Non-invasive fetal monitoring: Fetal Heart Rate multimodal estimation from abdominal electrocardiography and phonocardiography.

BACKGROUND: Fetal cardiac well-being is essential during labor as the delivery is at risk for fetal distress. Continuous monitoring by cardiotocography (CTG) is daily used to record the fetal heart rate (FHR) but this technique has important drawbacks in clinical use. OBJECTIVES: We propose to monitor FHR with a non-invasive technique, using multimodal recordings of the fetus cardiac activity, associating electrocardiographic (ECG) and phonocardiographic (PCG) sensors. The aim of this study is to evaluate the quality of these multimodal FHR estimations by comparison with CTG, based on clinical criteria. METHODS: A clinical protocol was established and a prospective open label study was carried out in the University Hospital of Grenoble. The objective was to record thoracic and abdominal PCG and ECG signals on pregnant women over 37 WG (weeks of gestation), simultaneously with CTG recordings. Adapted signal processing algorithms were then applied on abdominal PCG and ECG signals to extract FHR. Quantitative evaluation was carried out on FHR estimations compared with FHR extracted from CTG. RESULTS: A total of 40 recordings were performed. Due to technical mistakes the analysis was made possible for 38. 35 recordings allowed a FHR follow-up by ECG or PCG, 30 recordings allowed a FHR follow-up by PCG only, 25 recordings allowed a FHR follow-up by ECG only and 20 recordings allowed a FHR follow-up by both ECG and PCG. CONCLUSION: Reliable multimodal recording of FHR associating ECG and PCG sensors is possible during the last month of pregnancy. These positive results encourage the study of multimodal FHR recording during labor and delivery.

Non-invasive fetal monitoring using electrocardiography and phonocardiography: A preliminary study.

BACKGROUND: Continuous fetal monitoring is commonly used during pregnancy and labor to assess fetal wellbeing. The most often used technology is cardiotocography (CTG), but this technique has major drawbacks in clinical use. OBJECTIVES: Our aim is to test a non-invasive multimodal technique of fetal monitoring using phonocardiography (PCG) and electrocardiography (ECG) and to evaluate its feasibility in clinical practice, by comparison with CTG. METHODS: This prospective open label study took place in a French university hospital. PCG and ECG signals were recorded using abdominal and thoracic sensors from antepartum women during the second half of pregnancy, simultaneously with CTG recording. Signals were then processed to extract fetal PCG and ECG and estimate fetal heart rate (FHR). RESULTS: A total of 9 sets of recordings were evaluated. Very accurate fetal ECG and fetal PCG signals were recorded, enabling us to obtain FHR for several subjects. The FHR calculated from ECG was highly correlated with the FHR from the CTG reference (from 74% to 84% of correlation). CONCLUSION: This work with preliminary signal processing algorithms proves the feasibility of the approach and constitutes the beginnings of a unique database that is needed to improve and validate the signal processing algorithms.

Improving single-trial detection of event-related potentials through artificial deformed signals.

To propose a reliable and robust Brain-Computer Interface (BCI), efficient machine learning and signal processing methods have to be used. However, it is often necessary to have a sufficient number of labeled brain responses to create a model. A large database that would represent all of the possible variabilities of the signal is not always possible to obtain, because calibration sessions have to be short. In the case of BCIs based on the detection of event-related potentials (ERPs), we propose to tackle this problem by including additional deformed patterns in the training database to increase the number of labeled brain responses. The creation of the additional deformed patterns is based on two approaches: (i) smooth deformation fields, and (ii) right and left shifted signals. The evaluation is performed with data from 10 healthy subjects participating in a P300 speller experiment. The results show that small shifts of the signal allow a better estimation of both spatial filters, and a linear classifier. The best performance, AUC=0.828 ± 0.061, is obtained by combining the smooth deformation fields and the shifts, after spatial filtering, compared to AUC=0.543 ± 0.025, without additional deformed patterns. The results support the conclusion that adding signals with small deformations can significantly improve the performance of single-trial detection when the amount of training data is limited.

Performance comparison of laying hens segregating for the frizzle gene under thermoneutral and high ambient temperatures.

The effect on thermotolerance of the incompletely dominant frizzle (F) gene, which causes feather curling and feather mass reduction, was investigated in 281 laying hens that were homozygous for the frizzle mutation (FF), heterozygous (FN), or normally feathered (NN). One-half of the birds were kept under standard conditions (22°C) and half were exposed to high ambient temperatures (32°C) between 24 and 46 wk of age. Egg production, egg quality, feed efficiency, and dissection traits were recorded and compared. At standard conditions, egg production and quality traits did not differ among the 3 genotypes, whereas feed efficiency was lower for the homozygous birds. Under heat stress conditions, the superiority of the FF hens was evident for all egg quantity and quality traits. No significant difference was measured between heterozygous carriers and normally feathered hens, indicating that the incomplete dominant frizzle mutation behaved as a recessive mutation regarding heat tolerance. From this study, we deduced that the F mutation in its homozygous state has a beneficial effect in decreasing heat stress in poultry production, and it could be particularly advantageous in tropical countries where average temperatures are never too low to negatively affect feed efficiency.

Impact of spatial filters during sensor selection in a visual P300 brain-computer interface.

A challenge in designing a Brain-Computer Interface (BCI) is the choice of the channels, e.g. the most relevant sensors. Although a setup with many sensors can be more efficient for the detection of Event-Related Potential (ERP) like the P300, it is relevant to consider only a low number of sensors for a commercial or clinical BCI application. Indeed, a reduced number of sensors can naturally increase the user comfort by reducing the time required for the installation of the EEG (electroencephalogram) cap and can decrease the price of the device. In this study, the influence of spatial filtering during the process of sensor selection is addressed. Two of them maximize the Signal to Signal-plus-Noise Ratio (SSNR) for the different sensor subsets while the third one maximizes the differences between the averaged P300 waveform and the non P300 waveform. We show that the locations of the most relevant sensors subsets for the detection of the P300 are highly dependent on the use of spatial filtering. Applied on data from 20 healthy subjects, this study proves that subsets obtained where sensors are suppressed in relation to their individual SSNR are less efficient than when sensors are suppressed in relation to their contribution once the different selected sensors are combined for enhancing the signal. In other words, it highlights the difference between estimating the P300 projection on the scalp and evaluating the more efficient sensor subsets for a P300-BCI. Finally, this study explores the issue of channel commonality across subjects. The results support the conclusion that spatial filters during the sensor selection procedure allow selecting better sensors for a visual P300 Brain-Computer Interface.

A robust sensor-selection method for P300 brain-computer interfaces.

A brain-computer interface (BCI) is a specific type of human-computer interface that enables direct communication between human and computer through decoding of brain activity. As such, event-related potentials like the P300 can be obtained with an oddball paradigm whose targets are selected by the user. This paper deals with methods to reduce the needed set of EEG sensors in the P300 speller application. A reduced number of sensors yields more comfort for the user, decreases installation time duration, may substantially reduce the financial cost of the BCI setup and may reduce the power consumption for wireless EEG caps. Our new approach to select relevant sensors is based on backward elimination using a cost function based on the signal to signal-plus-noise ratio, after some spatial filtering. We show that this cost function selects sensors' subsets that provide a better accuracy in the speller recognition rate during the test sessions than selected subsets based on classification accuracy. We validate our selection strategy on data from 20 healthy subjects.

Major symptoms and differential diagnosis of neuroleptic malignant syndrome: three case reports.

The authors describe the cases of three patients presenting a major extrapyramidal symptom with rising CPK, inconstant hyperthermia and autonomic dysfunction. Through a brief review of the literature, the authors question the unity of the malignant syndrome. If hypertonia is quite constant, the rise in the seric CPK is aspecific and hyperthermia is inconstant.

Depression and Burnout in Hospital Health Care Professionals.

A cross-sectional study was conducted on a random sample of 1,200 health care professionals in Marseille, France, in order to assess the prevalences of depression and burnout, and to compare these two entities. Depression was assessed by the Center for Epidemiologic Studies-Depression scale (CES-D), and burnout by the Maslach Burnout Inventory (MBI). Burnout is a syndrome of emotional exhaustion, depersonalization towards patients, and reduced sense of personal accomplishment. Some psychiatrists consider burnout to be a clinical form of depression. The prevalences of depression and burnout were very close: 17.1% and 15.7% among the women, 19.4% and 22% among the men, but 6.5% of the women and 9.4% of the men were both depressive and burned-out. A correlation was found between the CES-D and the subscales Emotional Exhaustion and Depersonalization of the MBI. Multivariate analysis and logistic regression models showed that many demographic and subjective variables influenced depression and burnout in different ways.

[Descriptive approach to latent forms of schizophrenia]. / Approche descriptive des formes frontières des schizophrénies.

The computerized medical file, used in routine work in an Adult Psychiatry University-Hospital Unit enabled us to select 113 cases among 1,000 consecutive hospitalizations, the diagnosis of which could possibly lead to schizophrenia. These cases which we named "paraschizophrenic states" are linked to DSM III-R criteria of borderline (27 cases), schizoid (40 cases) or schizotypical (15 cases) personalities, schizophreniform trouble and unspecified psychotic trouble (17 cases), brief reactional psychosis (14 cases). We selected 196 cases of schizophrenia in the same cohort of hospitalized patients. As it is now usually admitted, we marked out two subgroups in this second group: the positive schizophrenia which gather together the paranoid and undifferentiated patterns and the negative schizophrenia which correspond to disorganized, catatonic and residual models, according to DSM III-R criterion. We compared the "paraschizophrenic states'" group and its five subgroups (we indeed joined schizophreniform trouble and unspecified psychotic trouble under the name of "other psychotic trouble" by reason of their relative nosographic lacks of precision and of their too small sizes) with the schizophrenia's group and its two subgroups. Each group is matched for sex (1.51 men for 1 woman in the first group and 1.45 men for 1 woman in the second group). We evaluated statistics for markers usually studied in schizophrenia in each subgroup. These markers are of three classes: biographical: age during the study, age of troubles' onset, season of birth; socioeconomic: socioeconomic level of family and patient's student status; psychiatric: family (history affective trouble, psychotic trouble, alcoholism), treatment response and short- and middle-term prognosis.(ABSTRACT TRUNCATED AT 250 WORDS)