Exercise promotion
  • Sensing chair
  • Sitting posture recognition
  • Dynamic time warping (DTW)

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References

  1. Guthold, R., Stevens, G.A., Riley, L.M., Bull, F.C.: Worldwide trends in insufficient physical activity from 2001 to 2016: a pooled analysis of 358 population-based surveys with 1–9 million participants. Lancet Glob. Health 6(10), e1077–e1086 (2018). https://doi.org/10.1016/S2214-109X(18)30357-7

  2. Maffiuletti, N.A., Cometti, G., Amiridis, I.G., Martin, A., Pousson, M.L., Chatard, J.C.: The effects of electromyostimulation training and basketball practice on muscle strength and jumping ability. Int. J. Sports Med. 21(6), 437–443 (2000). https://doi.org/10.1055/s-2000-3837, https://www.thieme-connect.de/products/ejournals/abstract/10.1055/s-2000-3837

  3. The Japan Home-health Apparatus Industrial Association.: voluntary standards for the safety of ems equipment for home use. https://www.hapi.or.jp/documentation/information/ems_20201009r.pdf. Accessed 11 Jan 2022. (In Japanese)

  4. Japan Sports Agency.: Public opinion poll on the status of sports implementation, etc., https://www.mext.go.jp/sports/content/20200507-spt_kensport01-000007034_1.pdf. Accessed 11 Jan 2022. (In Japanese)

  5. Bouchard, C., Deprks, J.P., Trernbluy, A.: Exercise and obesity. Coron. Artery Dis. 11(2), 111–116 (2000). https://doi.org/10.1097/00019501-200003000-00004

    CrossRef  Google Scholar 

  6. Dishman, R.K., Farquhar, R.P., Cureton, K.J.: Responses to preferred intensities of exertion in men differing in activity levels. Med. Sci. Sports Exerc. 26(6), 783–790 (1994). https://doi.org/10.1249/00005768-199406000-00019, http://journals.lww.com/00005768-199406000-00019

  7. Nabetani, T., Tokunaga, M.: A new approach to exercise adherence. Health Sci. 23, 103–116 (2001)

    Google Scholar 

  8. Consolvo, S., et al.: Flowers or a robot army?: encouraging awareness and activity with personal, mobile displays. In: UbiComp 2008 - Proceedings of the 10th International Conference on Ubiquitous Computing, pp. 54–63 (2008). https://doi.org/10.1145/1409635.1409644

  9. Klasnja, P., Consolvo, S., McDonald, D.W., Landay, J.A., Pratt, W.: Using mobile and personal sensing technologies to support health behavior change in everyday life: lessons learned. In: AMIA 2009 Symposium Proceedings, pp. 338–342 (2009). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2815473/

  10. Yuasa, S., Kise, K.: Confirmation of the effect of aerobic exercise on English vocabulary memorization. IPSJ SIG Technical Report 2020-HCI-1(10), pp. 1–5 (2020)

    Google Scholar 

  11. Shimizu, Y., Ohnishi, A., Terada, T., Tsukamoto, M.: DeskWalk: an exercise system by replacing key inputs with body movements. In: Proceedings of the 18th International Conference on Advances in Mobile Computing and Multimedia, pp. 202–209 (2020)

    Google Scholar 

  12. Shen, C., Ho, B.J., Srivastava, M.: MiLift: efficient Smartwatch-Based Workout Tracking Using Automatic Segmentation. IEEE Trans. Mob. Comput. 17(7), 1609–1622 (2018). https://doi.org/10.1109/TMC.2017.2775641

    CrossRef  Google Scholar 

  13. Guo, X., Liu, J., Chen, Y.: When your wearables become your fitness mate. Smart Health 16, 100114 (2020). https://doi.org/10.1016/j.smhl.2020.100114

  14. Morris, D., Saponas, T.S., Guillory, A., Kelner, I.: Recofit: using a wearable sensor to find, recognize, and count repetitive exercises. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 3225–3234. CHI 2014, ACM (2014). https://doi.org/10.1145/2556288.2557116

  15. Hao, T., Xing, G., Zhou, G.: RunBuddy: a smartphone system for running rhythm monitoring. UbiComp 2015, 133–144 (2015). https://doi.org/10.1145/2750858.2804293, https://dl.acm.org/doi/pdf/10.1145/2750858.2804293

  16. Griffiths, E., Saponas, T.S., Brush, A.J.B.: Health chair: implicitly sensing heart and respiratory rate. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp 2014 Adjunct, pp. 661–671 (2014). https://doi.org/10.1145/2632048.2632099, http://dl.acm.org/citation.cfm?doid=2632048.2632099

  17. Tan, H.Z., Slivovsky, L.A., Pentland, A.: A sensing chair using pressure distribution sensors. IEEE/ASME Trans. Mechatron. 6(3), 261–268 (2001). https://doi.org/10.1109/3516.951364, http://ieeexplore.ieee.org/document/951364/

  18. Roh, J., Park, H.j., Lee, K., Hyeong, J., Kim, S., Lee, B.: Sitting posture monitoring system based on a low-cost load cell using machine learning. Sensors 18(2), 208 (2018). https://doi.org/10.3390/s18010208, http://www.mdpi.com/1424-8220/18/1/208

  19. Ren, X., Yu, B., Lu, Y., Chen, Y., Pu, P.: HealthSit: designing posture-based interaction to promote exercise during fitness breaks. Int. J. Hum. Comput. Interact. 35(10), 870–885 (2019). https://doi.org/10.1080/10447318.2018.1506641

    CrossRef  Google Scholar 

  20. Nagano, S.: Get rid of your busy schedule and get some exercise! One-minute exercise diet, PHP Institute (2003). (in Japanese)

    Google Scholar 

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Correspondence to Kaori Fujinami .

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Kobayashi, M., Tsuji, A., Fujinami, K. (2022). An Exercise-Promoting System for Exercising While Doing Desk Work. In: Streitz, N.A., Konomi, S. (eds) Distributed, Ambient and Pervasive Interactions. Smart Living, Learning, Well-being and Health, Art and Creativity. HCII 2022. Lecture Notes in Computer Science, vol 13326. Springer, Cham. https://doi.org/10.1007/978-3-031-05431-0_19

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  • DOI: https://doi.org/10.1007/978-3-031-05431-0_19

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