TY - GEN
T1 - Allergy detection with statistical modelling of HRV-based non-reaction baseline features
AU - Twomey, Niall
AU - Temko, Andrey
AU - Hourihane, Jonathan O.B.
AU - Marnane, William P.
PY - 2011
Y1 - 2011
N2 - This paper investigates the automated classification of oral food challenges ('allergy tests'). The electrocardiograms (ECG) of the subjects being tested for allergies were recorded via a wireless mote, and the QRS complexes were manually annotated and 18 features were extracted from the signals. Principal component analysis was used for feature decorelation and dimensionality reduction and diagonal covariance Gaussian mixture models were used to model non-reaction baseline patient condition. The generated subject independent log likelihood plots were used to separate allergic reaction by means of subject adaptive thresholding. The platform resulted in 87% accuracy of classification with 100% specificity. The algorithm presented can detect allergy up to 30 minutes sooner than the current state of the clinical art allergy detection (7minutes ± 9).
AB - This paper investigates the automated classification of oral food challenges ('allergy tests'). The electrocardiograms (ECG) of the subjects being tested for allergies were recorded via a wireless mote, and the QRS complexes were manually annotated and 18 features were extracted from the signals. Principal component analysis was used for feature decorelation and dimensionality reduction and diagonal covariance Gaussian mixture models were used to model non-reaction baseline patient condition. The generated subject independent log likelihood plots were used to separate allergic reaction by means of subject adaptive thresholding. The platform resulted in 87% accuracy of classification with 100% specificity. The algorithm presented can detect allergy up to 30 minutes sooner than the current state of the clinical art allergy detection (7minutes ± 9).
UR - https://www.scopus.com/pages/publications/84856699441
U2 - 10.1145/2093698.2093832
DO - 10.1145/2093698.2093832
M3 - Conference proceeding
AN - SCOPUS:84856699441
SN - 9781450309134
T3 - ACM International Conference Proceeding Series
BT - Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11
T2 - 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL'11
Y2 - 26 October 2011 through 29 October 2011
ER -