Analysis of Muscle Fatigue Conditions in Surface EMG Signal with A Novel Hilbert Marginal Spectrum Entropy Method

Surface Electromyogram is the superposition of action potentials generated during muscle contraction that provides useful indices for biomechanics. Such signals are nonstationary and the measure of its time varying components are essentially needed to identify the progression of fatigue. In this work, an attempt has been made to identify the muscle fatigue condition using Hilbert-Huang Marginal Spectrum. The novelty of the proposed framework is that the Marginal Spectrum is computed by ordering the instantaneous frequency of an Intrinsic Mode Function obtained for a signal to be analyzed. For this purpose, signals are recorded from the biceps brachii muscles of 50 healthy volunteers using isometric and dynamic contraction exercise protocols. Initially, each signal is equally partitioned into 10 segments, where the 1^st, 5^th and 10^th segments are analyzed. Further, metrics estimated from marginal spectrum such as area under the curve, skewness and kurtosis are calculated for the considered three segments. The preliminary results show that the estimated metrics are able to distinguish the fatiguing conditions. The recorded signals show low amplitude and high frequencies in nonfatigue region and vice-versa. The obtained results are statistically significant with p <; 0.005. It appears that the instantaneous frequency based marginal spectrum estimator is able to measure the fatigue index. Therefore, the proposed method can be useful in analyzing fatigue condition of skeletal muscles.

Characterization of Alzheimer conditions in MR images using volumetric and sagittal brainstem texture features

BACKGROUND AND OBJECTIVE

Brainstem analysis in Magnetic Resonance Images is essential to detect Alzheimer's condition in the preclinical stages. In this work, an attempt has been made to segment the brainstem in sagittal (2D) and volumetric (3D) images and evaluate texture changes to differentiate Alzheimer's disease (AD) stages.

METHOD

The images obtained from a public access database are spatial normalized, skull stripped and contrast enhanced. Morphological Reconstruction based Fast and Robust Fuzzy 'C' Means technique is used to cluster the brain tissue in preprocessed images into three groups namely cerebrospinal fluid, grey matter and white matter. Brainstem is segmented from the white matter tissue using connected component labelling. Texture features from volumetric and sagittal brainstem slices are extracted and its statistical significance is evaluated.

RESULTS

Results show that the proposed approach is able to segment the brainstem from all the considered images. Variation in texture is observed to be less than 2% among sagittal brainstem slices. Additionally, midsagittal and volumetric features are correlated, suggesting that midsagittal brainstem structure gives an estimate of brainstem volume. Texture features extracted from midsagittal slice shows significant variation (p < 0.05) and is able to differentiate AD classes.

CONCLUSION

Midsagittal brainstem texture features are able to capture the changes occurring in the early stages of disease condition. As the distinction of AD in preclinical stage is complex and clinically significant, this approach could be useful for early diagnosis of the disease.

Ultrafine Pt Nanoparticles Stabilized by MoS2/N-Doped Reduced Graphene Oxide as a Durable Electrocatalyst for Alcohol Oxidation and Oxygen Reduction Reactions

Direct alcohol fuel cells play a pivotal role in the synthesis of catalysts because of their low cost, high catalytic activity, and long durability in half-cell reactions, which include anode (alcohol oxidation) and cathode (oxygen reduction) reactions. However, platinum catalysts suffer from CO tolerance, which affects their stability. The present study focuses on ultrafine Pt nanoparticles stabilized by flowerlike MoS₂/N-doped reduced graphene oxide (Pt@MoS₂/NrGO) architecture, developed via a facile and cost-competitive approach that was performed through the hydrothermal method followed by the wet-reflux strategy. Fourier transform infrared spectra, X-ray diffraction patterns, Raman spectra, X-ray photoelectron spectra, field-emission scanning electron microscopy, and transmission electron microscopy verified the conversion to Pt@MoS₂/NrGO. Pt@MoS₂/NrGO was applied as a potential electrocatalyst toward the anode reaction (liquid fuel oxidation) and the cathode reaction (oxygen reduction). In the anode reaction, Pt@MoS₂/NrGO showed superior activity toward electro-oxidation of methanol, ethylene glycol, and glycerol with mass activities of 448.0, 158.0, and 147.0 mA/mg_Pt, respectively, approximately 4.14, 2.82, and 3.34 times that of a commercial Pt-C (20%) catalyst. The durability of the Pt@MoS₂/NrGO catalyst was tested via 500 potential cycles, demonstrating less than 20% of catalytic activity loss for alcohol fuels. In the cathode reaction, oxygen reduction reaction results showed excellent catalytic activity with higher half-wave potential at 0.895 V versus a reversible hydrogen electrode for Pt@MoS₂/NrGO. The durability of the Pt@MoS₂/NrGO catalyst was tested via 30 000 potential cycles and showed only 15 mV reduction in the half-wave potential, whereas the Pt@NrGO and Pt-C catalysts experienced a much greater shift (Pt@NrGO, ∼23 mV; Pt-C, ∼20 mV).

Thermally Reduced Graphene Oxide as a Counter Electrode Material for Dye-Sensitized Solar Cells

In this present study, a highly conductive thermally reduced graphene oxide (TRGO) was synthesized by a low temperature thermal reduction method using RF heating, under an argon-hydrogen atmosphere. The crystallinity and morphology were examined by X-ray diffraction, Raman spectroscopy and TEM analysis. The chemical structure including the functional groups present on TRGO was studied using X-ray photoelectron spectroscopy and FTIR analysis. The studies reveal that thermal reduction of graphene oxide was successful under the experimental conditions and that the TRGO had high crystallinity. Further, the performance of the as-prepared TRGO was tested as a counter electrode (CE) in a dye-sensitized solar cell (DSSC). The maximum power conversion efficiency (PCE) obtained was 4.86% for TRGO under one sun illumination, which is comparable to that of a platinum CE-based DSSC (5.24%). The electrocatalytic activity and electron transfer kinetics were examined by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and Tafel measurements. The series resistance (R_s) and charge transfer resistance (R_ct) values were found to be 35.4 Ωcm^-2 and 56.40 Ωcm^-2 for TRGO. The results reveal that the TRGO had an electrocatalytic performance similar to that of Pt, making TRGO-CEs promising alternatives to the conventional Pt-CEs in DSSCs.

Randomized, double-blind, placebo-controlled, crossover study of the effects of repeated-dose caffeine on neurobehavioral performance during 48 h of total sleep deprivation

RATIONALE

Caffeine is widely used as a countermeasure against neurobehavioral impairment during sleep deprivation. However, little is known about the pharmacodynamic profile of caffeine administered repeatedly during total sleep deprivation.

OBJECTIVES

To investigate the effects of repeated caffeine dosing on neurobehavioral performance during sleep deprivation, we conducted a laboratory-based, randomized, double-blind, placebo-controlled, crossover, multi-dose study of repeated caffeine administration during 48 h of sleep deprivation. Twelve healthy adults (mean age 27.4 years, six women) completed an 18-consecutive-day in-laboratory study consisting of three 48 h total sleep deprivation periods separated by 3-day recovery periods. During each sleep deprivation period, subjects were awakened at 07:00 and administered caffeine gum (0, 200, or 300 mg) at 6, 18, 30, and 42 h of wakefulness. The Psychomotor Vigilance Test and Karolinska Sleepiness Scale were administered every 2 h.

RESULTS

The 200 and 300 mg doses of caffeine mitigated neurobehavioral impairment across the sleep deprivation period, approaching two-fold performance improvements relative to placebo immediately after the nighttime gum administrations. No substantive differences were noted between the 200 mg and 300 mg caffeine doses, and adverse effects were minimal.

CONCLUSIONS

The neurobehavioral effects of repeated caffeine dosing during sleep deprivation were most evident during the circadian alertness trough (i.e., at night). The difference between the 200 mg and 300 mg doses, in terms of the mitigation of performance impairment, was small. Neither caffeine dose fully restored performance to well-rested levels. These findings inform the development of biomathematical models that more accurately account for the time of day and sleep pressure-dependent effects of caffeine on neurobehavioral performance during sleep loss.

Multifractal analysis of uterine electromyography signals to differentiate term and preterm conditions

In this study, an attempt has been made to identify the origin of multifractality in uterine electromyography signals and to differentiate term (gestational age > 37 weeks) and preterm (gestational age ≤ 37 weeks) conditions by multifractal detrended moving average technique. The signals obtained from a publicly available database, recorded from the abdominal surface during the second trimester, are used in this study. The signals are preprocessed and converted to shuffle and surrogate series to examine the source of multifractality. Multifractal detrended moving average algorithm is applied on all the signals. The presence of multifractality is verified using scaling exponents, and multifractal spectral features are extracted from the spectrum. The variation of multifractal features in term and preterm conditions is analyzed statistically using Student's t-test. The results of scaling exponents show that the uterine electromyography or electrohysterography signals reveal multifractal characteristics in term and preterm conditions. Further investigation indicates the existence of long-range correlation as the primary source of multifractality. Among all extracted features, strength of multifractality, exponent index, and maximum and peak singularity exponents are statistically significant ( p < 0.05) in differentiating term and preterm conditions. The coefficient of variation is found to be lower for strength of multifractality and peak singularity exponent, which reveal that these features exhibit less inter-subject variance. Hence, it appears that multifractal analysis can aid in the diagnosis of preterm or term delivery of pregnant women.

Proposal of a Machine Learning Approach to Differentiate Mild and Alzheimer's Condition in MR Images Using Shape Changes in Corpus Callosum

The brain ventricles are surrounded by periventricular structures that are affected by dementia which results in neurodegenerative disorder such as Alzheimer's Disease (AD). The change in morphology of these structures must effect the shape and volume of Corpus Callosum (CC). These alterations in morphology of CC are considered to be a significant image biomarker for the early diagnosis of Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) subjects. Shape descriptors provide useful information about change in morphology of various brain structures during disease progression. In this work, Lattice Boltzmann criterion based hybrid level set method (LSM) is used to segment CC. Geometric and pseudo-Zernike moment measures are extracted from the segmented area of CC and are statistically analyzed using Statistical Package for Social Science (SPSS). The performance metric of significant moments is validated using machine learning algorithms. Results demonstrate that, hybrid level set is able to delineate CC and the segmented images are in high correlation with ground truth images. High accuracy value of 85.0% has been achieved using Multilayer Perceptron (MLP) classifier for Healthy Control (HC) versus AD subjects. Thus, moments are able to classify MCI from HC and AD subjects with high accuracy and hence the results are found to be clinically significant.

De-symmetrizing periodically grafted amphiphilic copolymers: design, synthesis and generation of Janus folded chains

The mutual immiscibility between the three segments, namely backbone HC, and pendant PEG and FC segments, causes zigzag folding of the polymer such that FC segments lie on one side and PEG on the other, thereby generating Janus-type folded chains.

Orthogonally clickable hyperbranched polymers: effect of reactant size and polarity on core-functionalization of peripherally jacketed HBPs

Using an orthogonally clickable strategy, the accessibility of internal allyl groups in jacketed HBPs, bearing either PEG or docosyl peripheral segments, was shown to depend both on the size and relative polarity of the reactant thiol.

Analysis of uterine electromyography signals in preterm condition using multifractal algorithm

In this work, an attempt has been made to analyze the preterm (gestation period $\leq 37$ weeks) condition using uterine electromyography (EMG) signals and multifractal detrended fluctuation analysis (MFDFA). The signals recorded from the electrodes placed on the surface of abdomen are used for this study and these are obtained from a publically available online database. These signals are preprocessed using 4-pole digital Butterworth filter. The preprocessed signals are subjected to MFDFA to extract multifractal features namely maximum singularity exponent, peak singularity exponent, strength of multifractality and exponent index. Generalized Hurst exponent extracted from the signals indicate that uterine EMG signals show multifractal behavior in preterm condition. Among the extracted features the coefficient of variation is found to be lower for peak singularity exponent. This indicates that this feature have lower inter-subject variability. Hence, it appears that the multifractal features can help in the assessment of uterine EMG signals for preterm detection.

Surface-Functionalized Polystyrene Latexes Using Itaconate-Based Surfmers

Itaconic acid was readily transformed to a series of amphiphilic diesters via stepwise esterification of itaconic anhydride; the diesters carry one alkyl (cetyl or octyl) group and either a PEG, glyceryl, or dopamine segment. These diesters were used as surfmers for the preparation of polystyrene (PS) emulsions, with the expectation that the surface of the emulsion particles would carry PEG, glyceryl or dopamine units. NMR spectroscopic studies revealed that the surfmers were covalently incorporated into the polystyrene chains; furthermore, NMR tube polymerization experiments also confirmed that when the PEG surfmer was used, the PEG segments are indeed present on the surface of the emulsion particles. The size of the PEGlyated PS emulsions was readily varied from 35 to 140 nm by changing the mole fraction of surfmer used. In the case of the glyceryl and dopamine carrying surfmers, an octyl unit was used as the hydrophobic segment to ensure appropriate hydrophobic-hydrophilic balance; it was noticed that significantly larger mole fractions of the surfmers were required (15-20 mol %) to generate stable emulsions with particle sizes of about 150 nm. The PS emulsions carrying dopamine units on the surface were found to adhere to glass surfaces; thus suggesting that such "sticky" emulsion particles could be used to functionalize different types of surfaces. Finally, itaconate diesters bearing cetyl and perfluorooctyl segments were also prepared and shown to copolymerize with styrene to generate fluoroalkyl-enriched PS copolymers; these were used to generate hydrophobic coatings, with water contact angles of over 120°. Thus, itaconate-based surfmers are readily accessible alternatives for the preparation of emulsions with tailored size and surface functionality.

Hybrasurfs-A New Class of Hyperbranched Surfactants

A hyperbranched (HB) polyester carrying peripheral allyl groups was prepared by melt-condensation of a suitably designed AB₂ monomer bearing two allyl ester groups and one hydroxyl group. The periphery of the hyperbranched polymer was co-clicked with two different organic thiols, namely, hexadecane thiol and 3-mercaptopropionic acid, using the thiol-ene reaction. Three different samples with varying mole fractions of the hydrophilic carboxylic acid groups were prepared; the conformational adaptability of the hyperbranched polymer backbone permitted these amphiphilic systems to form Janus structures that exhibit surfactant-like properties and, therefore, we have termed them hybrasurfs. These polymers behave like clusters of surfactants that have been stitched at the waist by the HB polymer backbone; the Langmuir isotherms revealed the formation of a monolayer, and in two of the samples having higher mole fractions of hexadecyl segments a weak inflection in the isotherm is seen. This suggests a densification, typically implying the crystallization of the alkyl segment at the air-water interface. The monolayers were transferred onto a substrate, and their heights were estimated using atomic force microscopy; the values thus obtained were in reasonable agreement with the expected value. The water contact angles of the substrates bearing the transferred monolayers of the three different samples (transferred at two different points along the isotherm) were measured; it was seen that the sample carrying the highest mole fraction of hexadecyl chains exhibited a significantly larger contact angle when compared to that of the other two samples. Interestingly, these hybrasurfs also formed vesicles in water and were shown to encapsulate water-soluble dyes, such as Eosin Y. Thus, this class of readily accessible amphiphilic HB polymers that behave as a cluster of surfactants opens some interesting possibilities for further exploration.