Nakajima Yuki, Kitayama Asami, Ohta Yuji, Motooka Nobuhisa, Kuno-Mizumura Mayumi, Miyachi Motohiko, Tanaka Shigeho, Ishikawa-Takata Kazuko, Tripette Julien
Department of Human-Environmental Sciences, Ochanomizu University, Bunkyo, Japan.
Department of Performing Arts, Ochanomizu University, Bunkyo, Japan.
JMIR Form Res. 2024 Apr 25;8:e51874. doi: 10.2196/51874.
The self-monitoring of physical activity is an effective strategy for promoting active lifestyles. However, accurately assessing physical activity remains challenging in certain situations. This study evaluates a novel floor-vibration monitoring system to quantify housework-related physical activity.
This study aims to assess the validity of step-count and physical behavior intensity predictions of a novel floor-vibration monitoring system in comparison with the actual number of steps and indirect calorimetry measurements. The accuracy of the predictions is also compared with that of research-grade devices (ActiGraph GT9X).
The Ocha-House, located in Tokyo, serves as an independent experimental facility equipped with high-sensitivity accelerometers installed on the floor to monitor vibrations. Dedicated data processing software was developed to analyze floor-vibration signals and calculate 3 quantitative indices: floor-vibration quantity, step count, and moving distance. In total, 10 participants performed 4 different housework-related activities, wearing ActiGraph GT9X monitors on both the waist and wrist for 6 minutes each. Concurrently, floor-vibration data were collected, and the energy expenditure was measured using the Douglas bag method to determine the actual intensity of activities.
Significant correlations (P<.001) were found between the quantity of floor vibrations, the estimated step count, the estimated moving distance, and the actual activity intensities. The step-count parameter extracted from the floor-vibration signal emerged as the most robust predictor (r=0.82; P<.001). Multiple regression models incorporating several floor-vibration-extracted parameters showed a strong association with actual activity intensities (r=0.88; P<.001). Both the step-count and intensity predictions made by the floor-vibration monitoring system exhibited greater accuracy than those of the ActiGraph monitor.
Floor-vibration monitoring systems seem able to produce valid quantitative assessments of physical activity for selected housework-related activities. In the future, connected smart home systems that integrate this type of technology could be used to perform continuous and accurate evaluations of physical behaviors throughout the day.
身体活动的自我监测是促进积极生活方式的有效策略。然而，在某些情况下准确评估身体活动仍然具有挑战性。本研究评估了一种新型的地面振动监测系统，以量化与家务相关的身体活动。
本研究旨在评估一种新型地面振动监测系统的步数和身体行为强度预测与实际步数和间接量热法测量结果相比的有效性。还将预测的准确性与研究级设备（ActiGraph GT9X）的准确性进行比较。
位于东京的Ocha-House作为一个独立的实验设施，配备了安装在地板上的高灵敏度加速度计以监测振动。开发了专用的数据处理软件来分析地面振动信号并计算三个定量指标：地面振动量、步数和移动距离。共有10名参与者进行了4种不同的与家务相关的活动，腰部和手腕都佩戴ActiGraph GT9X监测器，每次佩戴6分钟。同时，收集地面振动数据，并使用道格拉斯袋法测量能量消耗，以确定活动的实际强度。
在地面振动量、估计步数、估计移动距离和实际活动强度之间发现了显著相关性（P<0.001）。从地面振动信号中提取的步数参数是最可靠的预测指标（r=0.82；P<0.001）。纳入多个从地面振动中提取的参数的多元回归模型与实际活动强度显示出很强的相关性（r=0.88；P<0.001）。地面振动监测系统进行的步数和强度预测都比ActiGraph监测器的预测更准确。
地面振动监测系统似乎能够对选定的与家务相关的活动进行有效的身体活动定量评估。未来，集成这种技术的联网智能家居系统可用于全天对身体行为进行连续和准确的评估。
