Quantitative analysis of the electroencephalogram during cranial electrotherapy stimulation.

OBJECTIVE: Normal individuals were used to quantitate electroencephalographic (EEG) changes during concurrent administration of 0.5 and 100 Hz cranial electrotherapy stimulation (CES). METHODS: Twelve normal, right-handed males were used in a randomized, double-blind crossover design study. A 3 amplifier system incorporating noise-cancellation was used to collect one channel of EEG (O1-Cz configuration) for 30 min. Either 0.5, 100 Hz, or sham CES treatment was administered for 20 min of each session. Statistical analyses were applied to time- and frequency-domain EEG variables. RESULTS: Relative to sham control, 0.5 and 100 Hz CES caused the alpha band mean frequency to shift downward. Additionally, 100 Hz CES also caused a decrease of the alpha band median frequency and beta band power fraction. CONCLUSIONS: Both 0.5 and 100 Hz CES provide frequency distribution shifts that suggest beneficial changes in mental state. However, compared to 0.5 Hz CES, 100 Hz CES effected a greater overall change. It is suggested that similar tests be performed on individuals with various behavioral and neurological disorders to determine if comparable EEG changes can be realized and correlated with beneficial effects of CES therapy.

An alpha modulation index for electroencephalographic studies using complex demodulation.

An automated technique for measuring the relative amount of amplitude modulation of electroencephalographic (EEG) alpha activity is developed to increase the number of existing tools for differentiating the various types of alpha activity. EEG data collected from 12 normal males is used to characterize alpha modulation frequency characteristics. From these findings, a complex demodulation method is constructed to extract the amplitude modulation envelope of alpha activity from an epoch of EEG data while disregarding both continuous amplitude alpha activity and activity outside the alpha band. A threshold technique is then used to determine the relative amount of modulation contained within the data epoch. This metric is termed the alpha modulation index (AMI). Good correlation (R2 = 0.86) is found when automated scoring results are compared with manual scoring of physiologic EEG alpha modulation. The flexibility of this technique makes it easily adaptable to other EEG frequency bands and applications.

Muscle activity in rapid multi-degree-of-freedom elbow movements: solutions from a musculoskeletal model.

The activity of certain muscles that cross the elbow joint complex (EJC) are affected by forearm position and forearm movement during elbow flexion/extension. To investigate whether these changes are based on the musculoskeletal geometry of the joint, a three-dimensional musculotendinoskeletal computer model of the EJC was used to estimate individual muscle activity in multi-degree-of-freedom (df) rapid (ballistic) elbow movements. It is hypothesized that this model could reproduce the major features of elbow muscle activity during multi-df elbow movements using dynamic optimal control theory, given a minimum-time performance criterion. Results from the model are presented and verified with experimental kinematic and electromyographic data from movements that involved both one-df elbow flexion/extension and two-df flexion/extension with forearm pronation/supination. The model demonstrated how the activity of particular muscles is affected by both forearm position and movement, as measured in these experiments and as previously reported by others. These changes were most evident in the flexor muscles and least evident in the extensor muscles. The model also indicated that, for specific one- and two-df movements, activating a muscle that is antagonistic or noncontributory to the movement could reduce the movement time. The major features of muscle activity in multi-df elbow movements appear to be highly dependent on the joint's musculoskeletal geometry and are not strictly based on neural influences or neuroanatomical substrates.

Enhanced period-peak analysis of electro-encephalograms using a fast sinc function.

In an effort to reduce the memory space and processing time required by fast Fourier transforms, enhanced period-peak detection is investigated. The method is based on a combination of Fourier transforms and period-peak detection. The signal is considered as a train of truncated sinusoidal functions. Each truncated sinusoidal function is limited by two successive local extrema. The Fourier transform of the truncated sinusoidal function is a sinc function. The summation of these sinc functions yields an approximate frequency spectrum of the signal.

Potential and current density distributions of cranial electrotherapy stimulation (CES) in a four-concentric-spheres model.

Cranial electrotherapy stimulation (CES) has been successfully used for treatment of many psychiatric diseases. Its noninvasive nature is its major advantage over other forms of treatments such as drugs. It is postulated that the low electric current of CES causes the release of neurotransmitters. However, the current pathways have not been extensively investigated. In the following paper, analytical and numerical methods are used to determine the distribution of potential and current density in a four zone concentric spheres model of the human head when excited by two electrodes diametrically opposite to each other. Because of the azimuthal symmetry, which is assumed in this study, a two-dimensional (2-D) finite difference approximation is derived in the spherical grid. The current density distribution is projected around the center of the model, where the thalamus is modeled as a concentric sphere. All dimensions and electrical properties of the model are adapted from clinical data. Results of this simulation indicate that, in contrast to previous beliefs, a small fraction of the CES current does reaches the thalamic area and may facilitate the release of neurotransmitters.

Development and evaluation of a musculoskeletal model of the elbow joint complex.

This paper describes the development and evaluation of a musculoskeletal model that represents human elbow flexion-extension and forearm pronation-supination. The length, velocity, and moment arm for each of the eight musculotendon actuators were based on skeletal anatomy and joint position. Musculotendon parameters were determined for each actuator and verified by comparing analytical moment-angle curves with experimental joint torque data. The parameters and skeletal geometry were also utilized in the musculoskeletal model for the analysis of ballistic (rapid-directed) elbow joint complex movements. The key objective was to develop a computational model, guided by parameterized optimal control, to investigate the relationship among patterns of muscle excitation, individual muscle forces, and to determine the effects of forearm and elbow position on the recruitment of individual muscles during a variety of ballistic movements. The model was partially verified using experimental kinematic, torque, and electromyographic data from volunteer subjects performing both isometric and ballistic elbow joint complex movements. This verification lends credibility to the time-varying muscle force predictions and the recruitment of muscles that contribute to both elbow flexion-extension and forearm pronation-supination.

Adaptive digital notch filter design on the unit circle for the removal of powerline noise from biomedical signals.

This paper investigates adaptive digital notch filters for the elimination of powerline noise from biomedical signals. Since the distribution of the frequency variation of the powerline noise may or may not be centered at 60 Hz, three different adaptive digital notch filters are considered. For the first case, an adaptive FIR second-order digital notch filter is designed to track the center frequency variation. For the second case, the zeroes of an adaptive IIR second-order digital notch filter are fixed on the unit circle and the poles are adapted to find an optimum bandwidth to eliminate the noise to a pre-defined attenuation level. In the third case, both the poles and zeroes of the adaptive IIR second-order filter are adapted to track the center frequency variation within an optimum bandwidth. The adaptive process is considerably simplified by designing the notch filters by pole-zero placement on the unit circle using some suggested rules. A constrained least mean-squared (CLMS) algorithm is used for the adaptive process. To evaluate their performance, the three adaptive notch filters are applied to a powerline noise sample and to a noisy EEG as an illustration of a biomedical signal.

Enhanced period-peak analysis of the electroencephalogram using a fast Sinc function.

EEG computer analysis is still not widely used in the clinic, and the need for advanced signal processing techniques is still warranted. The fast Fourier transform (FFT) is the method most frequently used for power spectrum estimation of the EEG. In an effort to reduce memory space and processing time required by the fast Fourier transform (FFT), a new method, the enhanced period-peak detection (EPPD), is investigated. The method is based on a combination of the Fourier transform (FT) and period-peak detection. The signal is considered as a train of truncated sinusoidal functions. Each truncated sinusoidal function is limited by two successive local extrema (a peak and a valley). The Fourier transform of the truncated sinusoidal function is the well known Sinc function. The summation of these Sinc functions yields an approximate frequency spectrum of the signal. The speed and performance of the FFT rely upon the number of data collected and the sampling frequency. On the other hand, the enhanced period-peak detection (EPPD) method does not require that the entire EEG data be stored. Only the extrema of the signal and time between the peaks are needed. Furthermore, the frequency resolution of the EPPD is independent of the number of data available and of the sampling frequency.

Comparison of experimental and analytical torque-angle relationships of the human elbow joint complex.

The human elbow joint complex (EJC) is an intricate joint that is currently being modeled with eight musculotendon actuators for the analysis of flexion-extension and pronation-supination movements. The musculotendon length (LMT), musculotendon velocity (VMT), and muscular moment arm (MA) for each actuator have been investigated based on joint anatomy and joint angle position. Musculotendon parameters necessary for the muscle model have been collected from various sources. These parameters, along with the musculoskeletal geometry, are used in a static muscle model to compute the force and joint torque generated by each muscle. The results are plotted as torque-angle curves and compared with experimental joint torque data.

Comparison of experimental and predicted muscle activation patterns in ballistic elbow joint movements.

The human elbow joint complex (EJC) is an intricate joint which produces combinations of movements that are unique within the human body and that are involved in performing many important tasks. This paper discusses an on-going study to predict muscle force patterns in elbow flexion-extension. Four musculotendon actuators are included in this preliminary musculoskeletal model for the analysis of ballistic elbow flexion-extension movements. The key objective is to develop a computational model, guided by optimal control, to investigate the relationship among patterns of muscle excitation, individual muscle forces, and movement kinematics. Model verification is attempted using experimental data from volunteer subjects performing a ballistic elbow flexion movement.

Frequency-domain digital filtering techniques for the removal of powerline noise with application to the electrocardiogram.

This paper presents two new local processing frequency-domain methods for the removal of powerline noise from electrophysiological signals. The first is based on an iterative division or a multiplication of a set of frequencies centered at 60 Hz. The second users a basic property of the natural logarithm to smooth the 60-Hz noise. Both methods are intended to reduce powerline noise without affecting the frequency spectrum of the signal in the regions surrounding 60 Hz. For illustration, these local processing methods are applied to artificial and real electrocardiographic (ECG) data and are compared to a fixed IIR notch digital filter which is designed by pole-zero placements on the unit circle. The performance of each method is measured by the error squared, which is the square of the difference between the original noise-free signal and the filtered noisy ECG. Finally, since the two methods are iterative processes, comparison of their rate of convergence to a predefined noise reduction level is considered.

Alterations in the pulsatile mode of growth hormone release in men and women with insulin-dependent diabetes mellitus.

The mechanisms responsible for the elevated levels of circulating GH observed in diabetes mellitus (DM) remain incompletely defined. To assess the episodic fluctuations in serum GH as a reflection of hypothalamic-pituitary activity, we accumulated GH concentration-time series in a total of 48 adult men and women with and without insulin-dependent DM by obtaining serum samples at 10-min intervals over 24 h. Significant pulses of GH release were subsequently identified and characterized by an objective, statistically based pulse detection algorithm (Cluster) and fixed circadian (24-h) periodicities of secretory activity, resolved using Fourier expansion time-series analysis. Compared to those in age-matched controls, integrated 24-h concentrations of GH were 2- to 3.5-fold higher in diabetic men (P = 0.002) and women (P = 0.0005). Both men and women with DM had over 50% more GH pulses per 24 h than their non-DM counterparts. In addition, maximal GH pulse amplitude was markedly elevated in the men and women with DM (P = 0.0019 and 0.0189, respectively). That the increase in maximal pulse amplitude was accounted for by greater baseline levels was documented by a higher interpulse valley mean GH concentration in the diabetics compared to the controls (P = 0.0437 and 0.0056, men and women, respectively) and the absence of any difference in incremental pulse amplitude for either sex (P greater than 0.05). DM men had larger GH pulse areas (P = 0.039) than control men, apparently accounted for by greater pulse width (P = 0.0037). Pulse areas in DM and non-DM women were indistinguishable. Time-series analysis revealed that the 24-h (circadian) rhythms of serum GH concentrations exhibited significantly increased amplitudes in the diabetic group as a whole (compared to the controls, P = 0.011). However, the times of maximal GH concentrations (acrophases) were not significantly different. As a group, serum insulin-like growth factor-I was lower in DM vs. non-DM individuals (P = 0.0014), although when separated by sex this difference did not reach statistical significance in women (P = 0.317). The present data confirm the higher circulating levels of GH previously reported to occur in individuals with poorly controlled DM. The altered frequency of GH pulses together with enhanced interpulse GH concentrations and an amplified circadian GH rhythm are compatible with hypothalamic dysfunction associated with dysregulation of somatostatin and/or GHRH secretion.(ABSTRACT TRUNCATED AT 400 WORDS)

Multichannel real-time analysis of the clinical EEG on a dual microprocessor system.

A dual microprocessor system has been developed as an aid to conventional visual analysis of the EEG. Up to eight channels of EEG gathered from any standard EEG strip-chart machine can be processed in real time. The analysis is performed on a dual microprocessor "pipe-line" configuration that is built using Motorola 68000 (16-bit) and 6809 (8-bit) microprocessors. The system is basically software oriented in order to offer processing flexibility. The 16-bit processor is dedicated to the critical task of signal analysis based on a newly developed period-peak algorithm. The 8-bit processor is dedicated to the pre- and post-processing tasks, including statistical generations and display control. Analysis results for each channel are displayed on a video terminal in several convenient graphical formats.

Period-peak analysis of the EEG with microprocessor applications.

This paper describes the development and evaluation of a period-peak algorithm for background analysis of the clinical electroencephalogram (EEG). The procedure is a time-domain method which is harmonious with manual interpretation of the EEG tracing. Conceptually the algorithm functions in 2 modes. Major counts are detected by successive baseline crossings in the period analysis mode. Presence of superimposed activity between major-counts induces a transition to the peak-detection mode. In this manner, period-peak analysis is capable of detecting the simultaneity of slow base-waves and relatively fast superimposed activity in the EEG. Preliminary studies have been conducted in which the analysis results of this procedure were compared to those of other EEG algorithms. In general, the period-peak algorithm offered less bias towards either end of the EEG spectrum. Subsequent to testing of a FORTRAN version, the period-peak algorithm has been implemented in assembly language on a dedicated microprocessor system for on-line analysis of EEG data.

Characterization of adenylate cyclase activity in bovine and human corneal epithelium.

The properties of adenylate cyclase from bovine and human corneal epithelium were investigated. Adrenergic drugs were the most effective stimulatory agents tested in bovine tissue, causing greater activation than did fluoride. Isoproterenol was the most potent agonist, followed by epinephrine and norepinephrine. Phenylephrine and dopamine also stimulated adenylate cyclase through beta-adrenergic receptors at relatively high concentrations. Enzyme stimulation by all the adrenergic drugs tested was completely inhibited by 1 microM propranolol or 0.1 microM timolol. The GTP analogue, GppNp, produced considerable activation and caused an augmented response when combined with isoproterenol, but not with fluoride. Prostaglandins E1, E2, or F2 alpha produced a small but significant stimulation over control which was not sensitive to propranolol inhibition. Adenylate cyclase from human corneal epithelium exhibited qualitatively similar characteristics to those of the bovine enzyme. Fluoride was the most effective stimulatory agent, followed by isoproterenol, phenylephrine, and dopamine. Prostaglandins failed to stimulate adenylate cyclase activity in human corneal epithelial preparations.

Peak-detection algorithm for EEG analysis.

A peak-detection method is described for computer analysis of the the electroencephalogramme (EEG). The technique consists of measuring the amplitude and time interval between successive maxima (peaks) and minima (troughs) in the signal. A critical feature of the peak-detection algorithm is the inclusion of an amplitude threshold criterion which eliminates the registration of low-voltage activity riding on EEG waves. The peak-detection procedure permits the formulation of a variety of intra-band and inter-band EEG statistics which can be useful in on-line computer applications. The peak-detection algorithm has been successfully applied to a number of normal and clinical EEG recordings. Although no computer procedure for EEG analysis has yet been universally adopted, the peak-detection algorithm reported in this paper presents a standardised approach which can be used between EEG clinics.