Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System

Abstract

Considering that the population is aging rapidly, the demand for technology for aging-at-home, which can provide reliable, unobtrusive monitoring of human activity, is expected to expand. This research focuses on improving the solution of the posture detection problem, which is a part of fall detection system. Fall detection, using depth maps obtained by the Microsoft Kinect sensor, is a two-stage method. We concentrate on the first stage of the system, that is, pose recognition from a depth map. For lying pose detection, a new hybrid FRSystem is proposed. In the system, two rule sets are investigated, the first one created based on a domain knowledge and the second induced based on the rough set theory. Additionally, two inference aggregation approaches are considered with and without the knowledge measure. The results indicate that the new axiomatic definition of knowledge measures, which we propose has a positive impact on the effectiveness of inference and the rule induction method reducing the number of rules in a set maintains it.

Handling the Complexity of Computing Maximal Consistent Blocks

“…The estimation of the worst-case of such calculations makes it possible to determine their impact on a system's performance and indicates the upper limit of resources required in practical applications. In the future, we would like to apply this approach in the module of incomplete data mining of a fall detection system [33]. In systems based on sensors, various types of disturbances may occur, caused, for example, by power failure or battery depletion.…”

Federated Similarity-Based Learning with Incomplete Data

“…In our earlier paper [32], we proposed a federated learning approach that could deal with missing data (Figure 1).…”

“…We chose logistic regression with the use of similarity measures in the process of updating the parameters of the model, in contrast to the classically used stochastic gradient descent. Moreover, for the experiment, we modify it to operate on interval data, as in [32].…”

Fuzzy Support Vector Machine based Fall Detection Method for Traumatic Brain Injuries

“…The third part is the defuzzification process that converts the fuzzy sets into crisp values. Despite the availability of several defuzzification methods, the centroid technique remains the most popular among all of them [39,40].…”