EEG-Based Person Identification during Escalating Cognitive Load.

With the development of human society, there is an increasing importance for reliable person identification and authentication to protect a person's material and intellectual property. Person identification based on brain signals has captured substantial attention in recent years. These signals are characterized by original patterns for a specific person and are capable of providing security and privacy of an individual in biometric identification. This study presents a biometric identification method based on a novel paradigm with accrual cognitive brain load from relaxing with eyes closed to the end of a serious game, which includes three levels with increasing difficulty. The used database contains EEG data from 21 different subjects. Specific patterns of EEG signals are recognized in the time domain and classified using a 1D Convolutional Neural Network proposed in the MATLAB environment. The ability of person identification based on individual tasks corresponding to a given degree of load and their fusion are examined by 5-fold cross-validation. Final accuracies of more than 99% and 98% were achieved for individual tasks and task fusion, respectively. The reduction of EEG channels is also investigated. The results imply that this approach is suitable to real applications.

Postoperative pain management in geriatric patients after cholecystectomy and studies of glycemia and cortisol levels.

OBJECTIVE: The purpose of the study was to follow up the cortisol levels in relation to the postoperative pain intensity, its levels after treatment with opiate and non-opiate analgesics, and to monitor the relationship between the blood glucose and cortisol levels. Another goal was to optimize the postoperative analgesia of geriatric patients with the known combinations of analgesics. METHODS: The cohort comprised 28 geriatric patients undergoing laparoscopic cholecystectomy. The patients were divided according to the intensity of postoperative pain into the groups with opiate and non-opiate analgesia. Furthermore, they were divided according to their physical condition (ASA classification) into two groups, ASA 2 and ASA 3. We evaluated three values ​​of blood glucose levels, on the day before surgery, on the operative and the first postoperative days and those of cortisol on the day of surgery. RESULTS: The patients had the blood glucose levels without significant deviation during the three days of measurements. The cortisol levels increased with the intensity of postoperative pain. High levels of cortisol were observed not only in the patients, who experienced acute pain after non-optimal postoperative analgesia, but also in those treated with strong opiates in the immediate postoperative period. The patients with mild pain intensity, treated with a combination of non-opiate analgesics, had the lowest values. The role of the patient's gender in both blood glucose and cortisol levels was not observed. CONCLUSION: The cortisol levels have not corresponded so much with the assessment of acute postoperative pain as with the stress that was evoked in the patient due to hospitalization and fear of surgery. It is crucial to eliminate as much as possible all the stressors that can affect the cortisol levels and thus the blood glucose levels (Fig. 6, Ref. 25).