Biomedical subjects

Christopher E Williams

Publications and source records attributed to Christopher E Williams.

3 recordsLinked to original sources

PubMed2006

Seizure detection algorithm for neonates based on wave-sequence analysis.

OBJECTIVE: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. METHODS: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. RESULTS: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. CONCLUSIONS: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. SIGNIFICANCE: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring.

Algorithms↗

PubMed2005

Quantitative electroencephalographic patterns in normal preterm infants over the first week after birth.

BACKGROUND: Currently available tools to assist clinicians with prediction of neurodevelopmental outcome of preterm infants are inadequate. Modified cotside electroencephalography (EEG) has the ability to produce quantitative electrophysiologic measures. These measures may be useful in future prediction of outcome. AIM: To determine patterns of change in quantitative EEG measures in preterm infants during their first week after birth. DESIGN: Observational. SUBJECTS: Preterm infants born at less than 32 weeks completed gestation surviving to discharge with unremarkable serial ultrasound scans. OUTCOME MEASURES: Changes in continuity, amplitude and spectral edge frequency measures of EEGs obtained over the first week after birth. RESULTS: Results of EEGs performed using a novel EEG device on 63 infants are reported here. Their median (range) gestation was 29 (24-31) weeks and birthweight was 1,235 (540-1,980) g. Quantitative measures of EEG continuity increased over the first week after birth from 72 (25-99)% to 92 (54-100)% at the 25 microV threshold, and from 39 (10-87)% to 64 (34-75)% at the 50 microV threshold, both p<0.0001. There was a related 32% increase in median amplitude from 5.8 (2.6-10.6) microV on day 1 to 7.6 (4.3-9.4) microV on day 4, p=0.005. There was a trend for average spectral edge frequency to fall from 10.7 (9.3-12.9) Hz on day 1 to 9.9 (8.1-12.3) Hz on day 3, p=0.06. Each gestational tertile showed similar patterns. CONCLUSIONS: There are consistent changes in quantitative neurophysiologic measures over the first week after birth, and particularly measures of continuity over the first 4 days, in normal preterm infants.

Child Development↗

PubMed2003

Lowered electroencephalographic spectral edge frequency predicts the presence of cerebral white matter injury in premature infants.

OBJECTIVE: Current methods for early identification of cerebral white matter injury in the premature infant at the bedside are inadequate. This study investigated the utility of advanced spectral analysis of the neonatal electroencephalogram (EEG) in the early diagnosis of white matter injury in the premature infant. The critical measurement used, suggested largely by previous studies in animal models, was the spectral edge frequency (SEF), calculated here as the frequency below which 90% of the power in the EEG exists. METHODS: Fifty-nine very low birth weight infants (87% of eligible infants) had electrodes placed over the central and parietal regions (C3, P3, C4, and P4 sites according to the 10-20 international system) for the collection of EEG amplitude, intensity, and SEF. All averaged signals were analyzed off-line using software (Chart Analyzer; BrainZ Instruments, Auckland, NZ). All infants had a magnetic resonance imaging scan at term to identify the presence and severity of white matter injury. RESULTS: There was no significant difference between conventional EEG amplitude and intensity for infants with or without evidence of white matter injury. However, premature infants with increasingly severe white matter injury had progressively lower SEFs compared with infants who did not exhibit white matter injury. CONCLUSIONS: These data suggest that SEF-based measures are useful for defining the presence and severity of white matter injury at the bedside.

Analysis of Variance↗