Physiological sensing based stress analysis during assessment

During an examination, the performance of a student not only depends on the preparation but also depends on cognitive and psychological factors. The present study aims at analysing the dynamics of the mental workload or stress and its impact on students' performance during an examination process. The experiment is designed using a set of multiple choice questions (MCQs) in one of the subject area namely data-structure. The MCQs are selected in three levels of complexity, which are rated by subject matter experts. A total of 13 right-handed graduate students in the specialization of Masters in Computer Application participated in the experiment. In order to get rid of any bias related to the intelligent quotient (IQ), students are taken such that the IQ varies from low to high. Experimental tasks are designed as interleaved sequences of the MCQs of varying complexity levels. During the tasks, Galvanic skin response (GSR) and pulse-oximeter (SPO2) signals are captured to estimate the stress of an individual from electro-dermal changes and heart rate variability (HRV). Apart from the tonic and phasic power of the GSR, fluctuation analysis is performed on the raw GSR signals. The standard deviation of normal-to-normal interval (SDNN) is computed to measure the HRV using the Photoplethysmogram (PPG) signal obtained from the SPO2 device. An estimation of the stress level is done using a score computed by the fluctuation analysis of the GSR signal. Out of the 13 students, the GSR sensor data for the 6 students are found to erroneous and hence only 7 data are analyzed. The methodology used to reject the erroneous data is also presented. Results indicate that there is a strong statistical correlation between the complexity of the MCQs and the GSR signals. Results of HRV analysis provide new insights to guess work during an assessment process.