Efficacy and costs of a workplace wellness programme.

BACKGROUND: Research investigating the efficacy of workplace wellness programmes to promote exercise, and by extension, reduce obesity and increase productivity has proliferated in recent years. Although preliminary work is encouraging, more work is needed. AIMS: To evaluate the effects and overall cost of a workplace exercise programme on multiple physical outcomes, including body mass index, aerobic fitness and muscular fitness. METHODS: Data from the Bruin Health Improvement Programme .5 (BHIP) between August 2013 and July 2018 were analysed. BHIP is a 12-week workplace wellness programme that assesses multiple areas of physical and mental health. For this study, changes in weight, waist-to-hip ratio, aerobic fitness and muscular endurance were analysed using paired samples t-tests and chi-squared tests. Using results from a prior analysis of Medical Expenditure Panel Survey, the estimated medical expenditure savings associated with weight loss were also analysed. RESULTS: A total of 518 participants (84% female) took part in the BHIP programme (mean age = 41 years, SD = 1.17). There were significant decreases in all anthropometric indices and significant increases in all fitness outcomes (P < 0.01) from baseline to follow-up. Estimated programme cost per participant, per session was $473 US Dollars (USD), and weight loss is estimated to reduce annual medical care costs by ~$2200 USD. CONCLUSIONS: Results showed significant improvements in all physical outcomes of interest. Additionally, there appears to be an inverse relationship between improvements in employee health and employer healthcare costs. Strengths, limitations and future directions are discussed.

A morphological approach to detect respiratory phases of seismocardiogram.

This paper presents a new approach to identify the respiratory phases of heart cycles from acceleration signals (i.e., seismocardiogram) recorded from the sternum, in back to front direction. The acceleration signals were recorded simultaneously with a single lead electrocardiogram (ECG), and the respiratory signal (using a chest band strain gauge) from 20 healthy subjects. Two accelerometer-derived respiration (ADR) signals were computed by computing the lower and upper envelope of the accelerometer signal. In the proposed methodology, for each subject a metric so-called, the piecewise total harmonic distortion (THD) was used to identify which one of lower and upper envelopes is the best ADR for detecting respiratory phases. The accuracy of piecewise THD in the selection of the correct envelope of SCG signal as an estimation of ADR is 84.6%. Consequently, respiratory phases of heart cycles were identified using the estimated ADR signals. Results confirm that the proposed envelope detection based ADR technique can detect respiratory phases of heartbeats with the accuracy of above 75%. In other words, using aforementioned methods, THD thresholding and piecewise THD, the capability of ADR signal to detect respiratory phases is increased approximately 14% compared to the lower envelope of the accelerometer (ADRLower) and 4% compared to the upper envelope of accelerometer signal (ADRUpper).

fMRI and corpus callosum relationships in monozygotic twins discordant for handedness.

To further investigate brain structure and function in 26 handedness discordant monozygotic twin pairs (MzHd), MRI and behavioural assessments were carried out. These showed significant correlation between language-specific functional laterality in inferior and middle frontal gyri, and anterior corpus callosum. Previous studies of handedness discordant monozygotic twins failed to resolve the issue concerning handedness and hemispheric laterality for language due to methodological disparities. The results would be relevant to genetic theories as well as to brain structure:function explanations. MzHd twins underwent MRI and fMRI scanning as well as behavioural assessment of motor performance and cognition. There were significant differences on MRI and fMRI laterality measures, as well as a significant correlation between anterior callosal widths and functional laterality. LH twins showed higher frequencies of atypical functional laterality. There was no significant within-twin pair correlation on fMRI verbal laterality, nor did results show within-twin pair differences on verbal fluency or IQ. Implications for the field of laterality research pertain to frontal hemispheric equipotentiality for verbal processes in healthy individuals. In particular, there can be an apparent lack of cognitive 'cost' to atypical laterality. An fMRI verbal laterality index correlated significantly with corpus callosum widths near Broca's area.

Poster - Thur Eve - 16: Four-dimensional x-ray computed tomography and hyperpolarized 3 He magnetic resonance imaging of gas distribution in lung cancer.

Dynamic imaging methods such as four-dimensional computed tomography (4DCT) and static imaging methods such as noble gas magnetic resonance imaging (MRI) deliver direct and regional measurements of lung function even in lung cancer patients in whom global lung function measurements are dominated by tumour burden. The purpose of this study was to directly compare quantitative measurements of gas distribution from static hyperpolarized 3 He MRI and dynamic 4DCT in a small group of lung cancer patients. MRI and 4DCT were performed in 11 subjects prior to radiation therapy. MRI was performed at 3.0T in breath-hold after inhalation 1L of hyperpolarized 3 He gas. Gas distribution in 3 He MRI was quantified using a semi-automated segmentation algorithm to generate percent-ventilated volume (PVV), reflecting the volume of gas in the lung normalized to the thoracic cavity volume. 4DCT pulmonary function maps were generated using deformable image registration of six expiratory phase images. The correspondence between identical tissue elements at inspiratory and expiratory phases was used to estimate regional gas distribution and PVV was quantified from these images. After accounting for differences in lung volumes between 3 He MRI (1.9±0.5L ipsilateral, 2.3±0.7 contralateral) and 4DCT (1.2±0.3L ipsilateral, 1.3±0.4L contralateral) during image acquisition, there was no statistically significant difference in PVV between 3 He MRI (72±11% ipsilateral, 79±12% contralateral) and 4DCT (74±3% ipsilateral, 75±4% contralateral). Our results indicate quantitative agreement in the regional distribution of inhaled gas in both static and dynamic imaging methods. PVV may be considered as a regional surrogate measurement of lung function or ventilation.

A fuzzy rule-based system for epileptic seizure detection in intracranial EEG.

OBJECTIVE: We present a method for automatic detection of seizures in intracranial EEG recordings from patients suffering from medically intractable focal epilepsy. METHODS: We designed a fuzzy rule-based seizure detection system based on knowledge obtained from experts' reasoning. Temporal, spectral, and complexity features were extracted from IEEG segments, and spatio-temporally integrated using the fuzzy rule-based system for seizure detection. A total of 302.7h of intracranial EEG recordings from 21 patients having 78 seizures was used for evaluation of the system. RESULTS: The system yielded a sensitivity of 98.7%, a false detection rate of 0.27/h, and an average detection latency of 11s. There was only one missed seizure. Most of false detections were caused by high-amplitude rhythmic activities. The results from the system correlate well with those from expert visual analysis. CONCLUSION: The fuzzy rule-based seizure detection system enabled us to deal with imprecise boundaries between interictal and ictal IEEG patterns. SIGNIFICANCE: This system may serve as a good seizure detection tool with high sensitivity and low false detection rate for monitoring long-term IEEG.

EEG seizure prediction: Measures and challenges.

Different types of analyses of scalp and intracranial electroencephalography (EEG) recordings using linear and nonlinear time series analysis method have been done. They showed strong evidence of detectable changes in the EEG dynamics from minutes up to several hours in advance of seizure onset. The predictive performance of univariate and bivariate measures, comprising both linear and non-linear approaches have been carried in different studies Direct comparison among different measures and methods in seizure prediction is not possible, unless they are applied to the same dataset. In this review paper, we describe different seizure prediction measures briefly and discuss the existing challenges.

Seizure detection in intracranial EEG using a fuzzy inference system.

In this paper, we present a fuzzy rule-based system for the automatic detection of seizures in the intracranial EEG (IEEG) recordings. A total of 302.7 hours of the IEEG with 78 seizures, recorded from 21 patients aged between 10 and 47 years were used for the evaluation of the system. After preprocessing, temporal, spectral, and complexity features were extracted from the segmented IEEGs. The results were thresholded using the statistics of a reference window and integrated spatio-temporally using a fuzzy rule-based decision making system. The system yielded a sensitivity of 98.7%, a false detection rate of 0.27/h, and an average detection latency of 11 s. The results from the automatic system correlate well with the visual analysis of the seizures by the expert. This system may serve as a good seizure detection tool for monitoring long-term IEEG with relatively high sensitivity and low false detection rate.

Implementation of wavelet encoding spectroscopic imaging technique on a 3 Tesla whole body MR scanner: in vitro results.

Proton magnetic resonance spectroscopic imaging (MRSI) provides spatial information about tissue metabolite concentrations used in differentiating diseased from normal tissue. Obtaining metabolic maps with high spatial resolution requires long acquisition time where the patient has to lie still inside the magnet bore (scanner) especially if classical Chemical Shift Imaging (CSI) is used. To reduce acquisition time and obtain a more accurate metabolite distribution with low voxel contamination in MRSI, we have recently proposed and successfully implemented a full Wavelet Encoding-Spectroscopic Imaging (WE-SI) technique on a 1.5 Tesla whole body MR clinical scanner. In this paper we describe the implementation of the WE-SI technique at higher magnetic field strength (B(0)) on a clinical 3 Tesla Siemens scanner equipped with parallel imaging tools for better sensitivity. This increases the signal to noise ratio (SNR) and allows combination of the proposed technique with the so-called parallel imaging approach for further acquisition time reduction.

Analysis of p300 classifiers in brain computer interface speller.

In this paper, the performance of five classifiers in P300 speller paradigm are compared. Theses classifiers are Linear Support Vector Machine (LSVM), Gaussian Support Vector Machine (GSVM), Neural Network (NN), Fisher Linear Discriminant (FLD), and Kernel Fisher Discriminant (KFD). In classification of P300 waves, there has been a trend to use SVM classifiers. Although they have shown a good performance, in this paper, it is shown that the FLD classifiers outperform the SVM classifiers. FLD classifier uses only ten channels of the recorded electroencephalogram (EEG) signals. This makes them a very good candidate for real-time applications. In addition, FLD approach does not need any optimization similar to other methods. In addition, in this paper, it is shown that the efficiency of using Principal Component Analysis (PCA) for feature reduction results in decreasing the time for the classification and increasing the accuracy.

Assessment of preprocessing on classifiers used in the p300 speller paradigm.

Artifact removal is an essential part in electroencephalogram (EEG) recording and the raw EEG signals require preprocessing before feature extraction. In this work, we implemented three filtering methods and demonstrated their effects on the performance of different classifiers. Bandpass digital filtering, median filtering and facet method are three preprocessing approaches investigated in this paper. We used data set lib from the BCI competition 2003 for training and testing phase. Our accuracy varied between 80% and 96%. In our work, we demonstrated that the problems of choosing the classifier and preprocessing methods are not independent of each other. Two of our approaches could achieve the 96% accuracy i.e. 31 of 32 characters were predicted correctly. These two approaches have different classifier and different preprocessing method. It means that the performance of each classifier can be enhanced with a specific preprocessing method. In our approach, we used only three electrodes of 64 applied electrodes. Therefore it can noticeably reduce the time and cost of EEG measurement.

Nonsurgical treatment of extraoral lesions caused by necrotic nonvital tooth.

Two cases of extraoral fistula on the chin--caused by necrotic pulp of lower anterior teeth--are being presented. A paste consisting of equal amounts of calcium hydroxide and iodoform mixed with glycerin was used. It is concluded that the positive results of this method of treatment were due to the therapeutic properties of the paste. The historical background of similar pastes is--in retrospect--briefly reviewed.

Retroviral vectors pseudotyped with lymphocytic choriomeningitis virus.

Pseudotyping can improve retroviral vector stability and transduction efficiency. Here, we describe a novel pseudotype of murine leukemia virus packaged with lymphocytic choriomeningitis virus (LCMV). This pseudotype was stable during ultracentrifugation and infected several cell lines from different species. Moreover, LCMV glycoproteins were not cell toxic.