Search

One of the most popular types of personal health device is the activity monitor, which is attached to the user’s wrist or waist in order to measure physical activity data such as exercise time/duration and calorie consumption. However, for the purpose of checking the physical conditions, medical staffs may want to check remotely the movement of a patient’s body parts. Given that it has an activity sensor to measure the speed of a user’s movement, an activity monitor can also be used to track the movement of a user’s body part. In this paper, a multipurpose smart activity monitoring system for personalized health services is proposed. The purpose of the system is twofold. The first purpose is to perform easily smart monitoring of a user’s physical activity. The system proposed in this paper is referred to as “smart” because the personal activity monitor can be managed remotely through the management commands issued by the monitoring server. The personal data, device data or programs installed in the personal activity monitor can be updated remotely by the monitoring server or medical staffs, and error reports can be delivered to the server or the medical staffs for personalized health services. To do this, the ISO/IEEE 11073 and OMA DM communication protocols are extended and the protocol transformation between two protocols is performed. The second purpose is to perform convenient motion tracking of a user’s body part in order to monitor the speed of the body part, as well as its tracking path. The system is also referred as “multipurpose” since the activity monitor can be used in motion tracking as well as in activity monitoring. The objects in motion to be tracked remotely by medical staffs can be a human body part. To do this, in addition to the acceleration sensor, a gyro sensor is installed in the personal activity monitor and the movement data captured by the activity monitor is analyzed to show 2-way views of the movement of the body part on which the activity monitor is attached. Then medical staffs can check remotely the physical conditions of the body part in various ways. [ABSTRACT FROM AUTHOR]

Abstract: Many studies in biomedical fields are carried out using diagnoses reported by different raters to evaluate the agreement of multiple ratings. The most popular indices of agreement are kappa measures including Cohen’s kappa and weighted kappa for binary and ordinal outcomes, respectively. However, when raters assess the same observation on two or more occasions, these ratings are dependent and so the correlation between kappa estimates must be considered when making inferences. In this paper, we focus on testing the equality of correlated kappa coefficients using the generalized estimating equation (GEE) approach and applying quasi-likelihood under the independence model criterion (QIC) measures for model selection. Simulation studies are conducted to compare the performance between GEE with and without QIC measures, weighted least squares (WLS) and independence approaches for binary and ordinal data. Two applications are illustrated: a comparison of two methods for assessing cervical ectopy, and similarity in myopic status for monozygous twins and dizygous twins. We conclude that when performing the QIC model-selection procedure in GEE models and taking into account the correlation between kappa measures, it leads to nominal type I errors and larger powers. [Copyright &y& Elsevier]