TY - JOUR
T1 - Automated electroencephalogram identifies abnormalities in the ED
AU - Naunheim, Rosanne S.
AU - Treaster, Matthew
AU - English, Joy
AU - Casner, Teya
PY - 2011/10/1
Y1 - 2011/10/1
N2 - Background: Advances in analysis of electrical signals have now made it possible to create a handheld electroencephalogram (EEG). Methods: The BrainScope device, currently under development by BrainScope Co, Inc, Washington, DC, was used to assess 153 patients who presented to a tertiary referral hospital with headache or altered mental status. A limited array of 8 adhesive electrodes, similar to electrocardiographic leads, was applied to the forehead of the subjects. The data were analyzed, and the result given by the algorithm was compared with the clinical diagnosis given to the patient. Results: One hundred fifty-three patients were enrolled. The patient was determined to be normal or abnormal using the algorithm in the device, and blinded clinicians determined whether this was accurate. The sensitivity of the device was 96% and the specificity was 87% for detecting abnormality. Conclusions: The automated EEG device may be a useful tool for identifying brain abnormality in the emergency department.
AB - Background: Advances in analysis of electrical signals have now made it possible to create a handheld electroencephalogram (EEG). Methods: The BrainScope device, currently under development by BrainScope Co, Inc, Washington, DC, was used to assess 153 patients who presented to a tertiary referral hospital with headache or altered mental status. A limited array of 8 adhesive electrodes, similar to electrocardiographic leads, was applied to the forehead of the subjects. The data were analyzed, and the result given by the algorithm was compared with the clinical diagnosis given to the patient. Results: One hundred fifty-three patients were enrolled. The patient was determined to be normal or abnormal using the algorithm in the device, and blinded clinicians determined whether this was accurate. The sensitivity of the device was 96% and the specificity was 87% for detecting abnormality. Conclusions: The automated EEG device may be a useful tool for identifying brain abnormality in the emergency department.
UR - http://www.scopus.com/inward/record.url?scp=80053578247&partnerID=8YFLogxK
U2 - 10.1016/j.ajem.2010.03.010
DO - 10.1016/j.ajem.2010.03.010
M3 - Article
C2 - 20825903
AN - SCOPUS:80053578247
SN - 0735-6757
VL - 29
SP - 845
EP - 848
JO - American Journal of Emergency Medicine
JF - American Journal of Emergency Medicine
IS - 8
ER -