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Understanding Satisfaction Factors of Personalized Body-weight Exercises

Published: 14 October 2023 Publication History

Abstract

COVID-19 has accelerated mobile body-weight fitness services, enabling users to work out at home. Many body-weight exercise recommendation services, claiming to provide advanced personalization using AI technology, have been released. Given that most of these fitness services are self-paced, users’ satisfaction with personalized exercises would greatly influence their commitment and engagement with the service. However, users’ expectations of AI-generated workouts consisting of various body-weight movements have yet to be explored within the HCI community. In this paper, we conducted a Wizard-of-Oz experiment for two weeks with 12 participants to investigate users’ expectations of AI-generated body-weight exercises. Our results show that users expect the personalized system to match their preferred intensity and movement diversity while filtering out movements beyond their capability. We also propose design implications based on the findings.

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    cover image ACM Conferences
    CSCW '23 Companion: Companion Publication of the 2023 Conference on Computer Supported Cooperative Work and Social Computing
    October 2023
    596 pages
    ISBN:9798400701290
    DOI:10.1145/3584931
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 14 October 2023

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    Author Tags

    1. Bodyweight Exercise Personalization
    2. Home Training

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