Stress Recognition Using Photoplethysmogram Signal
This study proposed a novel method of stress recognition using photopletysmogram (PPG) signal. PPG devices are now widely used because it is convenient, low powered, cheap and also easy to handle due to its small size. A total of 5 subjects were involved in this study. The PPG signals were taken in resting condition using pulse oximetry. The subject then goes through a stressor test in order to record the physiological changes. The data were collected before and after the test was conducted and later extracted. These samples were then categorised using classification techniques to differentiate between normal and stress condition. Based on the experimentation results, the systolic peak value differences of normal and stress conditions are evident.Therefore, the outcome of this study suggest the reliability of implementing PPG signal for stress recognition.
Stress classification based on human electromagnetic radiation analysis
Stress is a feeling of emotional or physical tension due to any events that makes one feel frustrated, angry or nervous. It a situation that trigger particular biological response when encounter a threat or challenge. This paper discussed stress classification based on human electromagnetic radiation (EMR). At first, the collected radiation frequency data is analyzed using multivariate analysis of variance (MANOVA) to identify the significance points for the classification. Then, the data is classified using locally weighted learning (LWL) algorithm. The results show stress classification using EMR based on third eye and throat chakra points obtained accuracy of more than 60%.
Evaluation of buckling load and dynamic performance of steel shear wall retrofitted with strips made of shape memory alloy
One of the most imperfections of the steel shear wall is out of plane displacements that cause severe damage in both structural and non-structural elements. In this paper, the effects of shape-memory alloys on steel shear walls are investigated. First, a numerical analysis using the finite element method in ABAQUS software has been carried out according to an experimental test. The results of the numerical analysis have been verified with experimental results. Next, shape-memory alloy fibers have been added vertically and horizontally to various parts of the steel shear wall. The results show that retrofitting with the shape-memory alloy reduces the out-of-plane displacement of the steel shear wall under both cyclic and seismic loadings. Besides, the buckling load in the steel shear wall increases when it is retrofitted with the shape-memory alloy. Also, the total out-of-plane movement (accumulated absolute displacements) of the steel shear wall and non-structural damage are controlled by the characteristic of a shape-memory alloy material called “super-elastic”.