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Persuasive AI Voice-Assisted Technologies to Motivate and Encourage Physical Activity

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Advances in Computer Vision and Computational Biology

Abstract

Lack of physical activity (PA) is one major contributor to the high prevalence of modern-day chronic diseases. In this study, we design and implement an interactive PA motivation program for older adults (65+) and people with chronic conditions by adapting a commercially available artificial intelligence voice-assisted (AIVA) application and activity tracker (Alexa/Echo Show/Fitbit). Customized features are founded on persuasive technology theory and techniques- and evidence-based PA programs. A pilot study with four older adults for 5 days demonstrated moderate to good usability, learnability, satisfaction, and performance and key-persuasive techniques that enhance user experience and goal achievement. The study provides a tested model for PA behavior change using AIVA for feedback, education, and motivational guidance.

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Authors and Affiliations

  1. University of South Carolina, Columbia, SC, USA

    Benjamin Schooley, Dilek Akgun, Prashant Duhoon & Neset Hikmet

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  1. Benjamin Schooley
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  2. Dilek Akgun
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  3. Prashant Duhoon
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  4. Neset Hikmet
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Correspondence to Dilek Akgun .

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Editors and Affiliations

  1. Department of Computer Science, University of Georgia, Athens, GA, USA

    Hamid R. Arabnia

  2. School of Computing and Data Sciences, Wentworth Institute of Technology, Boston, MA, USA

    Leonidas Deligiannidis

  3. Graduate School of Information Science & Engineering, University of Electro-Communications, Chofu, Japan

    Hayaru Shouno

  4. Facultad de Informática - CIC PBA, Universidad Nacional de La Plata, La Plata, Argentina

    Fernando G. Tinetti

  5. Department of Computer Science, Southeastern Louisiana University, Hammond, LA, USA

    Quoc-Nam Tran

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Schooley, B., Akgun, D., Duhoon, P., Hikmet, N. (2021). Persuasive AI Voice-Assisted Technologies to Motivate and Encourage Physical Activity. In: Arabnia, H.R., Deligiannidis, L., Shouno, H., Tinetti, F.G., Tran, QN. (eds) Advances in Computer Vision and Computational Biology. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-71051-4_29

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