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BackgroundGreater adoption of wearable devices with multiple sensors may enhance personalized health monitoring, facilitate early detection of some diseases, and further scale up population health screening. However, few studies have explored the utility of data from wearable fitness trackers in cardiovascular and metabolic disease risk prediction. ObjectiveThis study aimed to investigate the associations between a range of activity metrics derived from a wearable consumer-grade fitness tracker and major modifiable biomarkers of cardiometabolic disease in a working-age population. MethodsThis was a cross-sectional study of 83 working adults. Participants wore Fitbit Charge 2 for 21 consecutive days and went through a health assessment, including fasting blood tests. The following clinical biomarkers were collected: BMI, waist circumference, waist-to-hip ratio, blood pressure, triglycerides (TGs), high-density lipoprotein (HDL) and low-density lipoprotein cholesterol, and blood glucose. We used a range of wearable-derived metrics based on steps, heart rate (HR), and energy expenditure, including measures of stability of circadian activity rhythms, sedentary time, and time spent at various intensities of physical activity. Spearman rank correlation was used for preliminary analysis. Multiple linear regression adjusted for potential confounders was used to determine the extent to which each metric of activity was associated with continuous clinical biomarkers. In addition, pairwise multiple regression was used to investigate the significance and mutual dependence of activity metrics when two or more of them had significant association with the same outcome from the previous step of the analysis. ResultsThe participants were predominantly middle aged (mean age 44.3 years, SD 12), Chinese (62/83, 75%), and male (64/83, 77%). Blood biomarkers of cardiometabolic disease (HDL cholesterol and TGs) were significantly associated with steps-based activity metrics independent of age, gender, ethnicity, education, and shift work, whereas body composition biomarkers (BMI, waist circumference, and waist-to-hip ratio) were significantly associated with energy expenditure–based and HR-based metrics when adjusted for the same confounders. Steps-based interdaily stability of circadian activity rhythm was strongly associated with HDL (beta=5.4 per 10% change; 95% CI 1.8 to 9.0; P=.005) and TG (beta=−27.7 per 10% change; 95% CI −48.4 to −7.0; P=.01). Average daily steps were negatively associated with TG (beta=−6.8 per 1000 steps; 95% CI −13.0 to −0.6; P=.04). The difference between average HR and resting HR was significantly associated with BMI (beta=−.5; 95% CI −1.0 to −0.1; P=.01) and waist circumference (beta=−1.3; 95% CI −2.4 to −0.2; P=.03). ConclusionsWearable consumer-grade fitness trackers can provide acceptably accurate and meaningful information, which might be used in the risk prediction of cardiometabolic disease. Our results showed the beneficial effects of stable daily patterns of locomotor activity for cardiometabolic health. Study findings should be further replicated with larger population studies.

The stiffness and strength properties of freshly poured concrete develop over time as the concrete hardens due to curing. The monitoring of such properties therefore enables timely construction decisions such as formwork removal. Traditional point-in-time destructive tests can be cumbersome, while continuous non-destructive testing is desirable. Piezoelectric-based electromechanical impedance (EMI) and wave propagation (WP) techniques fall into the latter, and they have been verified for monitoring concrete properties during curing in the laboratory. This paper reports the first field application of the EMI and WP techniques for monitoring concrete curing, where smart aggregate (SA) sensors are embedded into concrete pour strips of a multi-storey residential building during construction. For comparison and verification purposes, destructive compression and non-destructive ultrasonic pulse velocity (UPV) tests were conducted. Results obtained from both EMI and WP techniques were consistent and repeatable. They were also comparable to the UPV result, and they showed a close correlation to the compressive strength tests. The current study has also revealed that the electrical signatures acquired from the EMI and WP techniques have a linear relationship. EMI-based and WP-based semi-analytical models (and their derivations) that can quantify the compressive strength and modulus of elasticity of concrete at various curing durations are also presented. This reported study ultimately demonstrates the applicability and practical application of the EMI and WP techniques for real-time measurements, bridging the gap between laboratory-based studies and field applications. [ABSTRACT FROM AUTHOR]