%0 Journal Article
%@ 2561-326X
%I JMIR Publications
%V 8
%N 
%P e51874
%T Objective Assessment of Physical Activity at Home Using a Novel Floor-Vibration Monitoring System: Validation and Comparison With Wearable Activity Trackers and Indirect Calorimetry Measurements
%A Nakajima,Yuki
%A Kitayama,Asami
%A Ohta,Yuji
%A Motooka,Nobuhisa
%A Kuno-Mizumura,Mayumi
%A Miyachi,Motohiko
%A Tanaka,Shigeho
%A Ishikawa-Takata,Kazuko
%A Tripette,Julien
%+ Center for Interdisciplinary AI and Data Science, Ochanomizu University, 2-1-1 Otsuka, Bunkyo, 112-8610, Japan, 81 03 5978 2032 ext 2032, tripette.julien@ocha.ac.jp
%K smart home system
%K physical behavior
%K physical activity
%K activity tracker
%K floor vibration
%K housework-related activity
%K home-based activity
%K mobile phone
%D 2024
%7 25.4.2024
%9 Original Paper
%J JMIR Form Res
%G English
%X Background: 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. Objective: 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). Methods: 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. Results: 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 (r2=0.82; P<.001). Multiple regression models incorporating several floor-vibration–extracted parameters showed a strong association with actual activity intensities (r2=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. Conclusions: 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. 
%M 38662415
%R 10.2196/51874
%U https://formative.jmir.org/2024/1/e51874
%U https://doi.org/10.2196/51874
%U http://www.ncbi.nlm.nih.gov/pubmed/38662415