Supplementary Material for: An Exergame-Integrated IoT-Based Ergometer System Delivers Personalized Training Programs for Older Adults and Enhances Physical Fitness: A Pilot Randomized Controlled Trial

<b><i>Introduction:</i></b> Regular physical exercise is believed to counteract the adverse physiological consequences of aging. However, smart fitness equipment specifically designed for older adults is quite rare. Here we designed an exergame-integrated internet of things (IoT)-based ergometer system (EIoT-ergo) that delivers personalized exercise prescriptions for older adults. First, physical fitness was evaluated using the Senior Fitness Test (SFT) application. Then, radio frequency identification (RFID) triggered the EIoT-ergo to deliver the corresponding exercise session based on the individual level of physical fitness. The exercise intensity during each workout was measured to generate the next exercise session. Further, EIoT-ergo provides an exergame to help users control and maintain their optimal cadence while engaging in exercise. <b><i>Methods:</i></b> This was a randomized controlled trial with 1:1 randomization. Participants were older adults, 50+ years of age (<i>N</i> = 35), who are active in their community. Participants in the EIoT-ergo group received a 12-week personalized exercise program delivered by EIoT-ergo for 30 min per session, with 2 sessions per week. Participants in the control group continued with their usual activities. A senior’s fitness test and a health questionnaire were assessed at baseline and at a 13-week reassessment. The Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST) was used to evaluate the satisfaction of EIoT-ergo. <b><i>Results:</i></b> Compared with the control group, the EIoT-ergo group showed significant improvements in muscle strength (time-by-group interaction, sit-to-stand: β = 5.013, <i>p</i> &lt; 0.001), flexibility (back stretch: β = 4.008, <i>p</i> = 0.005; and sit-and-reach: β = 4.730, <i>p</i> = 0.04), and aerobic endurance (2-min step: β = 9.262, <i>p</i> = 0.03). The body composition was also improved in the EIoT-ergo group (body mass index: β = −0.737, <i>p</i> &lt; 0.001; and skeletal muscle index: β = 0.268, <i>p</i> = 0.03). Satisfaction with EIoT-ergo was shown in QUEST, with an average score of 4.4 ± 0.32 (5 for very satisfied). The percentage maximum heart rate in each session also indicated that EIoT-ergo can gradually build up the exercise intensity of users. <b><i>Conclusions:</i></b> EIoT-ergo was developed to provide personal identification, exergames, intelligent exercise prescriptions, and remote monitoring, as well as to significantly enhance the physical fitness of the elderly individuals under study.

<b><i>引言：</i></b> 现有研究认为，规律的体育运动可抵消衰老带来的不良生理影响。然而，专为老年人设计的智能健身设备仍较为稀缺。本研究设计了一款集成健身游戏的物联网（Internet of Things, IoT）测功系统（EIoT-ergo），可为老年人提供个性化运动处方。首先，通过老年体能测试（Senior Fitness Test, SFT）应用程序对参与者的体能状况进行评估；随后，射频识别（Radio Frequency Identification, RFID）技术将根据个体体能水平，触发EIoT-ergo系统执行对应的运动课程。每次运动过程中的运动强度数据将被采集，用于生成下一次的运动课程方案。此外，EIoT-ergo系统搭载健身游戏模块，可帮助使用者在运动过程中控制并维持最优运动节奏。
<b><i>研究方法：</i></b> 本研究采用1:1随机分组的随机对照试验设计。研究招募了35名50岁及以上、活跃于社区的老年人作为参与者（<i>N</i> = 35）。EIoT-ergo组参与者接受由EIoT-ergo系统提供的为期12周的个性化运动方案，每次运动时长30分钟，每周进行2次；对照组参与者则维持其日常活动习惯不变。分别在基线期与13周随访时，对参与者进行老年体能测试与健康问卷调研。采用魁北克辅助技术使用者满意度评估量表（Quebec User Evaluation of Satisfaction with Assistive Technology, QUEST）对EIoT-ergo系统的用户满意度进行评价。
<b><i>研究结果：</i></b> 与对照组相比，EIoT-ergo组在多项体能指标上均获得显著改善：肌肉力量方面（时间×组间交互效应，坐站测试：β=5.013，<i>p</i> < 0.001）、柔韧性方面（背伸测试：β=4.008，<i>p</i>=0.005；坐位体前屈：β=4.730，<i>p</i>=0.04）以及有氧耐力方面（2分钟台阶测试：β=9.262，<i>p</i>=0.03）。EIoT-ergo组的身体成分指标也得到改善：体质量指数：β=-0.737，<i>p</i> < 0.001；骨骼肌指数：β=0.268，<i>p</i>=0.03。QUEST量表结果显示，参与者对EIoT-ergo系统的满意度较高，平均得分为4.4±0.32（满分5分代表非常满意）。每次运动中的最大心率百分比数据也表明，EIoT-ergo系统可逐步提升使用者的运动强度。
<b><i>结论：</i></b> 本研究开发的EIoT-ergo系统具备身份识别、健身游戏、智能运动处方与远程监测等功能，可显著提升研究中老年人的体能水平。