Detection and Tracking of Anxiety Related Diseases for Autism Spectrum Disorder Using ECG

摘要

Anxiety distress are excessive or continual panic of everyday circumstances causing behavioral and emotional consequences, eventually leading to diseases like heart attack, epilepsy and dyspnea. Anxiety disorders are common for people with developmental disorders like autism spectrum disorder, cerebral palsy, down syndrome. Patients suffering from these diseases have difficulties in communication and emotional recognition eventually leading to narrow interests and repetitive behavior. Sometimes their ways of communicating any symptoms may not be recognizable by the caretakers, hence building up a need of a non-invasive, continuous, real-time detection and tracking of their ECG signals for prediction of these diseases providing possible medications. Here a system framework based on unscented Kalman filter (UKF) is developed to continuously detect and track the R-R interval for anxiety prediction to make these unpredictable diseases predictable and reducing death tolls with timely treatment.