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SWear: Sensing Using WEARables. Generalized Human Crowdsensing on Smartwatches

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Advances in Usability, User Experience, Wearable and Assistive Technology (AHFE 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1217))

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Abstract

In this work, we present SWear, a generalized human crowdsensing platform to collect human behavior data on smartwatches. It uses the stand-alone capabilities of smartwatches to collect data without being connected to smartphones. SWear collects both sensor data (e.g. GPS and audio) and self-reported survey data through micro surveys administered on the watch. SWear has been validated in multiple studies to understand the relationship between humans and their context.

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References

  1. Seneviratne, S., Hu, Y., Nguyen, T., Lan, G., Khalifa, S., Thilakarathna, K., Seneviratne, A.: A survey of wearable devices and challenges. IEEE Commun. Surv. Tutorials 19(4), 2573–2620 (2017)

    Article  Google Scholar 

  2. Ganti, R., Ye, F., Lei, H.: Mobile crowdsensing: current state and future challenges. IEEE Commun. Mag. 49(11), 32–39 (2011). https://doi.org/10.1109/mcom.2011.6069707

  3. Cai, L., Boukhechba, M., Kaur, N., Wu, C., Barnes, L.E., Gerber, M.S.: Adaptive passive mobile sensing using reinforcement learning. In: 2019 IEEE 20th International Symposium on A World of Wireless, Mobile and Multimedia Networks. IEEE (2019)

    Google Scholar 

  4. Xiong, H., Huang, Y., Barnes, L.E., Gerber, M.S.: Sensus: a cross-platform, general-purpose system for mobile crowdsensing in human-subject studies. In: Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 415–426 (2016)

    Google Scholar 

  5. Boukhechba, M., Daros, A.R., Fua, K., Chow, P.I., Teachman, B.A., Barnes, L.E.: DemonicSalmon: Monitoring mental health and social interactions of college students using smartphones. Smart Health 9–10, 192–203 (2018)

    Article  Google Scholar 

  6. Boukhechba, M., Cai, L., Wu, C., Barnes, L.E.: ActiPPG: Using deep neural networks for activity recognition from wrist-worn photoplethysmography (PPG) sensors. Smart Health 14, 100082 (2019)

    Article  Google Scholar 

  7. Homdee, N., Boukhechba, M., Feng, Y.W., Kramer, N., Lach, J., Barnes, L.E.: Enabling Smartphone-based Estimation of Heart Rate. arXiv preprint arXiv:1912.08910 (2019)

  8. Boukhechba, M., Chow, P., Fua, K., Teachman, B.A., Barnes, L.E.: Predicting social anxiety from global positioning system traces of college students: feasibility study. JMIR Mental Health 5(3), e10101 (2018)

    Article  Google Scholar 

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Correspondence to Mehdi Boukhechba .

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Boukhechba, M., Barnes, L.E. (2020). SWear: Sensing Using WEARables. Generalized Human Crowdsensing on Smartwatches. In: Ahram, T., Falcão, C. (eds) Advances in Usability, User Experience, Wearable and Assistive Technology. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1217. Springer, Cham. https://doi.org/10.1007/978-3-030-51828-8_67

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  • DOI: https://doi.org/10.1007/978-3-030-51828-8_67

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-51827-1

  • Online ISBN: 978-3-030-51828-8

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