Machine Learning Techniques for Personalized Detection of Epileptic Events in Clinical Video Recordings.

Continuous patient monitoring is essential to achieve an effective and optimal patient treatment in the intensive care unit. In the specific case of epilepsy it is the only way to achieve a correct diagnosis and a subsequent optimal medication plan if possible. In addition to automatic vital sign monitoring, epilepsy patients need manual monitoring by trained personnel, a task that is very difficult to be performed continuously for each patient. Moreover, epileptic manifestations are highly personalized even within the same type of epilepsy. In this work we assess two machine learning methods, dictionary learning and an autoencoder based on long short-term memory (LSTM) cells, on the task of personalized epileptic event detection in videos, with a set of features that were specifically developed with an emphasis on high motion sensitivity. According to the strengths of each method we have selected different types of epilepsy, one with convulsive behaviour and one with very subtle motion. The results on five clinical patients show a highly promising ability of both methods to detect the epileptic events as anomalies deviating from the stable/normal patient status.

Laryngeal morphological changes due to gastroesophageal reflux disease.

UNLABELLED: Chronic laryngitis may have life impact on professional voice users. Besides smoking and excessive alcohol intake, GERD is a determiniing factor in the etiology of dysphonia. AIM: To evaluate the laryngeal alteration due to GERD in professional voice users. MATERIAL AND METHODS: The study included 96 vocal professionals (teachers, actors, singers and priests), 58 males and 38 females, with a mean age of 38.3 +/- 7.5 years, presented for chronic laryngeal symptoms. The patients filled out a standardized questionnaire and were examined laryngoscopically. RESULTS: Laryngeal changes were scaled 0 (absence) to 7 (maximum) - arytenoid edema (5.07 +/- 1.08), interarytenoid edema (6.18 +/- 1.12), vocal folds edema (5.67 +/- 1.04), ventricular bands edema (4.96 +/- 0.97), laryngeal edema 4.12 +/- 0.83). CONCLUSIONS: Laryngoscopic changes may suggest the concomitance of GERD in professional voice users with dysphonia.