Validation of the use of Actigraph GT3X accelerometers to estimate energy expenditure in full time manual wheelchair users with spinal cord injury.

STUDY DESIGN: Cross-sectional validation study. OBJECTIVES: The goals of this study were to validate the use of accelerometers by means of multiple linear models (MLMs) to estimate the O2 consumption (VO2) in paraplegic persons and to determine the best placement for accelerometers on the human body. SETTING: Non-hospitalized paraplegics' community. METHODS: Twenty participants (age=40.03 years, weight=75.8 kg and height=1.76 m) completed sedentary, propulsion and housework activities for 10 min each. A portable gas analyzer was used to record VO2. Additionally, four accelerometers (placed on the non-dominant chest, non-dominant waist and both wrists) were used to collect second-by-second acceleration signals. Minute-by-minute VO2 (ml kg(-1) min(-1)) collected from minutes 4 to 7 was used as the dependent variable. Thirty-six features extracted from the acceleration signals were used as independent variables. These variables were, for each axis including the resultant vector, the percentiles 10th, 25th, 50th, 75th and 90th; the autocorrelation with lag of 1 s and three variables extracted from wavelet analysis. The independent variables that were determined to be statistically significant using the forward stepwise method were subsequently analyzed using MLMs. RESULTS: The model obtained for the non-dominant wrist was the most accurate (VO2=4.0558-0.0318Y25+0.0107Y90+0.0051YND2-0.0061ZND2+0.0357VR50) with an r-value of 0.86 and a root mean square error of 2.23 ml kg(-1) min(-1). CONCLUSIONS: The use of MLMs is appropriate to estimate VO2 by accelerometer data in paraplegic persons. The model obtained to the non-dominant wrist accelerometer (best placement) data improves the previous models for this population.

Kaplan-Meier Type Survival Curves for COVID-19: A Health Data Based Decision-Making Tool.

Countries are recording health information on the global spread of COVID-19 using different methods, sometimes changing the rules after a few days. All of them are publishing the number of new individuals infected, recovered and dead individuals, along with some supplementary material. These data are often recorded in a non-uniform manner and do not conform the standard definitions of these variables. In this paper we show that, using data from the first wave of the epidemic (February-June), Kaplan-Meier curves calculated with them could provide useful information on the dynamics of the disease in different countries. We developed our scheme based on the cumulative total number of infected, recovered and dead individuals provided by the countries. We present a robust and simple model to show certain characteristics of the evolution of the dynamic process, showing that the differences in evolution between countries are reflected in the corresponding Kaplan-Meier-type curves. We compare the curves obtained for the most affected countries at that time, with the corresponding interpretation of the properties that distinguish them. The model is revealed as a practical tool for countries in the management of the Healthcare System.