Soulard Julie, Kairy Dahlia, Walha Roua, Duclos Cyril, Nadeau Sylvie, Auger Claudine
Centre de recherche interdisciplinaire en réadaptation du Montréal métropolitain (CRIR) - Institut universitaire sur la réadaptation en déficience physique de Montréal (IURDPM) du Centre intégré universitaire de santé et de services sociaux du Centre-Sud-de-l'Île-de-Montréal (CCSMTL), Université de Montréal, Institut de Réadaptation Gingras Lindsay de Montréal, 6300 avenue de Darlington, Montréal, QC, H3S 2J4, Canada, 1 514-343-6111.
JMIR Rehabil Assist Technol. 2024 Dec 31;11:e64121. doi: 10.2196/64121.
BACKGROUND: Stationary bikes are used in numerous rehabilitation settings, with most offering limited functionalities and types of training. Smart technologies, such as artificial intelligence and robotics, bring new possibilities to achieve rehabilitation goals. However, it is important that these technologies meet the needs of users in order to improve their adoption in current practice. OBJECTIVE: This study aimed to collect professionals' perspectives on the use of smart stationary bikes in rehabilitation. METHODS: Twelve health professionals (age: mean 43.4, SD 10.1 years) completed an online questionnaire and participated in a semistructured interview regarding their needs and expectations before and after a 30-minute session with a smart bike prototype. RESULTS: A content analysis was performed with inductive coding. Seven main themes emerged: (1) bike functionalities (cycling assistance, asymmetric resistance, and forward and backward cycling), (2) interface between bike and users (simple, user-friendly, personalized, with written reminders during training), (3) feedback to users (user and performance data), (4) training programs (preprogrammed and personalized, and algorithmic programs), (5) user engagement (telerehabilitation, group sessions, music, and automatic suggestion of training), (6) the bike as a physical device (dimensions, comfort, setup, screen, etc), and (7) business model (various pricing strategies, training for professionals, and after-sales service). CONCLUSIONS: This study provides an interpretive understanding of professionals' perspectives regarding smart stationary bikes and is the first to identify the expectations of health professionals regarding the development of future bikes in rehabilitation.
背景:健身自行车在众多康复环境中都有使用,但大多数功能和训练类型有限。人工智能和机器人技术等智能技术为实现康复目标带来了新的可能性。然而,这些技术要满足用户需求,才能提高其在当前实践中的应用率。 目的:本研究旨在收集专业人员对智能健身自行车在康复中应用的看法。 方法:12名健康专业人员(年龄:平均43.4岁,标准差10.1岁)完成了一份在线问卷,并参与了一次半结构化访谈,内容涉及他们在使用智能自行车原型进行30分钟训练前后的需求和期望。 结果:采用归纳编码进行内容分析。出现了七个主要主题:(1)自行车功能(骑行辅助、不对称阻力以及向前和向后骑行),(2)自行车与用户之间的界面(简单、用户友好、个性化,训练时有书面提醒),(3)对用户的反馈(用户和性能数据),(4)训练计划(预编程和个性化以及算法程序),(5)用户参与度(远程康复、小组课程、音乐以及训练自动建议),(6)自行车作为物理设备(尺寸、舒适度、设置、屏幕等),以及(7)商业模式(各种定价策略、专业人员培训和售后服务)。 结论:本研究对专业人员对智能健身自行车的看法提供了一种解释性理解,并且首次确定了健康专业人员对未来康复自行车发展的期望。
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