RESUMO
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.
RESUMO
BACKGROUND: Diabetic patients present higher level of red blood cell (RBC) aggregation contributing to the development of vascular complications. While it has been suggested that this hematology/rheology parameter could bring additional prognostic information for the management of those patients, RBC aggregation screening is not included as a clinical practice. Most medical centers are not equipped to measure properly this parameter, although sedimentation tests can bring some indication. Here, we aimed at evaluating the feasibility of using ultrasound to assess in-vivo hyper-aggregation in type 2 diabetic patients. RESEARCH DESIGN AND METHODS: Seventeen diabetic patients and 15 control subjects underwent ultrasound measurements of RBC aggregation in both cephalic and great saphenous veins. Non-invasive in-vivo ultrasound measurements were performed using a newly developed cellular imaging technique, the structure factor size and attenuation estimator (SFSAE). Comparisons with an ex-vivo gold standard rheometry technique were done, along with measurements of pro-aggregating plasma molecule concentrations. RESULTS: In-vivo RBC aggregation was significantly higher in diabetic patients compared with controls for cephalic vein measurements, while a trend (p = 0.055) was noticed in the great saphenous vein. SFSAE measurements were correlated with gold standard in-vitro measures, fibrinogen and C-reactive protein plasma concentrations. CONCLUSION: RBC aggregation can be measured in-vivo in diabetic patients using ultrasound. Prospective studies are needed to determine whether the SFSAE method could help clinicians in the early management of vascular complications in this patient population.