PURPOSE: Most seizure monitoring units use the Gotman algorithm or a variation on it for EEG spike detection, but the effect of various detection parameters on its accuracy has not been well established. The authors report sensitivities and false-positive rates for several different sets of detection parameters. METHODS: Nine patients were studied. For each patient, 6 hours of EEG data were analyzed using five different sets of spike detection parameters including combinations of amplitude thresholds, state-dependent spike detection and advanced artifact rejection. Automated spike detections were compared with spikes found on visual EEG review. RESULTS: Mean spike detection sensitivities for the different parameter sets ranged from 0.09 to 0.34. The highest sensitivity occurred with an amplitude threshold of 4, state-dependent spike detection turned on and advanced artifact rejection turned off. Mean rates of false-positives ranged from 4.2 to 48.6 per hour. The highest false-positive rate occurred with the same set of detection parameters that produced the highest sensitivity. CONCLUSIONS: The sensitivity of spike detection with the Gotman algorithm is relatively low. The data favor using a lower amplitude threshold and not using advanced artifact rejection. The false-positive rate increases with improved sensitivity, but it is still within an acceptable range for clinical application.
PURPOSE: Most seizure monitoring units use the Gotman algorithm or a variation on it for EEG spike detection, but the effect of various detection parameters on its accuracy has not been well established. The authors report sensitivities and false-positive rates for several different sets of detection parameters. METHODS: Nine patients were studied. For each patient, 6 hours of EEG data were analyzed using five different sets of spike detection parameters including combinations of amplitude thresholds, state-dependent spike detection and advanced artifact rejection. Automated spike detections were compared with spikes found on visual EEG review. RESULTS: Mean spike detection sensitivities for the different parameter sets ranged from 0.09 to 0.34. The highest sensitivity occurred with an amplitude threshold of 4, state-dependent spike detection turned on and advanced artifact rejection turned off. Mean rates of false-positives ranged from 4.2 to 48.6 per hour. The highest false-positive rate occurred with the same set of detection parameters that produced the highest sensitivity. CONCLUSIONS: The sensitivity of spike detection with the Gotman algorithm is relatively low. The data favor using a lower amplitude threshold and not using advanced artifact rejection. The false-positive rate increases with improved sensitivity, but it is still within an acceptable range for clinical application.
Authors: Elham Bagheri; Justin Dauwels; Brian C Dean; Chad G Waters; M Brandon Westover; Jonathan J Halford Journal: Clin Neurophysiol Date: 2017-07-18 Impact factor: 3.708
Authors: Maxime O Baud; Jonathan K Kleen; Gopala K Anumanchipalli; Liberty S Hamilton; Yee-Leng Tan; Robert Knowlton; Edward F Chang Journal: Neurosurgery Date: 2018-10-01 Impact factor: 4.654
Authors: Jonathan J Halford; Amir Arain; Giridhar P Kalamangalam; Suzette M LaRoche; Bonilha Leonardo; Maysaa Basha; Nabil J Azar; Ekrem Kutluay; Gabriel U Martz; Wolf J Bethany; Chad G Waters; Brian C Dean Journal: J Clin Neurophysiol Date: 2017-03 Impact factor: 2.177
Authors: Elham Bagheri; Jing Jin; Justin Dauwels; Sydney Cash; M Brandon Westover Journal: Proc IEEE Int Conf Acoust Speech Signal Process Date: 2018-09-13