Title :
A wrist-worn biosensor system for assessment of neurological status
Author :
Cogan, D. ; Pouyan, M. Baran ; Nourani, M. ; Harvey, J.
Author_Institution :
Quality of Life Technol. Lab., Univ. of Texas at Dallas, Richardson, TX, USA
Abstract :
EEG based monitoring for the purpose of assessing a patient´s neurological status is conspicuous and uncomfortable at best. We are analyzing a set of physiological signals that may be monitored comfortably by a wrist worn device. We have found that these signals and machine based classification allows us to accurately discriminate among four stress states of individuals. Further, we have found a clear change in these signals during the 70 minutes preceding a single convulsive epileptic seizure. Our classification accuracy on all data has been greater than 90% to date.
Keywords :
body sensor networks; electroencephalography; learning (artificial intelligence); medical disorders; medical signal processing; neurophysiology; patient monitoring; signal classification; EEG based monitoring; classification accuracy; machine-based classification; neurological status assessment; patient neurological status; physiological signal analysis; single convulsive epileptic seizure; stress states; time 70 min; wrist worn device; wrist-worn biosensor system; Biomedical monitoring; Conferences; Electroencephalography; Monitoring; Stress; Temperature measurement;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
DOI :
10.1109/EMBC.2014.6944933
