[Efficacy of HRV-biofeedback as additional treatment of depression and PTSD]. / Effectiviteit van hartritmevariabiliteitbiofeedback als aanvulling bij behandeling van depressie en posttraumatische stressstoornis.

BACKGROUND: Heartrate variability biofeedback (HRVB) is a non-invasive treatment in which patients are assumed to self-regulate a physiological dysregulated vagal nerve. Although the therapeutic approach of HRVB is promising in various stress-related disorders, it has only been offered on a regular basis in a few mental health treatment settings. AIM: To analyse the efficacy of HRV biofeedback as an additional psychophysiological treatment for depression and PTSD. METHOD: Systematic review with search terms HRV, biofeedback, PTSD, depression, panic disorder and anxiety disorder. RESULTS: Our search of the literature yielded 789 studies. After critical appraisal using the GRADE method, we selected 6 randomised controlled trials (RCTs) and 4 relevant studies. The RCTs with control groups 'treatment as usual' and muscle relaxation training revealed significant clinical efficacy and better results than control conditions after 4 to 8 weeks training. CONCLUSION: Although this systematic review shows the popularity of HRV in literature, it does not indicate that HRVB really has been reviewed systematically. Significant outcomes of this limited number of randomised studies indicate there may be a clinical improvement when HRVB training is integrated into treatment of PTSD and depression, particularly when this integration procedure is combined with psychotherapy. More research needs to be done with larger groups and further efforts are needed to integrate HRVB into treatment of stress-related disorders in psychiatry. Future research also needs to focus on the psychophysiological mechanisms involved.

Functional connectivity in preterm infants derived from EEG coherence analysis.

OBJECTIVE: To quantify the neuronal connectivity in preterm infants between homologous channels of both hemispheres. METHODS: EEG coherence analysis was performed on serial EEG recordings collected from preterm infants with normal neurological follow-up. The coherence spectrum was divided in frequency bands: δnewborn(0-2 Hz), θnewborn(2-6 Hz), αnewborn(6-13 Hz), ßnewborn(13-30 Hz). Coherence values were evaluated as a function of gestational age (GA) and postnatal maturation. RESULTS: All spectra show two clear peaks in the δnewborn and θnewborn-band, corresponding to the delta and theta EEG waves observed in preterm infants. In the δnewborn-band the peak magnitude coherence decreases with GA and postnatal maturation for all channels. In the θnewborn-band, the peak magnitude coherence decreases with GA for all channels, but increases with postnatal maturation for the frontal polar channels. In the ßnewborn-band a modest magnitude coherence peak was observed in the occipital channels, which decreases with GA. CONCLUSIONS: Interhemispherical connectivity develops analogously with electrocortical maturation: signal intensities at low frequencies decrease with GA and postnatal maturation, but increase at high frequencies with postnatal maturation. In addition, peak magnitude coherence is a clear trend indicator for brain maturation. SIGNIFICANCE: Coherence analysis can aid in the clinical assessment of the functional connectivity of the infant brain with maturation.

A higher illuminance induces alertness even during office hours: findings on subjective measures, task performance and heart rate measures.

Nocturnal white light exposure has shown marked results on subjective and objective indicators of alertness, vitality and mood, yet effects of white light during daytime and under usual office work conditions have not been investigated extensively. The current study employed a mixed-group design (N=32), testing effects of two illuminance levels (200lx or 1000lx at eye level, 4000K) during one hour of morning versus afternoon exposure. In four repeated blocks, subjective reports, objective performance and physiological arousal were measured. Results showed effects of illuminance on subjective alertness and vitality, sustained attention in tasks, and heart rate and heart rate variability. Participants felt less sleepy and more energetic in the high versus the low lighting condition, had shorter reaction times on the psychomotor vigilance task and increased physiological arousal. Effects of illuminance on the subjective measures, as well as those on heart rate were not dependent on time of day or duration of exposure. Performance effects were most pronounced in the morning sessions and towards the end of the one-hour exposure period. The effect on heart rate variability was also most pronounced at the end of the one-hour exposure. The results demonstrate that even under normal, i.e., neither sleep nor light deprived conditions, more intense light can improve feelings of alertness and vitality, as well as objective performance and physiological arousal.

Automatic breath-to-breath analysis of nocturnal polysomnographic recordings.

Diagnosis of sleep-disordered breathing is based on the presence of an abnormal breathing pattern during sleep. In this study, an algorithm was developed for the offline breath-to-breath analysis of the nocturnal respiratory recordings. For that purpose, respiratory signals (nasal airway pressure, thoracic and abdominal movements) were divided into half waves using period amplitude analysis. Individual breaths were characterized by the parameters of the half waves (duration, amplitude, and slope). These values can be used to discriminate between normal and abnormal breaths. This algorithm was applied to six polysomnographic recordings to distinguish abnormal breathing events (apneas and hypopneas). The algorithm was robust for the identification of breaths (sensitivity = 96.8%, positive prediction value (PPV) = 99.5%). The detection of apneas and hypopneas was compared to the manual scoring of two experienced sleep technicians: sensitivity was, respectively, 89.2 and 88.9%, PPV was 54.1 and 59.3%. The classification of apneas into central, obstructive, or mixed was in concordance with the observers in 68% of the apneas. Although the algorithm tended to detect more hypopneas than the clinical standard, this study shows that the extraction of breath-to-breath parameters is useful for detection of abnormal respiratory events and provides a basis for further characterization of these events.

Designing for reliable textile neonatal ECG monitoring using multi-sensor recordings.

When designing an ECG monitoring system embedded with textile electrodes for comfort, it is challenging to ensure reliable monitoring, because textile electrodes suffer from motion artifacts and incidental poor signal quality. For the design of a comfortable monitoring system for prematurely born babies in the Neonatal Intensive Care Unit (NICU), we propose the concepts of 'diversity measurement' and 'context awareness' to improve reliability. Clinical multi-modal sensor data was collected in the NICU with the Smart Jacket connected to a state-of-the-art amplifier. We found that the ECG signals quality varied among sensors and varied over time, and found correlations between ECG signal, acceleration data, and context, which supports the feasibility of the concepts. Our explorative system level approach has lead to design parameters and meta-insights into the role of clinical validation in the design process.

An algorithm for the automatic detection of seizures in neonatal amplitude-integrated EEG.

AIM: To develop and evaluate an algorithm for the automatic screening of electrographic neonatal seizures (ENS) in amplitude-integrated electroencephalography (aEEG) signals. METHODS: CFM recordings were recorded in asphyxiated (near)term newborns. ENS of at least 60 sec were detected based on their characteristic pattern in the aEEG signal, an increase of its lower boundary. The algorithm was trained using five CFM recordings (training set) annotated by a neurophysiologist, observer1. The evaluation of the algorithm was based on eight different CFM recordings annotated by observer1 (test set observer 1) and an independent neurophysiologist, observer2 (test set observer 2). RESULTS: The interobserver agreement between observer1 and 2 in interpreting ENS from the CFM recordings was high (G coefficient: 0.82). After dividing the eight CFM recordings into 1-min segments and classification in ENS or non-ENS, the intraclass correlation coefficient showed high correlations of the algorithm with both test sets (respectively, 0.95 and 0.85 with observer1 and 2). The algorithm showed in five recordings a sensitivity > or = 90% and approximately 1 false positive ENS per hour. However, the algorithm showed in three recordings much lower sensitivities: one recording showed ENSs of extremely high amplitude that were incorrectly classified by the algorithm as artefacts and two recordings suffered from low interobserver agreement. CONCLUSION: This study shows the feasibility of automatic ENS screening based on aEEG signals and may facilitate in the bed-side interpretation of aEEG signals in clinical practice.

Context related artefact detection in prolonged EEG recordings.

The need for reliable detection of artefacts in raw and processed EEG is widely acknowledged. Although different EEG analysis systems have been described, only few general applicable artefact recognition techniques have emerged. This paper tackles the problem of artefact detection in seven 24 h EEG recordings in the intensive care unit. ICU recordings have received less attention than, e.g. epilepsy monitoring, although recordings in this environment present an interesting application area. The EEG data used here was recorded during the difficult circumstances of an explorative ICU study. The data set includes a diverse set of EEG patterns, as well as EEG artefacts. The study investigates objective artefact detection methods based on statistical differences between signal parameters, using time-varying autoregressive modelling (AR) and Slope detection. In addition to matching the performance of artefact detection against two human observers, the study focuses on the optimal settings for context incorporation by testing the algorithms for different time windows and epoch lengths. Results indicate that a relatively short period (20-40 s) provides sufficient context information for the methods used. The combined AR and Slope detection parameters yielded good performance, detecting approximately 90% of the artefacts as indicated by the consensus score of the human observers.

Event-related desynchronization related to the anticipation of a stimulus providing knowledge of results.

In the present paper, event-related desynchronization (ERD) in the alpha and beta frequency bands is quantified in order to investigate the processes related to the anticipation of a knowledge of results (KR) stimulus. In a time estimation task, 10 subjects were instructed to press a button 4 s after the presentation of an auditory stimulus. Two seconds after the response they received auditory or visual feedback on the timing of their response. Preceding the button press, a centrally maximal ERD is found. Preceding the visual KR stimulus, an ERD is present that has an occipital maximum. Contrary to expectation, preceding the auditory KR stimulus there are no signs of a modality-specific ERD. Results are related to a thalamo-cortical gating model which predicts a correspondence between negative slow potentials and ERD during motor preparation and stimulus anticipation.

Digital archival and exchange of events in a simple format for polygraphic recordings with application in event related potential studies.

This paper describes a simple method of event encoding as an extension to a previously defined standard format, the European Data Format (EDF). The specification ensures full backward compatibility with the existing definition. By using this extension, the format can be used to store both continuous recordings and selected epochs of recordings. The encoding is performed in a channel of event-codes or in a pseudo-channel for annotations. Standardisation of event encoding is discussed. Decoding of events or annotations from the extended format is implemented at the application level. Existing programs that do not support the new encoding scheme still operate correctly and can simply ignore the new channels in processing 'extended' data files. The event encoding is also compatible with EDF's capability to encode channels of different sampling frequency.

Detection of muscle artefact in the normal human awake EEG.

OBJECTIVES: A study was performed to investigate automatic detection of muscle artefact, using time domain and frequency domain methods. The evaluation focussed on epoch length and performance of detection. METHODS: EEG data were recorded in 21 normal adult subjects for 50 min during awake state. Investigated positions included central, temporal and parietal scalp electrodes. Expert annotation of muscle artefact was performed by accurate visual marking in a randomised test-set of the data, which allowed for intra-expert comparison. For time domain detection, the parameter set consisted of slope and maximum/minimum amplitude. Parameters in the frequency domain were absolute and relative 'high beta' power (>25 Hz) and spectral edge frequency. Distributions as calculated from a reference period in each subject were used to investigate the statistics of the parameter ranges. Detection thresholds were calculated from these distributions per subject, and performance was compared to constant (empirical) thresholds for the entire data set. RESULTS: Results indicate a 1 s epoch length as optimal for detection of muscle artefact. The analysis using a slope threshold or absolute 'high beta' power showed the best results in sensitivity (80%) and specificity (90%), matching the expert's performance. CONCLUSIONS: Constant threshold settings performed better than statistical thresholds per subject.

Event-related potential measures of information processing during general anesthesia.

To investigate the incidence and manner of auditory information processing during a state of presumed unconsciousness event-related brain potentials (ERPs) were studied in 41 patients undergoing cardiac surgery with propofol/alfentanil anesthesia. The ERPs were recorded during auditory oddball tasks administered before and within several periods of the operation. Mean nasopharyngeal temperature and anesthetic concentrations were determined for each intraoperative ERP recording epoch. During anesthesia ERP waves could still be observed up to 500 ms after stimulus onset indicating that auditory information processing was not suppressed completely by the administered anesthetic agents. Relative to the preoperative recordings, the P1-N1-P2 complex was delayed and more positive going during anesthesia. Comparable changes in ERP morphology have been observed during Stage II-IV sleep, suggesting parallels in the mechanisms underlying early auditory processing in both states of reduced arousal level, possibly related to a selective reduction of a non-specific activity. N1 and P2 peak amplitudes were found to be larger for the deviant tones compared to the standard tones. These amplitude differences most likely reflect automatic detection of stimulus deviance, although it cannot be excluded entirely that they were due to differences in refractoriness. Anesthetic concentrations and nasopharyngeal temperature were found to be of minor significance for ERP control. It is suggested that ERPs could serve as intraoperative reference measures, providing the earliest evidence for auditory processing. This characteristic is important for validation of signals and techniques that are proposed to improve conventional monitoring of anesthesia with respect to detecting unintended awareness.

Midlatency auditory evoked potentials as indicators of perceptual processing during general anaesthesia.

We tested the hypothesis that midlatency auditory evoked potentials (MLAEP) can predict the occurrence of long latency AEP components (LLAEP), which are taken as evidence for perceptual processing. Forty-one patients undergoing cardiac surgery were anaesthetized with propofol and alfentanil. During several periods of surgery we recorded LLAEP. Peak-to-peak amplitude measures were used to determine if a particular LLAEP recording trace contained a recognizable waveform. Both before and after each LLAEP recording epoch, MLAEP and the spontaneous electroencephalogram (EEG) were recorded. Peak latencies and amplitudes of brainstem peak V and midlatency peaks Na, Pa, Nb, Pb and Nc, characteristic frequencies from the spontaneous EEG, mean arterial pressure (MAP) and nasopharyngeal temperature (7) were compared between recording epochs with and without clear LLAEP waveforms. These variables were also used in a discriminant analysis to predict the occurrence of an LLAEP waveform. Pa and Nb latencies were significantly shorter both before and after recording epochs in which an LLAEP waveform occurred, compared with epochs in which no LLAEP waveform occurred. Using a combination of up to six EEG, MLAEP, MAP and T measures, it was possible to predict the occurrence or absence of an LLAEP waveform with a sensitivity of 89% and specificity of 86%. We conclude that MLAEP components provide information on the possibility of perceptual processing during general anaesthesia, and thus may be relevant for monitoring depth of anaesthesia.

Non-linear algorithms for processing biological signals.

This paper illustrates different approaches to the analysis of biological signals based on non-linear methods. The performance of such approaches, despite the greater methodological and computational complexity is, in many instances, more successful compared to linear approaches, in enhancing important parameters for both physiological studies and clinical protocols. The methods introduced employ median filters for pattern recognition, adaptive segmentation, data compression, prediction and data modelling as well as multivariate estimators in data clustering through median learning vector quantizers. Another approach described uses Wiener-Volterra kernel technique to obtain a satisfactory estimation and causality test among EEG recordings. Finally, methods for the assessment of non-linear dynamic behaviour are discussed and applied to the analysis of heart rate variability signal. In this way invariant parameters are studied which describe non-linear phenomena in the modelling of the physiological systems under investigation.

Haemodynamic responses to incision and sternotomy in relation to the auditory evoked potential and spontaneous EEG.

We investigated the effect of incision and sternotomy on the auditory evoked potential (AEP) and EEG, to try to predict a haemodynamic response to incision or sternotomy using the AEP and EEG in 41 patients undergoing cardiac surgery during propofol and alfentanil anaesthesia. The AEP and EEG were recorded before incision, between incision and sternotomy, and after sternotomy. Peak latencies and amplitudes of AEP peaks V, Na, Pa, Nb, Pb and Nc were determined. From the EEG the median, spectral edge and peak power frequencies, and percentages of delta, theta, alpha and beta power were calculated. Each patient was classified as responsive, equivocally responsive or unresponsive to incision or sternotomy based on increase in arterial pressure and heart rate on incision and sternotomy. Before incision, Nb and Pb latency and propofol concentration were higher for unresponsive patients but heart rate and median frequency before incision were lower. After sternotomy, Pa and Nb amplitude, peak power frequency and percentage alpha power were higher, and percentage theta power lower for responsive patients. Pa latency was higher after sternotomy for unresponsive patients. Using a combination of heart rate, arterial pressures and features derived from the AEP (all recorded before incision), the occurrence of a response to incision could be predicted in individual patients with a sensitivity of 85%, positive predictive accuracy of 63% and total accuracy of 72%. We conclude that AEP are more sensitive to pain stimuli than spectral features of the spontaneous EEG. In addition, the AEP may help in predicting inadequate anaesthesia.

Clinical evaluation of a method for automatic detection and removal of artifacts in auditory evoked potential monitoring.

OBJECTIVE: The objective of our study was to evaluate the method for detection and removal of artifacts in evoked potential monitoring described earlier by Cluitmans and colleagues in a clinical setting. METHODS: The method for detection and removal of artifacts by Cluitmans and colleagues is based on the assumption that a sweep of the recorded electroencephalogram (EEG) signal contains artifacts if one or more variables derived from the signal deviates strongly from the normal range of values. Once these normal ranges are defined, all future EEG recordings that are recorded under comparable circumstances can be automatically evaluated for artifacts by tracking when one or more signal variables falls outside the normal range. To assess the performance of this method in a clinical setting, recordings from a learning set were visually evaluated for artifacts. From the empirical distribution functions of the signal variables, the thresholds for automatic detection of artifacts were determined. The auditory evoked potential (AEP) waveforms resulting after automatic screening were compared with the waveforms obtained after visual evaluation of the raw signal combined with manual exclusion of signal periods containing artifacts. RESULTS: The quality of the resulting waveform was improved by our method of automatic detection and removal of artifacts in 97% of partly contaminated recordings. In only 2% of the recordings, automatic screening slightly degraded the resulting waveform. CONCLUSIONS: We conclude that the described method of automatic detection and removal of artifacts in AEP recordings effectively improves the quality of the resulting AEP waveform, without excessive rejection of artifact-free signal periods. The signal variables used in this method seem appropriate for distinguishing artifact-free signal periods from periods containing artifacts for the types of artifact that were studied.

Information processing during cardiac surgery: an event related potential study.

The aim of this study was to investigate whether information processing persists during general anesthesia, and if so, to determine the relationship between the degree of cognitive processing measured during anesthesia and the presence or absence of intraoperative memories measured after anesthesia. Subjects were 12 patients, undergoing cardiac surgery with propofol/alfentanil anesthesia. During several periods of the operation, event related potentials (ERPs) to frequent and infrequent tones of different pitch were analyzed. After the operation, a word recognition task with ERP recording was administered to determine whether intraoperatively presented words would elicit a (covert) recognition reaction in the brain. ERP wave forms could be obtained during the intraoperative recording periods but differed substantially from those in the awake state. The presence of ERP components up to 500 msec after stimulus presentation suggests that auditory information processing continued during anesthesia up to a certain level of cognition. Intraoperative ERPs to frequent and infrequent tones were not different from each other implying that differences in pitch could not be detected. The postoperative results demonstrated evidence for intraoperative memories in 3 patients. For 2 of these 3 patients, low propofol levels as well as reliable ERPs with large amplitudes were found close to the moment of information presentation. The results emphasize the importance of combining intra- and postoperative measurements and suggest that late ERP components might be used as indicators of an increased risk of auditory perception.

A spatio-temporal dipole model of the readiness potential in humans. I. Finger movement.

Preceding unilateral finger movements readiness potentials (RPs) were recorded in 9 right-handed subjects. The data are presented as time series, potential maps and spatio-temporal dipole models. The latter are interpreted with respect to the underlying generators of the RP. Explicit hypotheses about the unilateral or bilateral activation of particular sensorimotor areas preceding unilateral movements are addressed. The choice for the best spatio-temporal dipole model was guided by a test on the orthogonality of the individual residuals and by a priori neurophysiological evidence. From the final model it is concluded that the initial bilateral symmetrical part of the RP is generated in the posterior walls of the precentral gyrus bilaterally, whereas the later lateralized components originate from the crown of that same gyrus contralaterally. This confirms and extends data from subdural recording, magnetoencephalography (MEG) and EEG.

A spatio-temporal dipole model of the readiness potential in humans. II. Foot movement.

Readiness potentials (RP) have been recorded in 9 subjects who performed voluntary unilateral plantar flexions with the right or left foot. These show a paradoxical ipsilateral dominance. Spatio-temporal dipole models were obtained for these data, by iterative parameter estimation. The non-uniqueness of the inverse problem leads to several models which describe the data almost equally well, and which all pass orthogonality tests for the individual residuals and source waves. In these dipole models the ipsilateral preponderance is attributed to generators in the contralateral hemisphere, which agrees with results from MEG recording. According to these models the main generators of the RP are in the primary motor cortex, one bilaterally in its posterior wall and the other in the contralateral crown. This agrees with earlier results for finger RPs. However, for foot RPs, it was difficult to distinguish individual sub-components in both the observed scalp potentials and the estimated temporal activation patterns of the dipoles. Some of the presented models include a fronto-central dipole which possibly represents activity of the supplementary motor area. It is concluded that this finding is at best suggestive and needs further investigation.

Identification of peak V in brainstem auditory evoked potentials with neural networks.

A feature extractor for determining the latency of peak V in brainstem auditory evoked potentials (BAEPs) is presented in this paper. A feature extractor that combines artificial neural networks with an algorithmic approach is presented. It consists of a series of small neural networks that have to make simple decisions. Each neural network decides what part of the input pattern contains the peak, and the algorithm passes that part of the pattern to the next neural network; in this way the size of the input patterns decreases during the process, and the last neural network determines the exact location of the peak. An optimal configuration of neural networks could determine the latencies of peak V in all synthetic evoked potentials correctly. With real evoked potentials, the networks yield results that comply with the opinion of a human expert in 80 +/- 6% of the cases.

Artifact detection and removal during auditory evoked potential monitoring.

Various artifacts can distort or obscure evoked potential waveforms. The algorithms presented in this paper scan the output electroencephalographic signal for artifacts during evoked potential recordings. If possible, the artifact is removed; if not possible, that sweep is excluded from the averaging process required to raise the evoked response above the background electroencephalographic activity. An artifact is detected if 1 or more amplitude or frequency parameters exceed a threshold. These thresholds have been determined after constructing histograms of the parameters concerned using a number of control evoked potential recordings containing no visually recognizable artifacts. The distributions of the parameters shown by these histograms give information about their normal range. The method improves the quality of the waveform in many cases, but its effectiveness strongly depends on the characteristics of the artifacts concerned.