Instantaneous Mean Frequency Research Articles

Epilepsy EEG classification using morphological component analysis

In this paper, we have proposed an application of sparse-based morphological component analysis (MCA) to address the problem of classification of the epileptic seizure using time series electroencephalogram (EEG). MCA was employed to decompose the EEG signal segments considering its morphology during epileptic events using undecimated wavelet transform (UDWT), local discrete cosine transform (LDCT), and Dirac bases forming the over-complete dictionary. Frequency-modulated time frequency features were extracted after applying the Hilbert transform. Feature root mean instantaneous frequency square (RMIFS) and its parameters and parameters ratio are used in two different pairs for classification using support vector machine (SVM), showing good and comparable results.

A virtual injection sensor by means of time frequency analysis

Abstract A time frequency analysis has been applied to an experimental pressure signal that is measured along a high-pressure pipe that connects the rail to an injector in a fuel injection system for diesel engines. An experimental test campaign has been carried out at a high-performance hydraulic rig for Common Rail systems. The variations in the mean instantaneous frequency, which is calculated from a spectrogram of the experimental injector inlet pressure time histories, are related to key events pertaining to the injection phase. The physical meaning of these variations in the mean instantaneous frequency is identified through a comparison with the outcomes of a numerical simulation using a previously developed one-dimensional model of the injection system. This tool allows the lift of the mobile valves, the instantaneous injected flow-rate and the pressure transients inside the injector to be predicted accurately. The objective of the research has been to realize a virtual sensor to detect the opening and closure instants of the mobile valves within the injector, on the basis of the pattern of the mean instantaneous frequency trace. The realized virtual sensor has been applied to the analysis of both single and multiple injection events.

Differential effects of radiant and mechanically applied thermal stimuli on human C-tactile afferent firing patterns.

C-tactile (CT) afferents respond to gentle tactile stimulation, but only a handful of studies in humans and animals have investigated whether their firing is modified by temperature. We describe the effects of radiant thermal stimuli, and of stationary and very slowly moving mechanothermal stimuli, on CT afferent responses. We find that CT afferents are primarily mechanoreceptors, as they fired little during radiant thermal stimuli, but they exhibited different patterns of firing during combined mechano-cool stimulation compared with warming. CTs fired optimally to gentle, very slowly moving, or stationary mechanothermal stimuli delivered at neutral temperature (~32°C, normal skin temperature), but they responded with fewer spikes (median 67% decrease) and at significantly lower rates (47% decrease) during warm (~42°C) tactile stimuli. During cool tactile stimuli (~18°C), their mean instantaneous firing frequency significantly decreased by 35%, but they often fired a barrage of afterdischarge spikes at a low frequency (~5 Hz) that outlasted the mechanical stimulus. These effects were observed under a variety of stimulus conditions, including during stationary and slowly moving touch (0.1 cm/s), and we complemented these tactile approaches using a combined electrical-thermal stimulation experiment where we found a suppression of spiking during warming. Overall, CT afferents are exquisitely sensitive to tactile events, and we show that their firing is modulated with touch temperatures above and below neutral skin temperature. Warm touch consistently decreased their propensity to fire, whereas cool touch produced lower firing rates but afterdischarge spiking. NEW & NOTEWORTHY C-tactile (CT) afferents are thought to underpin pleasant touch, and previous work has shown that they respond optimally to a slow caress delivered at typical (neutral) skin temperature. Here, we show that, although CTs are primarily mechanoreceptive afferents, they are modified by temperature: warm touch decreases their firing, whereas cool touch produces lower firing rates but long-lasting spiking, frequently seen as afterdischarges. This has implications for the encoding of affective sensory events in human skin.

Classification of ictal and interictal EEG using RMS frequency, dominant frequency, root mean instantaneous frequency square and their parameters ratio

Abstract In this work, we have proposed to use root mean square (RMS) frequency fr and dominant frequency fd along with the ratio of their contributing parameters as features for classification of interictal and ictal electroencephalogram (EEG). Empirical mode decomposition (EMD) is used for decomposing EEG into a finite set of intrinsic mode functions (IMFs). IMFs are then represented into analytic form by applying Hilbert transform over it. Analytical form of these IMFs are utilized to extract the features. Kruskal–Wallis test was applied to determine features from first two IMFs to be used for classification purpose using support vector machine (SVM). A novel feature root mean instantaneous frequency square (RMIFS) fR been proposed using relationship between RMS frequency and dominant frequency to define it as square root of the sum of time averaged instantaneous frequency spread around center frequency and square of center frequency. It is also been used along with its parameters ratio for ictal and interictal classification. The best results were observed using RMS frequency and its parameters ratio from IMF2 to discriminate ictal from interictal. The highest average accuracy and sensitivity observed was 99.91%, 100%. An adaptive thresholding method has also been proposed in this work to recover the false positives. Adaptive thresholding was able to recover the average accuracy.

Neural Responses to Physical Characteristics of a High-velocity, Low-amplitude Spinal Manipulation: Effect of Thrust Direction.

Electrophysiological recordings were obtained from proprioceptors in deep lumbar paraspinal muscles of anesthetized cats during high-velocity low-amplitude spinal manipulation (HVLA-SM). To determine how thrust direction of an HVLA-SM affects neural input from back musculature. A clinician's ability to apply the thrust of an HVLA-SM in a specified direction is considered an important component of its optimal delivery. However, previous biomechanical studies indicate that the shear force component of the thrust vector is not actually transmitted to paraspinal tissues deep to the thoracolumbar fascia because the skin-fascia interface is frictionless. Neural activity from muscle spindles in the multifidus and longissimus muscles was recorded from L6 dorsal rootlets in 18 anesthetized cats. After preload to the spinal tissues, HVLA-SMs (100-ms thrust duration) were applied through the intact skin overlying the L6 lamina. Thrusts were applied at angles oriented perpendicularly to the back and obliquely at 15° and 30° medialward or cranialward using a 6 × 6 Latin square design with three replicates. The normal force component was kept constant at 21.3 N. HVLA-SMs were preceded and followed by simulated spinal movement applied to the L6 vertebra. Changes in mean instantaneous discharge frequency (ΔMIF) of muscle spindles were determined both during the thrust and spinal movement. ΔMIFs during the HVLA-SM thrust were significantly greater in response to all thrust directions compared with the preload alone, but there was no difference in ΔMIF for any of the thrust directions during the HVLA-SM. HVLA-SM decreased some of the responses to simulated spinal movement but thrust direction had no effect on these changes. The shear force component of an HVLA-SM's thrust vector is not transmitted to the underlying vertebra sufficient to activate muscle spindles of the attached muscles. Implications for clinical practice and clinical research are discussed. N/A.

Continuous Wavelet Transform Analysis of Surface Electromyography for Muscle Fatigue Assessment on the Elbow Joint Motion

Studying muscle fatigue plays an important role in preventing the risks associated with musculoskeletal disorders. The effect of elbow-joint angle on time-frequency parameters during a repetitive motion provides valuable information in finding the most accurate position of the angle causing muscle fatigue. Therefore, the purpose of this study is to analyze the effect of muscle fatigue on the spectral and time-frequency domain parameters derived from electromyography (EMG) signals using the Continuous Wavelet Transform (CWT). Four male participants were recruited to perform a repetitive motion (flexion and extension movements) from a non-fatigue to fatigue condition. EMG signals were recorded from the biceps muscle. The recorded EMG signals were then analyzed offline using the complex Morlet wavelet. The time-frequency domain data were analyzed using the time-averaged wavelet spectrum (TAWS) and the Scale-Average Wavelet Power (SAWP) parameters. The spectral domain data were analyzed using the Instantaneous Mean Frequency (IMNF) and the Instantaneous Mean Power Spectrum (IMNP) parameters. The index of muscle fatigue was observed by calculating the increase of the IMNP and the decrease of the IMNF parameters. After performing a repetitive motion from non-fatigue to fatigue condition, the average of the IMNF value decreased by 15.69% and the average of the IMNP values increased by 84%, respectively. This study suggests that the reliable frequency band to detect muscle fatigue is 31.10-36.19Hz with linear regression parameters of 0.979mV^2Hz^(-1) and 0.0095mV^2Hz^(-1) for R^2 and slope, respectively.

Alterations in Spectral Attributes of Surface Electromyograms after Utilization of a Foot Drop Stimulator during Post-Stroke Gait.

A foot drop stimulator (FDS) is a rehabilitation intervention that stimulates the common peroneal nerve to facilitate ankle dorsiflexion at the appropriate time during post-stroke hemiplegic gait. Time-frequency analysis (TFA) of non-stationary surface electromyograms (EMG) and spectral variables such as instantaneous mean frequency (IMNF) can provide valuable information on the long-term effects of FDS intervention in terms of changes in the motor unit (MU) recruitment during gait, secondary to improved dorsiflexion. The aim of this study was to apply a wavelet-based TFA approach to assess the changes in neuromuscular activation of the tibialis anterior (TA), soleus (SOL), and gastrocnemius (GA) muscles after utilization of an FDS during gait post-stroke. Surface EMG were collected bilaterally from the TA, SOL, and GA muscles from six participants (142.9 ± 103.3 months post-stroke) while walking without the FDS at baseline and 6 months post-FDS utilization. Continuous wavelet transform was performed to get the averaged time-frequency distribution of band pass filtered (20-300 Hz) EMGs during multiple walking trials. IMNFs were computed during normalized gait and were averaged during the stance and swing phases. Percent changes in the energies associated with each frequency band of 25 Hz between 25 and 300 Hz were computed and compared between visits. Averaged time-frequency representations of the affected TA, SOL, and GA EMG show altered spectral attributes post-FDS utilization during normalized gait. The mean IMNF values for the affected TA were significantly lower than the unaffected TA at baseline (p = 0.026) and follow-up (p = 0.038) during normalized stance. The mean IMNF values significantly increased (p = 0.017) for the affected GA at follow-up during normalized swing. The frequency band of 250-275 Hz significantly increased in the energies post-FDS utilization for all muscles. The application of wavelet-based TFA of EMG and outcome measures (IMNF, energy) extracted from the time-frequency distributions suggest alterations in MU recruitment strategies after the use of FDS in individuals with chronic stroke. This further establishes the efficacy of FDS as a rehabilitation intervention that may promote motor recovery in addition to treating the secondary complications of foot drop due to post-stroke hemiplegia.

The efficiency of seismic attributes to differentiate between massive and non-massive carbonate successions for hydrocarbon exploration activity

The present work investigates the efficiency of applying volume seismic attributes to differentiate between massive and non-massive carbonate sedimentary successions on using seismic data. The main objective of this work is to provide a pre-drilling technique to recognize the porous carbonate section (probable hydrocarbon reservoirs) based on seismic data. A case study from the Upper Cretaceous – Eocene carbonate successions of Abu Gharadig Basin, northern Western Desert of Egypt has been tested in this work. The qualitative interpretations of the well-log data of four available wells distributed in the study area, namely; AG-2, AG-5, AG-6 and AG-15 wells, has confirmed that the Upper Cretaceous Khoman A Member represents the massive carbonate section whereas the Eocene Apollonia Formation represents the non-massive carbonate unit. The present work have proved that the most promising seismic attributes capable of differentiating between massive and non-massive carbonate sequences are; Root Mean Square (RMS) Amplitude, Envelope (Reflection Strength), Instantaneous Frequency, Chaos, Local Flatness and Relative Acoustic Impedance.

Characteristics of Paraspinal Muscle Spindle Response to Mechanically Assisted Spinal Manipulation: A Preliminary Report

ObjectivesThe purpose of this preliminary study is to determine muscle spindle response characteristics related to the use of 2 solenoid powered clinical mechanically assisted manipulation (MAM) devices. MethodsL6 muscle spindle afferents with receptive fields in paraspinal muscles were isolated in 6 cats. Neural recordings were made during L7 MAM thrusts using the Activator V (Activator Methods Int. Ltd., Phoenix, AZ) and/or Pulstar (Sense Technology Inc., Pittsburgh, PA) devices at their 3 lowest force settings. Mechanically assisted manipulation response measures included (a) the time required post-thrust until the first action potential, (b) differences in mean frequency (MF) and mean instantaneous frequency (MIF) 2 seconds before and after MAM, and (c) the time required for muscle spindle discharge (MF and MIF) to return to 95% of baseline after MAM. ResultsDepending on device setting, between 44% to 80% (Pulstar) and 11% to 63% (Activator V) of spindle afferents required >6 seconds to return to within 95% of baseline MF values; whereas 66% to 89% (Pulstar) and 75% to 100% (Activator V) of spindle responses returned to within 95% of baseline MIF in <6 seconds after MAM. Nonparametric comparisons between the 22 N and 44 N settings of the Pulstar yielded significant differences for the time required to return to baseline MF and MIF. ConclusionShort duration (<10 ms) MAM thrusts decrease muscle spindle discharge with a majority of afferents requiring prolonged periods (>6 seconds) to return to baseline MF activity. Physiological consequences and clinical relevance of described MAM mechanoreceptor responses will require additional investigation.

Classification of EMG Signals by BFA-Optimized GSVCM for Diagnosis of Fatigue Status

In this paper, a novel bacterial foraging algorithm (BFA)-Gaussian support vector classifier machine (GSVCM) model was proposed to improve the fatigue classification accuracy of electromyography (EMG) signals. This optimization mechanism involves the kernel parameter setting in the GSVCM training procedure, which significantly influences the classification accuracy. Experiments were conducted based on the EMG signal to differentiate the normal and fatigue status. In the proposed method, the EMG signals were decomposed into intrinsic mode functions by ensemble empirical mode decomposition (EEMD) before the mean instantaneous frequency could be obtained by Hilbert transform (HT). Finally, the fatigue statistical features can be extracted from fast Fourier transform and EEMD—HT. The application of this model to the fatigue status recognition of EMG signal indicated that further significant enhancement of the classification accuracy can be achieved by the proposed BFA-GSVCM classification system. The diagnostic method is effective and feasible.

Intermuscular coupling characteristics based on variational mode decomposition-coherence

Intermuscular coupling is defined as the interaction, correlation and coordination between different muscles during the body movement, which could be revealed by the synchronization analysis of surface electromyogram (sEMG). The multiscaled coherence analysis of sEMG signals could describe the multiple spatial and temporal functional connection characteristics of intermuscular coupling, which could be helpful for understanding the multiple spatial and temporal coupling mechanism of neuromuscular system. Furthermore, the coupling characteristics in frequency band of sEMG generally reflect the functional connection between muscles which relate to motion control and coordinative mechanism of the central nervous system (CNS). In this paper, we combine variational mode decomposition (VMD) and intermuscular coherence (IMC) analysis to propose a new method named VMD-IMC to quantitatively describe the muscular coupling characteristics in the corresponding frequency bands. First, sEMG data of flexor digitorum superficialis (FDS), flexor carpi ulnaris (FCU) and extensor digitorum (ED) are recorded simultaneously from twenty healthy subjects (253 years) who perform the designed grip task at sustained 20% maximum voluntary contraction under the static load. Then, the VMD approach is employed to adaptively decompose sEMG into several intrinsic mode functions to describe the information about different time-frequency scales. Furthermore, the coherence on different time-frequency scales between different sEMG signals is analyzed, and the significant coherent area index is calculated to quantitatively describe the functional coupling characteristics of the feature bands. And combining VMD with Hilbert transform, we calculate root mean square and mean instantaneous frequency (MIF) to describe the variations of energy and frequency of each muscle. The results show that coupling strengths increase with time, respectively, in beta (15-30 Hz) and gamma (30-45 Hz) band between two muscles (FDS vs FCU, FDS vs ED) during the sustained static force with low load. In addition, compared with the coupling between FDS and ED, the couplings between FDS and FCU in beta and gamma band under the condition of fatigue present more significant changes and similar trend in MIF variation with time. The obtained results reveal that the congenerous muscle is coordinated by CNS in a more synchronous way during the sustained isometric fatiguing contraction.

Standing balance post total knee arthroplasty: sensitivity to change analysis from four to twelve weeks in 466 patients

Little is known about how static standing balance changes post total knee arthroplasty (TKA). The primary aim of this study was to examine the sensitivity to change and redundancy of center of pressure (COP) variables post-TKA. The secondary aim was to compare the sensitivity of these measures to standard clinical assessments of one repetition maximum knee extension strength and fast pace gait speed. 466 participants performed instrumented double-limb standing balance tests with eyes open at 4 and 12 weeks post-TKA. Measures of COP standard deviation, amplitude, root mean square (RMS), path length, detrended fluctuation analysis (DFA) and signal frequency content for the medial-lateral (ML) and anterior-posterior (AP) axes were examined. Significant decreases in total path length, ML variables related to sway velocity and AP signal complexity and frequency were observed. Inter-session Cohen's d effect size (ES) revealed the strongest effect was for high velocity ML path length, with a 12% decrease in this rapid sway. This variable, along with AP mean instantaneous frequency and AP DFA, were the only ones significantly different with effect sizes >0.20 and non-redundant (Spearman's rho <0.75). The ES of COP-derived variables (maximum=0.45) were lower than gait speed (1.40) and knee extensor strength (1.54). Increased high velocity ML sway is present at four compared to 12 weeks post-TKA. This augmented rapid sway may provide increased challenges to the postural control system at a time coinciding with reduced strength levels, which could have implications for physical function during activities of daily living.

Feature Extraction of Wrist Pulse Signals using Gabor Spectrogram

Background/Objectives: The practice of Ayurveda has been long followed in India which is based on the analysis of wrist pulse signal for diagnosing human health. The pulse signal is a non-stationary signal. A signal can be analyzed in either time domain, frequency domain or joint time-frequency domain. This paper highlights the need of joint time-frequency analysis for a non-stationary signal and provides an approach of analyzing wrist pulse signals in time-frequency domain using Gabor Spectrogram. Methods/Statistical Analysis: The work in this paper has been done using Virtual Instruments (VI’s) in ®LabVIEW. In this paper, band pass filter and wavelet de-noising technique has been used for pre-processing of raw pulse signals. Segmentation and Normalization has been performed on the noise free pulse signals. For representing the pulse signals in t-f space, Gabor Spectrogram has been used. The Gabor Spectrogram is a time-frequency distribution technique that offers good time-frequency resolution and negligible cross term interference. The performance has been analyzed using a parameter Mean Square Error (MSE). Findings: Various features: Mean Instantaneous Frequency (MIF), Mean Instantaneous Bandwidth (MIB), Frequency Marginal Integral (FMI), Time Marginal Integral (TMI) and Group Delay (GD) have been extracted in t-f domain for pulse signals from healthy subjects and correlation has been performed. The extracted features for different healthy subjects show similarity in variation pattern even though the actual signals differ in time domain, illustrated through correlation, which marks a successful attempt towards the significance of time-frequency distribution for pulse signals. Application/Improvement: These features can prove very significant in health diagnosis of human beings.

Surface electromyography based muscle fatigue progression analysis using modified B distribution time–frequency features

Abstract In this work, an attempt has been made to analyze the progression of muscle fatigue using surface electromyography (sEMG) signals and modified B distribution (MBD) based time–frequency analysis. For this purpose, signals are recorded from biceps brachii muscles of fifty healthy adult volunteers during dynamic contractions. The recorded signals are preprocessed and then subjected to MBD based time–frequency distribution (TFD). The instantaneous median frequency (IMDF) is extracted from the time–frequency matrix for different values of kernel parameter. The linear regression technique is used to model the temporal variations of IMDF. Correlation coefficient is computed in order to select the appropriate value for kernel parameter of MBD based TFD. Further, extended version of frequency domain features namely instantaneous spectral ratio (InstSPR) at low frequency band (LFB), medium frequency band (MFB) and high frequency band (HFB) are extracted from the time–frequency spectrum. In addition to these features, IMDF and instantaneous mean frequency (IMNF) are also calculated. The least square error based linear regression technique is used to track the slope variations of these features. The results show that MBD based time–frequency spectrum is able to provide the instantaneous variations of frequency components associated with fatiguing contractions. The values of InstSPR at MFB and HFB regions, IMDF and IMNF show a decreasing trend during the progression of muscle fatigue. However, an increasing trend is observed in LFB regions. Further the coefficient of variation is calculated for all the features. It is found that the values of IMDF, IMNF and InstSPR in LFB region have lowest variability across different subjects in comparison with other two features. It appears that this method could be useful in analyzing various neuromuscular activities in normal and abnormal conditions.

Electromyographic adjustments during continuous and intermittent incremental fatiguing cycling.

We studied the sensitivity of electromyographic (EMG) variables to load and muscle fatigue during continuous and intermittent incremental cycling. Fifteen men attended three laboratory sessions. Visit 1: lactate threshold, peak power output, and VO2max . Visits 2 and 3: Continuous (more fatiguing) and intermittent (less fatiguing) incremental cycling protocols [20%, 40%, 60%, 80% and 100% of peak power output (PPO)]. During both protocols, multichannel EMG signals were recorded from vastus lateralis: muscle fiber conduction velocity (MFCV), instantaneous mean frequency (iMNF), and absolute and normalized root mean square (RMS) were analyzed. MFCV differed between protocols (P < 0.001), and only increased consistently with power output during intermittent cycling. RMS parameters were similar between protocols, and increased linearly with power output. However, only normalized RMS was higher during the more fatiguing 100% PPO stage of the continuous protocol [continuous-intermittent mean difference (95% CI): 45.1 (8.5% to 81.7%)]. On the contrary, iMNF was insensitive to load changes and muscle fatigue (P = 0.14). Despite similar power outputs, continuous and intermittent cycling influenced MFCV and normalized RMS differently. Only normalized RMS was sensitive to both increases in power output (in both protocols) and muscle fatigue, and thus is the most suitable EMG parameter to monitor changes in muscle activation during cycling.

Suppressive Effects of Resveratrol Treatment on The Intrinsic Evoked Excitability of CA1 Pyramidal Neurons.

Resveratrol, a phytoalexin, has a wide range of desirable biological actions. Despite a growing body of evidence indicating that resveratrol induces changes in neu- ronal function, little effort, if any, has been made to investigate the cellular effect of res- veratrol treatment on intrinsic neuronal properties. This experimental study was performed to examine the acute effects of resveratrol (100 µM) on the intrinsic evoked responses of rat Cornu Ammonis (CA1) pyramidal neurons in brain slices, using whole cell patch clamp re- cording under current clamp conditions. Findings showed that resveratrol treatment caused dramatic changes in evoked responses of pyramidal neurons. Its treatment induced a significant (P<0.05) increase in the after hyperpolarization amplitude of the first evoked action potential. Resveratrol-treated cells displayed a significantly broader action potential (AP) when compared with either control or vehicle-treated groups. In addition, the mean instantaneous firing frequency between the first two action potentials was significantly lower in resveratrol-treated neurons. It also caused a significant reduction in the time to maximum decay of AP. The rheobase current and the utilization time were both significantly greater following resveratrol treatment. Neurons exhibited a significantly depolarized voltage threshold when exposed to resveratrol. Results provide direct electrophysiological evidence for the inhibitory effects of resveratrol on pyramidal neurons, at least in part, by reducing the evoked neural activity.

An improved ensemble empirical mode decomposition and Hilbert transform for fatigue evaluation of dynamic EMG signal

A hybrid dynamic fatigue diagnosis method based on a variation of ensemble empirical mode decomposition (VEEMD) and mean instantaneous frequency (MIF) is presented. This new approach consists of sifting an ensemble of white noise-added signal (data) and treats the mean as the final true result. In the method here proposed, a particular noise is added at each stage of the decomposition and a unique residue is computed to obtain each mode. Our results showed that MIF estimated from each instantaneous frequency of intrinsic mode functions (IMFs) decomposed by the proposed VEEMD is a relevant feature to muscular fatigue diagnosis. We found that MIF reduces when the force level of the muscle contraction increases.

In-cylinder pressure-based direct techniques and time frequency analysis for combustion diagnostics in IC engines

In-cylinder pressure measurement and analysis has historically been a key tool for off-line combustion diagnosis in internal combustion engines, but online applications for real-time condition monitoring and combustion management have recently become popular. The present investigation presents and compares different low computing-cost in-cylinder pressure based methods for the analyses of the main features of combustion, that is, the start of combustion, the end of combustion and the crankshaft angle that responds to half of the overall burned mass. The instantaneous pressure in the combustion chamber has been used as an input datum for the described analytical procedures and it has been measured by means of a standard piezoelectric transducer.Traditional pressure-based techniques have been shown to be able to predict the burned mass fraction time history more accurately in spark ignition engines than in diesel engines. The most suitable pressure-based techniques for both spark ignition and compression ignition engines have been chosen on the basis of the available experimental data. Time–frequency analysis has also been applied to the analysis of diesel combustion, which is richer in events than spark ignited combustion. Time frequency algorithms for the calculation of the mean instantaneous frequency are computationally efficient, allow the main events of the diesel combustion to be identified and provide the greatest benefits in the presence of multiple injection events. These algorithms can be optimized and applied to onboard diagnostics tools designed for real control, but can also be used as an advanced validation tool for refined combustion models.The presented results on the pressure-based techniques, including a time frequency analysis, have been compared with the numerical outcomes from previously developed two- and three-zone thermodynamic combustion models.

ANALYSIS OF SURFACE EMG SIGNALS UNDER FATIGUE AND NON-FATIGUE CONDITIONS USING B-DISTRIBUTION BASED QUADRATIC TIME FREQUENCY DISTRIBUTION

In this paper, an attempt has been made to analyze surface electromyography (sEMG) signals under non-fatigue and fatigue conditions using time-frequency based features. The sEMG signals are recorded from biceps brachii muscle of 50 healthy volunteers under well-defined protocol. The pre-processed signals are divided into six equal epochs. The first and last segments are considered as non-fatigue and fatigue zones respectively. Further, these signals are subjected to B-distribution based quadratic time-frequency distribution (TFD). Time frequency based features such as instantaneous median frequency (IMDF) and instantaneous mean frequency (IMNF) are extracted. The expression of spectral entropy is modified to obtain instantaneous spectral entropy (ISPEn) from the time-frequency spectrum. The results show that all the extracted features are distinct in both conditions. It is also observed that the values of all features are higher in non-fatigue zone compared to fatigue condition. It appears that this method is useful in analysing various neuromuscular conditions using sEMG signals.

Neural responses to the mechanical characteristics of high velocity, low amplitude spinal manipulation: Effect of specific contact site

BackgroundSystematic investigations are needed identifying how variability in the biomechanical characteristics of spinal manipulation affects physiological responses. Such knowledge may inform future clinical practice and research study design. ObjectiveTo determine how contact site for high velocity, low amplitude spinal manipulation (HVLA-SM) affects sensory input to the central nervous system. DesignHVLA-SM was applied to 4 specific anatomic locations using a no-HVLA-SM control at each location randomized in an 8×8 Latin square design in an animal model. MethodsNeural activity from muscle spindles in the multifidus and longissimus muscles were recorded from L6 dorsal rootlets in 16 anesthetized cats. A posterior to anterior HVLA-SM was applied through the intact skin overlying the L6 spinous process, lamina, inferior articular process and L7 spinous process. HVLA-SMs were preceded and followed by simulated spinal movement applied to the L6 vertebra. Change in mean instantaneous discharge frequency (ΔMIF) was determined during the thrust and the simulated spinal movement. ResultsAll contact sites increased L6 muscle spindle discharge during the thrust. Contact at all L6 sites significantly increased spindle discharge more than at the L7 site when recording at L6. There were no differences between L6 contact sites. For simulated movement, the L6 contact sites but not the L7 contact site significantly decreased L6 spindle responses to a change in vertebral position but not to movement to that position. ConclusionsThis animal study showed that contact site for an HVLA-SM can have a significant effect on the magnitude of sensory input arising from muscle spindles in the back.