Comparison of extrasystolic ECG signal classifiers using discrete wavelet transforms

This work compares and contrasts results of classifying time-domain ECG signals with pathological conditions taken from the MITBIH arrhythmia database. Linear discriminant analysis and a multi-layer perceptron were used as classifiers. The neural network was trained by two different methods, namely back-propagation and a genetic algorithm. Converting the time-domain signal into the wavelet domain reduced the dimensionality of the problem at least 10-fold. This was achieved using wavelets from the db6 family as well as using adaptive wavelets generated using two different strategies. The wavelet transforms used in this study were limited to two decomposition levels. A neural network with evolved weights proved to be the best classifier with a maximum of 99.6% accuracy when optimised wavelet-transform ECG data wits presented to its input and 95.9% accuracy when the signals presented to its input were decomposed using db6 wavelets. The linear discriminant analysis achieved a maximum classification accuracy of 95.7% when presented with optimised and 95.5% with db6 wavelet coefficients. It is shown that the much simpler signal representation of a few wavelet coefficients obtained through an optimised discrete wavelet transform facilitates the classification of non-stationary time-variant signals task considerably. In addition, the results indicate that wavelet optimisation may improve the classification ability of a neural network. (c) 2005 Elsevier B.V. All rights reserved.

Single trial BCI operation via Wackermann parameters

Accurate single trial P300 classification lends itself to fast and accurate control of Brain Computer Interfaces (BCIs). Highly accurate classification of single trial P300 ERPs is achieved by characterizing the EEG via corresponding stationary and time-varying Wackermann parameters. Subsets of maximally discriminating parameters are then selected using the Network Clustering feature selection algorithm and classified with Naive-Bayes and Linear Discriminant Analysis classifiers. Hence the method is assessed on two different data-sets from BCI competitions and is shown to produce accuracies of between approximately 70% and 85%. This is promising for the use of Wackermann parameters as features in the classification of single-trial ERP responses.

Adiposity, insulin and lipid metabolism in post-menopausal women

OBJECTIVE: To investigate relationships between body fat and its distribution and carbohydrate and lipid tolerance using statistical comparisons in post-menopausal women. DESIGN: Sequential meal, postprandial study (600 min) which included a mixed standard breakfast (30 g fat) and lunch (44 g fat) given at 0 and 270 min, respectively, after an overnight fast. SUBJECTS: Twenty-eight post-menopausal women with a diverse range of body weight (body mass index (BMI), mean 27.2, range 20.5-38.8 kg/m2) and abdominal fat deposition (waist, mean 86.4, range 63.5-124.0 cm). Women with BMI <18 or >37 kg/m2, age>80 y and taking hormone replacement therapy (HRT) were excluded. MEASUREMENTS: Anthropometric measurements were performed to assess total and regional fat deposits. The concentrations of plasma total cholesterol, high density lipoprotein (HDL) cholesterol, triacylglycerol (TAG), glucose, insulin (ins), non-esterified fatty acids (NEFA) and apolipoprotein (apo) B-48 were analysed in plasma collected at baseline (fasted state) and at 13 postprandial time points for a 600 min period. RESULTS: Insulin concentrations in the fasted and fed state were significantly correlated with all measures of adiposity (BMI, waist, waist-hip ratio (W/H), waist-height ratio (W/Ht) and sum of skinfold thickness (SSk)). After controlling for BMI, waist remained significantly and positively associated with fasted insulin (r=0.559) with waist contributing 53% to the variability after multiple regression analysis. After controlling for waist, BMI remained significantly correlated with postprandial (IAUC) insulin (r=0.535) contributing 66% of the variability of this measurement. No association was found between any measures of adiposity and glucose concentrations, although insulin concentration in relation to glucose concentration (glucose-insulin ratio) was significantly negatively correlated with all measures of adiposity. A significant positive correlation was found between fasted TAG and BMI (r=0.416), waist (r=0.393) and Ssk (r=0.457) and postprandial (AUC) TAG with BMI (r=0.385) and Ssk (r=0.406). A significantly higher postprandial apolipoprotein (apo) B-48 response was observed in those women with high BMI (>27 kg/m2). Fasting levels of NEFA were significantly and positively correlated with all measures of adiposity (except W/H). No association was found between cholesterol containing particles and any measure of adiposity. CONCLUSION: Hyperinsulinaemia associated with increasing body fat and central fat distribution is associated with normal glucose but not TAG or NEFA concentrations in postmenopausal women.

Statistical evaluation of the early-stage development of Jatropha energy plantations in Northeastern Mexico

A systematic evaluation of agricultural factors affecting the adaptation of the tropical oil plant Jatropha curcas L. to the semi-arid subtropical climate in Northeastern Mexico has been conducted. The factors studied include plant density and topology, as well as fungi and virus abundances. A multiple regression analysis shows that total fruit production can be well predicted by the area per plant and the total presence of fungi. Four common herbicides and a mechanical weed control measure were established at a dedicated test array and their impact on plant productivity was assessed.

Survival of freeze dried Lactobacillus plantarum in instant fruit powders and reconstituted fruit juices

The aim of this study was to investigate the survival of freeze dried Lactobacillus plantarum cells mixed with several freeze dried instant fruit powders (strawberry, pomegranate, blackcurrant and cranberry) during storage for 12 months as well as after reconstitution with water each month. Inulin and gum arabic were also added to the instant fruit powders at two levels (10% and 20% w/w of dry weight) to improve the cell survival and functional properties of the product. The best cell survival over the 12 months of storage was observed for the blackcurrant powder (almost no decrease) followed by strawberry (~ 0.3 log decrease), pomegranate (~ 0.9 log decrease), whereas the worst survival was obtained in cranberry powder (~ 4.5 logs). To explain these results multiple regression analysis was conducted with the log decrease [log10N0 month − log10N12 months] as the dependent variable and water activity, pH, citric acid, dietary fibre and total phenol as the independent variables. The results indicated that among all the examined factors, the [log10N0 month − log10N12 months] depended only on the water activity (P < 0.05). Inulin and gum arabic demonstrated a substantial protective effect on cell survival (1–1.5 log) in the case of cranberry, which was likely due to a physical interaction between the cells and the carbohydrates. After reconstituting the dried fruit powders at room temperature and measuring cell viability for up to 4 h, it was shown that in the case of strawberry juice there was no decrease, and very little in the case of pomegranate and blackcurrant juices (< 0.5 log). On the other hand, a significant decrease was observed for cranberry juice (P < 0.05), which increased as the storage time of the dried cranberry powder increased, indicating that the cells became more susceptible with prolonged storage. Multiple regression analysis indicated that the main factors influencing cell survival were water activity and pH, while citric acid, dietary fibre and total phenol did not have an effect. Furthermore, inulin and gum arabic addition did not have a significant (P > 0.05) effect upon reconstitution of the dried fruit powder. This study showed that instant juice powders are very good carriers of probiotic cells and constitute good alternatives to highly acidic fruit juices.

What determines the out-of-home placement of children in the USA?

Using NCANDS data of US child maltreatment reports for 2009, logistic regression, probit analysis, discriminant analysis and an artificial neural network are used to determine the factors which explain the decision to place a child in out-of-home care. As well as developing a new model for 2009, a previous study using 2005 data is replicated. While there are many small differences, the four estimation techniques give broadly the same results, demonstrating the robustness of the results. Similarly, apart from age and sexual abuse, the 2005 and 2009 results are roughly similar. For 2009, child characteristics (particularly child emotional problems) are more important than the nature of the abuse and the situation of the household; while caregiver characteristics are the least important. All these models have low explanatory power.

Individual differences in mental control predict involuntary musical imagery

The experience of earworms, a type of involuntary musical imagery, may reflect a systematic failure in mental control. This study focused on how individual differences in each of two factors, schizotypy, or “openness to experience”, and thought suppression might relate to the appearance of the involuntary musical image (earworm). Schizotypy, was measured by Raine’s schizotypal personality questionnaire (SPQ; Raine, 1991) and thought suppression was measured by the White Bear Suppression Inventory (WBSI; Wegner & Zanakos, 1994). Each was found to contribute independently to the overall experience of involuntary musical imagery. Schizotypy was correlated with the length and disruptiveness of earworms, the difficulty with which they were dismissed and the worry they caused, but was not correlated with the frequency of such intrusive imagery. In turn, schizotypy was predicted by suppression and intrusion components of WBSI. The WBSI is associated with the length, disruptiveness, difficulty dismissing and interference but not with the worry caused or the frequency of earworms. The assumption of “ownership” of earworms was also found to affect the extent to which the earworms were considered worrying. Multiple regression analysis showed that both schizotypy and the WBSI predicted the difficulty with which unwanted musical images were dismissed, but that the WBSI accounted for additional variance on top of that accounted for by schizotypy. Finally we consider how earworm management might relate to wider cognitive processes.

Impact of geographical region on urinary metabolomic and plasma fatty acid profiles in subjects with the metabolic syndrome across Europe: the LIPGENE study

The application of metabolomics in multi-centre studies is increasing. The aim of the present study was to assess the effects of geographical location on the metabolic profiles of individuals with the metabolic syndrome. Blood and urine samples were collected from 219 adults from seven European centres participating in the LIPGENE project (Diet, genomics and the metabolic syndrome: an integrated nutrition, agro-food, social and economic analysis). Nutrient intakes, BMI, waist:hip ratio, blood pressure, and plasma glucose, insulin and blood lipid levels were assessed. Plasma fatty acid levels and urine were assessed using a metabolomic technique. The separation of three European geographical groups (NW, northwest; NE, northeast; SW, southwest) was identified using partial least-squares discriminant analysis models for urine (R 2 X: 0•33, Q 2: 0•39) and plasma fatty acid (R 2 X: 0•32, Q 2: 0•60) data. The NW group was characterised by higher levels of urinary hippurate and N-methylnicotinate. The NE group was characterised by higher levels of urinary creatine and citrate and plasma EPA (20 : 5 n-3). The SW group was characterised by higher levels of urinary trimethylamine oxide and lower levels of plasma EPA. The indicators of metabolic health appeared to be consistent across the groups. The SW group had higher intakes of total fat and MUFA compared with both the NW and NE groups (P≤ 0•001). The NE group had higher intakes of fibre and n-3 and n-6 fatty acids compared with both the NW and SW groups (all P< 0•001). It is likely that differences in dietary intakes contributed to the separation of the three groups. Evaluation of geographical factors including diet should be considered in the interpretation of metabolomic data from multi-centre studies.

Metabolic phenotype modulation by caloric restriction in a lifelong dog study

Modeling aging and age-related pathologies presents a substantial analytical challenge given the complexity of gene−environment influences and interactions operating on an individual. A top-down systems approach is used to model the effects of lifelong caloric restriction, which is known to extend life span in several animal models. The metabolic phenotypes of caloric-restricted (CR; n = 24) and pair-housed control-fed (CF; n = 24) Labrador Retriever dogs were investigated by use of orthogonal projection to latent structures discriminant analysis (OPLS-DA) to model both generic and age-specific responses to caloric restriction from the 1H NMR blood serum profiles of young and older dogs. Three aging metabolic phenotypes were resolved: (i) an aging metabolic phenotype independent of diet, characterized by high levels of glutamine, creatinine, methylamine, dimethylamine, trimethylamine N-oxide, and glycerophosphocholine and decreasing levels of glycine, aspartate, creatine and citrate indicative of metabolic changes associated largely with muscle mass; (ii) an aging metabolic phenotype specific to CR dogs that consisted of relatively lower levels of glucose, acetate, choline, and tyrosine and relatively higher serum levels of phosphocholine with increased age in the CR population; (iii) an aging metabolic phenotype specific to CF dogs including lower levels of liproprotein fatty acyl groups and allantoin and relatively higher levels of formate with increased age in the CF population. There was no diet metabotype that consistently differentiated the CF and CR dogs irrespective of age. Glucose consistently discriminated between feeding regimes in dogs (≥312 weeks), being relatively lower in the CR group. However, it was observed that creatine and amino acids (valine, leucine, isoleucine, lysine, and phenylalanine) were lower in the CR dogs (<312 weeks), suggestive of differences in energy source utilization. 1H NMR spectroscopic analysis of longitudinal serum profiles enabled an unbiased evaluation of the metabolic markers modulated by a lifetime of caloric restriction and showed differences in the metabolic phenotype of aging due to caloric restriction, which contributes to longevity studies in caloric-restricted animals. Furthermore, OPLS-DA provided a framework such that significant metabolites relating to life extension could be differentiated and integrated with aging processes.

Novel single trial movement classification based on temporal dynamics of EEG

Various complex oscillatory processes are involved in the generation of the motor command. The temporal dynamics of these processes were studied for movement detection from single trial electroencephalogram (EEG). Autocorrelation analysis was performed on the EEG signals to find robust markers of movement detection. The evolution of the autocorrelation function was characterised via the relaxation time of the autocorrelation by exponential curve fitting. It was observed that the decay constant of the exponential curve increased during movement, indicating that the autocorrelation function decays slowly during motor execution. Significant differences were observed between movement and no moment tasks. Additionally, a linear discriminant analysis (LDA) classifier was used to identify movement trials with a peak accuracy of 74%.

The housing pathways of young people in the UK

The authors examine the housing pathways of young people in the UK in the years 1999 to 2008, and consider the changing nature of these pathways in the run up to 2020. They employ a highly innovative methodology, which begins with the identification and description of key drivers likely to affect young people’s housing circumstances in the future. The empirical identification and analysis of housing pathways is then achieved using multiple-sequence analysis and cluster analysis of the British Household Panel Survey, contextualised by qualitative interviews with a large sample of young people. The authors describe how the interactions between the meanings, perceptions, and aspirations of young people, and the opportunities and constraints imposed by the drivers, are having a major impact on young people’s housing pathways, resulting in considerable housing policy challenges, particularly in relation to the private rented sector

Motor imagery-induced EEG patterns in individuals with spinal cord injury and their impact on brain–computer interface accuracy

Objective. Assimilating the diagnosis complete spinal cord injury (SCI) takes time and is not easy, as patients know that there is no ‘cure’ at the present time. Brain–computer interfaces (BCIs) can facilitate daily living. However, inter-subject variability demands measurements with potential user groups and an understanding of how they differ to healthy users BCIs are more commonly tested with. Thus, a three-class motor imagery (MI) screening (left hand, right hand, feet) was performed with a group of 10 able-bodied and 16 complete spinal-cord-injured people (paraplegics, tetraplegics) with the objective of determining what differences were present between the user groups and how they would impact upon the ability of these user groups to interact with a BCI. Approach. Electrophysiological differences between patient groups and healthy users are measured in terms of sensorimotor rhythm deflections from baseline during MI, electroencephalogram microstate scalp maps and strengths of inter-channel phase synchronization. Additionally, using a common spatial pattern algorithm and a linear discriminant analysis classifier, the classification accuracy was calculated and compared between groups. Main results. It is seen that both patient groups (tetraplegic and paraplegic) have some significant differences in event-related desynchronization strengths, exhibit significant increases in synchronization and reach significantly lower accuracies (mean (M) = 66.1%) than the group of healthy subjects (M = 85.1%). Significance. The results demonstrate significant differences in electrophysiological correlates of motor control between healthy individuals and those individuals who stand to benefit most from BCI technology (individuals with SCI). They highlight the difficulty in directly translating results from healthy subjects to participants with SCI and the challenges that, therefore, arise in providing BCIs to such individuals

Motor imagery induced EEG patterns in spinal cord injury patients and their impact on Brain-Computer Interface accuracy

OBJECTIVE: Assimilating the diagnosis complete spinal cord injury (SCI) takes time and is not easy, as patients know that there is no 'cure' at the present time. Brain-computer interfaces (BCIs) can facilitate daily living. However, inter-subject variability demands measurements with potential user groups and an understanding of how they differ to healthy users BCIs are more commonly tested with. Thus, a three-class motor imagery (MI) screening (left hand, right hand, feet) was performed with a group of 10 able-bodied and 16 complete spinal-cord-injured people (paraplegics, tetraplegics) with the objective of determining what differences were present between the user groups and how they would impact upon the ability of these user groups to interact with a BCI. APPROACH: Electrophysiological differences between patient groups and healthy users are measured in terms of sensorimotor rhythm deflections from baseline during MI, electroencephalogram microstate scalp maps and strengths of inter-channel phase synchronization. Additionally, using a common spatial pattern algorithm and a linear discriminant analysis classifier, the classification accuracy was calculated and compared between groups. MAIN RESULTS: It is seen that both patient groups (tetraplegic and paraplegic) have some significant differences in event-related desynchronization strengths, exhibit significant increases in synchronization and reach significantly lower accuracies (mean (M) = 66.1%) than the group of healthy subjects (M = 85.1%). SIGNIFICANCE: The results demonstrate significant differences in electrophysiological correlates of motor control between healthy individuals and those individuals who stand to benefit most from BCI technology (individuals with SCI). They highlight the difficulty in directly translating results from healthy subjects to participants with SCI and the challenges that, therefore, arise in providing BCIs to such individuals.

Robust future changes in temperature variability under greenhouse gas forcing and the relationship with thermal advection

Recent temperature extremes have highlighted the importance of assessing projected changes in the variability of temperature as well as the mean. A large fraction of present day temperature variance is associated with thermal advection, as anomalous winds blow across the land-sea temperature contrast for instance. Models project robust heterogeneity in the 21st century warming pattern under greenhouse gas forcing, resulting in land-sea temperature contrasts increasing in summer and decreasing in winter, and the pole-to-equator temperature gradient weakening in winter. In this study, future monthly variability changes in the 17 member ensemble ESSENCE are assessed. In winter, variability in midlatitudes decreases while in very high latitudes and the tropics it increases. In summer, variability increases over most land areas and in the tropics, with decreasing variability in high latitude oceans. Multiple regression analysis is used to determine the contributions to variability changes from changing temperature gradients and circulation patterns. Thermal advection is found to be of particular importance in the northern hemisphere winter midlatitudes, where the change in mean state temperature gradients alone could account for over half the projected changes. Changes in thermal advection are also found to be important in summer in Europe and coastal areas, although less so than in winter. Comparison with CMIP5 data shows that the midlatitude changes in variability are robust across large regions, particularly high northern latitudes in winter and mid northern latitudes in summer.

An LDA and probability-based classifier for the diagnosis of Alzheimer's Disease from structural MRI

In this paper a custom classification algorithm based on linear discriminant analysis and probability-based weights is implemented and applied to the hippocampus measurements of structural magnetic resonance images from healthy subjects and Alzheimer’s Disease sufferers; and then attempts to diagnose them as accurately as possible. The classifier works by classifying each measurement of a hippocampal volume as healthy controlsized or Alzheimer’s Disease-sized, these new features are then weighted and used to classify the subject as a healthy control or suffering from Alzheimer’s Disease. The preliminary results obtained reach an accuracy of 85.8% and this is a similar accuracy to state-of-the-art methods such as a Naive Bayes classifier and a Support Vector Machine. An advantage of the method proposed in this paper over the aforementioned state of the art classifiers is the descriptive ability of the classifications it produces. The descriptive model can be of great help to aid a doctor in the diagnosis of Alzheimer’s Disease, or even further the understand of how Alzheimer’s Disease affects the hippocampus.