Invasive or uncomfortable procedures especially during healthcare trigger emotions. Technological development of the equipment and systems for monitoring and recording psychophysiological functions enables continuous observation of changes to a situation responding to a situation. The presented study aimed to focus on the analysis of the individual’s affective state. The results reflect the excitation expressed by the subjects’ statements collected with psychological questionnaires. The research group consisted of 49 participants (22 women and 25 men). The measurement protocol included acquiring the electrodermal activity signal, cardiac signals, and accelerometric signals in three axes. Subjective measurements were acquired for affective state using the JAWS questionnaires, for cognitive skills the DST, and for verbal fluency the VFT. The physiological and psychological data were subjected to statistical analysis and then to a machine learning process using different features selection methods (JMI or PCA). The highest accuracy of the kNN classifier was achieved in combination with the JMI method (81.63%) concerning the division complying with the JAWS test results. The classification sensitivity and specificity were 85.71% and 71.43%.
In the paper a human activity recognition system has been presented based on the data gathered with the smartphone sensors. The acceleration, magnetic field and sound have been registered and four different activities of daily living has been recognized i.e. riding a bike, driving in a car, walking and sitting. Two version of Support Vector Machine (SVM) classifier have been employed and the obtained results are promising.
Keywords Human activity recognition · Smartphones · Support vector machineThe Human Activity Recognition (HAR) systems aim to automatically determine what people do on the basis of signals recorded from different sensors. These systems can be divided into two main types: external and wearable [11].In the first approach the sensors are placed in a fixed position so the people have to interact with the system and they are confined to a certain area. The most popular are video cameras [20]. Typically they can register a 2D images but it can also record a 3D sequences when two or more devices are employed [1,17]. In order to track the human activity also the depths sensors (especially Time-of-Flight cameras) are introduced. The solutions are based on tracking both the whole body [7,14] as well as only it certain parts, in particular joints [19]. Although this approach allows obtaining a full information about the human activity and his/her environment. The image processing methods are very time consuming and not resource-efficient. Moreover, many people are not willing to be monitored permanently, except for the
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