Rathinaswamy B. Govindan

Integrated Approach for Fetal QRS Detection

Fetal magnetocardiography provides reliable signals of the fetal heart dynamics with high temporal resolution that can be used in a clinical setting. We present a robust Hilbert transform method for extraction of the fetal heart rate. Our method may be applied to signals derived from a single channel or an array of channels. In the case of multichannel data, the channels can be combined to improve signal-to-noise ratio for the extraction of fetal heart data. The method is inherently insensitive to fetal position or movement and, in addition, can be automated. We demonstrate that the determination of R-wave timing is relatively insensitive to waveform morphology. The method can also be applied if the data were preprocessed by independent component analysis (ICA). We compared the Hilbert method, ICA, ICA + Hilbert, and raw signals and found that the Hilbert method gave the best overall performance. We demonstrated that there were approximately 171 errors in 46 789 fetal heart beats.

Adaptive rule based fetal QRS complex detection using hilbert transform

In this paper we introduce an adaptive rule based QRS detection algorithm using the Hilbert transform (adHQRS) for fetal magnetocardiography processing. Hilbert transform is used to combine multiple channel measurements and the adaptive rule based decision process is used to eliminate spurious beats. The algorithm has been tested with a large number of datasets and promising results were obtained.

A Novel Approach to Track Fetal Movement Using Multi-sensor Magnetocardiographic Recordings

Changes in fetal magnetocardiographic (fMCG) signals are indicators for fetal body movement. We propose a novel approach to reliably extract fetal body movements based on the field strength of the fMCG signal independent of its frequency. After attenuating the maternal MCG, we use a Hilbert transform approach to identify the R-wave. At each R-wave, we compute the center-of-gravity (cog) of the coordinate positions of MCG sensors, each weighted by the magnitude of the R-wave amplitude recorded at the corresponding sensor. We then define actogram as the distance between the cog computed at each R-wave and the average of the cog from all the R-waves in a 3-min duration. By applying a linear de-trending approach to the actogram we identify the fetal body movement and compare this with the synchronous occurrence of the acceleration in the fetal heart rate. Finally, we apply this approach to the fMCG recorded simultaneously with ultrasound from a single subject and show its improved performance over the QRS-amplitude based approach in the visually verified movements. This technique could be applied to transform the detection of fetal body movement into an objective measure of fetal health and enhance the predictive value of prevalent clinical testing for fetal wellbeing.

Heart rate variability in encephalopathic newborns during and after therapeutic hypothermia

Objective:To evaluate whether heart rate variability (HRV) measures are predictive of neurological outcome in babies with hypoxic ischemic encephalopathy (HIE).Study Design:This case–control investigation included 20 term encephalopathic newborns treated with systemic hypothermia in a regional neonatal intensive care unit. Electrocardiographic data were collected continuously during hypothermia. Spectral analysis of beat-to-beat heart rate interval was used to quantify HRV. HRV measures were compared between infants with adverse outcome (death or neurodevelopmental impairment at 15 months, n=10) and those with favorable outcome (survivors without impairment, n=10).Result:HRV differentiated infants by outcome during hypothermia through post-rewarming, with the best distinction between groups at 24 h and after 80 h of life.Conclusion:HRV during hypothermia treatment distinguished HIE babies who subsequently died or had neurodevelopmental impairment from intact survivors. This physiological biomarker may identify infants in need of adjuvant neuroprotective interventions. These findings warrant further investigation in a larger population of infants with HIE.

Habituation of visual evoked responses in neonates and fetuses: A MEG study

In this study we aimed to develop a habituation paradigm that allows the investigation of response decrement and response recovery and examine its applicability for measuring the habituation of the visually evoked responses (VERs) in neonatal and fetal magnetoencephalographic recordings. Two paradigms, one with a long and one with a short inter-train interval (ITI), were developed and tested in separate studies. Both paradigms consisted of a train of four light flashes; each train being followed by a 500Hz burst tone. Healthy pregnant women underwent two prenatal measurements and returned with their babies for a neonatal investigation. The amplitudes of the neonatal VERs in the long-ITI condition showed within-train response decrement. An increased response to the auditory dishabituator was found confirming response recovery. In the short-ITI condition, neonatal amplitude decrement could not be demonstrated while response recovery was present. In both ITI conditions, the response rate of the cortical responses was much lower in the fetuses than in the neonates. Fetal VERs in the long-ITI condition indicate amplitude decline from the first to the second flash with no further decrease. The long-ITI paradigm might be useful to investigate habituation of the VERs in neonates and fetuses, although the latter requires precaution.

Correlation between fetal brain activity patterns and behavioral states: An exploratory fetal magnetoencephalography study

The fetal brain remains inaccessible to neurophysiological studies. Magnetoencephalography (MEG) is being assessed to fill this gap. We performed 40 fetal MEG (fMEG) recordings with gestational ages (GA) ranging from 30 to 37 weeks. The data from each recording were divided into 15 second epochs which in turn were classified as continuous (CO), discontinuous (DC), or artifact. The fetal behavioral state, quiet or active sleep, was determined using previously defined criteria based on fetal movements and heart rate variability. We studied the correlation between the fetal state, the GA and the percentage of CO and DC epochs. We also analyzed the spectral edge frequency (SEF) and studied its relation with state and GA. We found that the odds of a DC epoch decreased by 6% per week as the GA increased (P = 0.0036). This decrease was mainly generated by changes during quiet sleep, which showed 52% DC epochs before a 35 week GA versus 38% after 35 weeks (P = 0.0006). Active sleep did not show a significant change in DC epochs with GA. When both states were compared for MEG patterns within each GA group (before and after 35 weeks), the early group was found to have more DC epochs in quiet sleep (54%) compared to active sleep (42%) (P = 0.036). No significant difference in DC epochs between the two states was noted in the late GA group. Analysis of SEF showed a significant difference (P = 0.0014) before and after a 35 week GA, with higher SEF noted at late GA. However, when both quiet and active sleep states were compared within each GA group, the SEF did not show a significant difference. We conclude that fMEG shows reproducible variations in gross features and frequency content, depending on GA and behavioral state. Fetal MEG is a promising tool to investigate fetal brain physiology and maturation.

Extraction, quantification and characterization of uterine magnetomyographic activity--a proof of concept case study.

OBJECTIVE The objective was to extract, quantify and characterize the uterine magnetomyographic (MMG) signals that correspond to the electrophysiological activity of the uterus. METHODS Transabdominal MMG recordings with high spatial-temporal resolution were performed with the use of the 151 non-invasive magnetic sensor system. The extraction, quantification and characterization procedures were developed and applied to representative MMG signals that were recorded from a pregnant woman at regular intervals starting at 37 weeks of gestation until the subject reached active labor. RESULTS Multiple MMG recordings were successfully performed on the subject before she went into active labor. The extracted MMG burst activity showed a statistically significant correlation (r=0.2; p<0.001) with the contractile events perceived by mothers. The time-frequency analysis of the burst activity showed a power shift towards higher-frequency at 48 h before the subject went into active labor as compared to earlier recordings. Further there was a gradual increase in the synchrony in the higher-frequency band as the subject reached close to active labor. CONCLUSIONS The non-invasive recording of the magnetic signals of pregnant uterus with high spatial-temporal resolution can provide an insight into the preparatory phase of labor and has the potential of predicting term and preterm labor.

Central Oscillators in a Patient with Neuropathic Tremor: Evidence from Intraoperative Local Field Potential Recordings

Present pathophysiological concepts of neuropathic tremor assume mistimed and defective afferent input resulting in deregulation of cerebello‐thalamo‐cortical motor networks. Here, we provide direct evidence of central tremor processing in a 76‐year‐old female who underwent bilateral deep brain stimulation of the ventral intermedial nucleus of the thalamus (Vim‐DBS) because of neuropathic tremor associated with IgM paraproteinemia. Electrophysiological recordings of EEG and EMG were performed in three perioperative sessions: (1) preoperatively, (2) intraoperatively, and (3) 4 days after surgery in both rest and postural tremor conditions. Tremor‐related synchronization (coherence) between motor cortex (M1) and muscles (M. extensor digitorum, M. flexor digitorum) was assessed, and additional intraoperative local field potential (LFP) recordings from Vim allowed comprehensive coherence mapping in thalamo‐cortico‐muscular networks. Directionality of information flow was determined by directed transfer function (DTF) and phase analyses. Stimulation effects on tremor and corticomuscular coherence were assessed and the patient was followed for 12 months on clinical outcome measures (Tremor Rating Scale, CADET‐Score). Vim‐DBS reduced tremor (59%) and improved motor functionality in daily activities (31%, CADET‐A) after 12 months. Intraoperative recordings demonstrated significant coherence in the tremor frequency (4 Hz) between M1 and contralateral muscle, Vim and ipsilateral M1, Vim and contralateral muscle, but not between Vim and contralateral M1. Information flow was directed from M1 to Vim and bidirectional between M1 and muscle and between Vim and muscle, respectively. Corticomuscular coherence at tremor frequency was completely suppressed by Vim‐DBS. Our case study demonstrates central oscillators underlying neuropathic tremor and implies a strong pathophysiological rationale for Vim‐DBS.

Detrended fluctuation analysis of non-stationary cardiac beat-to-beat interval of sick infants

We performed detrended fluctuation analysis (DFA) of cardiac beat-to-beat intervals (RRis) collected from sick newborn infants over 1–4 day periods. We calculated four different metrics from the DFA fluctuation function: the DFA exponents (>40 beats up to one-fourth of the record length), (15–30 beats), root-mean-square (RMS) fluctuation on a short-time scale (20–50 beats), and RMS fluctuation on a long-time scale (110–150 beats). Except , all metrics clearly distinguished two groups of newborn infants (favourable vs. adverse) with well-characterized outcomes. However, the RMS fluctuations distinguished the two groups more consistently over time compared to . Furthermore, RMS distinguished the RRi of the two groups earlier compared to the DFA exponent. In all the three measures, the favourable outcome group displayed higher values, indicating a higher magnitude of (auto-)correlation and variability, thus normal physiology, compared to the adverse outcome group.

Mitigating the effect of non-stationarity in spectral analysis-An application to neonate heart rate analysis

In order to mitigate the effect of non-stationarity in frequency domain analysis of data, we propose a modification to the power spectral estimation, a widely used technique to characterize physiological signals. Spectral analysis requires partitioning data into smaller epochs determined by the desired frequency resolution. The modified approach proposed here involves dividing the data within each epoch by the standard deviation of the data for that epoch. We applied this modified approach to cardiac beat-to-beat interval data recorded from a newborn infant undergoing hypothermia treatment for birth asphyxia. The critically ill infant had episodes of tachyarrhythmia, distributed sporadically throughout the study, which affected the stationarity of the heart rate. Over the period of continuous heart rate recording, the infants clinical course deteriorated progressively culminating in death. Coinciding with this clinical deterioration, the heart rate signal showed striking changes in both low-frequency and high-frequency power indicating significant impairment of the autonomic nervous system. The standard spectral approach failed to capture these phenomena because of the non-stationarity of the signal. Conversely, the modified approach proposed here captured the deteriorating physiology of the infant clearly.