A time–frequency based approach for generalized phase synchrony assessment in nonstationary multivariate signals

This paper establishes the relevance of the GePS measure for quantifying the global phase synchronization within multivariate nonstationary signals such as newborn EEG using an IP/IF estimation approach in the time-frequency (T-F) domain. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated).This paper proposes a new approach to estimate the phase synchrony among nonstationary multivariate signals using the linear relationships between their instantaneous frequency (IF) laws. For cases where nonstationary signals are multi-component, a decomposition method like multi-channel empirical mode decomposition (MEMD) is used to simultaneously decompose the multi-channel signals into their intrinsic mode functions (IMFs). We then apply the Johansen method on the IF laws to assess the phase synchrony within multivariate nonstationary signals. The proposed approach is validated first using multi-channel synthetic signals. The method is then used for quantifying the inter-hemispheric EEG asynchrony during ictal and inter-ictal periods using a newborn EEG seizure/non-seizure database of five subjects. For this application, pair-wise phase synchrony measures may not be able to account for phase interactions between multiple channels. Furthermore, the classical definition of phase synchrony, which is based on the rational relationships between phases, may not reveal the hidden phase interdependencies caused by irrational long-run relationships. We evaluate the performance of the proposed method using the differentiation of unwrapped phase as well as other IF estimation techniques. The results obtained on newborn EEG signals confirm that the generalized phase synchrony within EEG channels increases significantly during ictal periods. A statistically consistent phase coupling is also observed within the non-seizure segments supporting the concept of constant inter-hemispheric connectivity in the newborn brain during inter-ictal periods

Detection of perinatal hypoxia using time-frequency analysis of heart rate variability signals

This paper presents a time-frequency approach to detect perinatal hypoxia by characterizing the nonstationary nature of heart rate variability (HRV) signals. Quadratic time-frequency distributions (TFDs) are used to represent the HRV signals. Six features based on the instantaneous frequency (IF) of the lower frequency components of HRV signals are selected to establish a classifier using support vector machine. The classifier is trained and tested using the signals recorded from a neonatal piglet model under a controlled hypoxic condition, which provides reliable annotations on the data. The method shows superior performance in the detection of hypoxic epochs with sensitivity (89.8%), specificity (100%) and total accuracy (94.9%) compared with that based on frequency domain features, indicating that nonstationarity should be taken into account for a more accurate assessment of the newborn status with possible hypoxia when analyzing HRV signals

Performance evaluation of multi-component instantaneous frequency estimation techniques for heart rate variability analysis

Accurate instantaneous frequency (IF) estimation of the non-stationary heart rate signal is important in quantifying the heart rate variability (HRV) measures. This study compares the effectiveness of four IF estimation methods in analyzing HRV signals. Specifically, they are the direct localization of the maximal peaks in the signal time-frequency distribution (TFD), IF estimation based on component linking technique in the TFD, IF estimation using the TFD with optimal windows based on intersection of confidence intervals rule and complex demodulation. Results of applying the IF estimation methods to synthesized and real piglet HRV signals reveal that, the approach using component linking technique outperform the other techniques with respect to the accuracy and implementation. It provides new insights in studying the evolution of the autonomic nervous regulation of the cardiovascular function over time.Scopu

Passive detection of accelerometer-recorded fetal movements using a time–frequency signal processing approach

This paper presents a proof-of-concept that shows that the use of accelerometers can be used for the detection of Fetal Movements. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated).This paper describes a multi-sensor fetal movement (FetMov) detection system based on a time–frequency (TF) signal processing approach. Fetal motor activity is clinically useful as a core aspect of fetal screening for well-being to reduce the current high incidence of fetal deaths in the world. FetMov are present in early gestation but become more complex and sustained as the fetus progresses through gestation. A decrease in FetMov is an important element to consider for the detection of fetal compromise. Current methods of FetMov detection include maternal perception, which is known to be inaccurate, and ultrasound imaging which is intrusive and costly. An alternative passive method for the detection of FetMov uses solid-state accelerometers, which are safe and inexpensive. This paper describes a digital signal processing (DSP) based experimental approach to the detection of FetMov from recorded accelerometer signals. The paper provides an overview of the significant measurement and signal processing challenges, followed by an approach that uses quadratic time–frequency distributions (TFDs) to appropriately deal with the non-stationary nature of the signals. The paper then describes a proof-of-concept with a solution consisting of a detection method that includes (1) a new experimental set-up, (2) an improved data acquisition procedure, and (3) a TF approach for the detection of FetMov including TF matching pursuit (TFMP) decomposition and TF matched filter (TFMF) based on high-resolution quadratic TFDs. Detailed suggestions for further refinement are provided with preliminary results to establish feasibility, and considerations for application to clinical practice are reviewed

Ibuprofen inhibits neuroinflammation and attenuates white matter damage following hypoxia-ischemia in the immature rodent brain

Damage to major white matter tracts is a hallmark mark feature of hypoxic ischemic (HI) brain injury in the preterm neonate. There is, however, no therapeutic intervention to treat this injury. Neuroinflammation is thought to play a prominent role in the pathogenesis of the HI-induced white matter damage but identification of the key mediators that constitute the inflammatory response remain to be fully elucidated. Cyclooxygenase enzymes (COX-1 and COX-2) are candidate neuroinflammatory mediators that may contribute to the HI-induced demise of early oligodendrocyte progenitors and myelination. We investigated whether ibuprofen, a non-steroidal anti-inflammatory drug that inhibits COX enzymes, can attenuate neuroinflammation and associated white matter damage incurred in a rodent model of preterm HI. On postnatal day 3 (P3), HI was produced (right carotid artery ligation and 30 mm 6% O(2)). An initial dose of ibuprofen (100 mg,/kg, s.c.) was administered 2 h after HI followed by a maintenance dose (50 mg/kg, s.c.) every 24 h for 6 days. Post-HI ibuprofen treatment significantly attenuated the P3 HI-induced increases in COX-2 protein expression as well as interleukin-1beta (IL-1 beta) and tumour necrosis factor-alpha (TNF-alpha) levels in the brain. Ibuprofen treatment also prevented the HI-induced loss O4- and O1-positive oligodendrocyte progenitor cells and myelin basic protein (MBP)-positive myelin content one week after P3 HI. These findings suggest that a repeated, daily, ibuprofen treatment regimen administered after an HI insult may be a potential therapeutic intervention to prevent HI-induced damage to white matter progenitors and early myelination in the preterm neonate. (C) 2011 Elsevier B.V. All rights reserved

Validation of an MRI brain injury and growth scoring system in very preterm infants scanned at 29-to 35-week postmenstrual age

Background and Purpose: The diagnostic and prognostic potential of brain MR imaging before term-equivalent age is limited until valid MR imaging scoring systems are available. This study aimed to validate an MR imaging scoring system of brain injury and impaired growth for use at 29 to 35 weeks postmenstrual age in infants born at < 31 weeks gestational age. Materials and Methods: Eighty-three infants in a prospective cohort study underwent early 3T MR imaging between 29 and 35 weeks' postmenstrual age (mean, 32 +2 ± 1 +3 weeks; 49 males, born at median gestation of 28 +4 weeks; range, 23 +6 -30 +6 weeks; mean birthweight, 1068±312 g). Seventy-seven infants had a secondMRscan at term-equivalent age (mean, 40 +6 ±1 +3 weeks). Structural images were scored using a modified scoring system which generated WM, cortical gray matter, deep gray matter, cerebellar, and global scores. Outcome at 12-months corrected age (mean, 12 months 4 days ± 1 +2 weeks) consisted of the Bayley Scales of Infant and Toddler Development, 3rd ed. (Bayley III), and the Neuro-Sensory Motor Developmental Assessment. Results: Early MR imaging global, WM, and deep gray matter scores were negatively associated with Bayley III motor (regression coefficient for global score ß =-1.31; 95% CI,-2.39 to-0.23; P = .02), cognitive (ß =-1.52; 95% CI,-2.39 to-0.65; P < .01) and the Neuro-Sensory Motor Developmental Assessment outcomes (ß =-1.73; 95% CI,-3.19 to-0.28; P = .02). Early MR imaging cerebellar scores were negatively associated with the Neuro-Sensory Motor Developmental Assessment (ß =-5.99; 95% CI,-11.82 to-0.16; P = .04). Results were reconfirmed at term-equivalent-age MR imaging. Conclusions: This clinically accessible MR imaging scoring system is valid for use at 29 to 35 weeks postmenstrual age in infants born very preterm. It enables identification of infants at risk of adverse outcomes before the current standard of term-equivalent age