Soft sensors for a sensing-actuation system with high bladder voiding efficiency.

Sensing-actuation systems can assist a bladder with lost sensation and weak muscle control. Here, we advance the relevant technology by integrating a soft and thin capacitive sensor with a shape memory alloy-based actuator to achieve a high-performance closed-loop configuration. In our design, sensors capable of continuous bladder volume detection and actuators with strong emptying force have been used. This integration has previously hindered performance due to large bladder volume changes. Our solution integrates sensing-actuation elements that are bladder compatible but do not interfere with one another, achieving real-time bladder management. The system attains a highly desirable voiding target of 71 to 100% of a rat's bladder with a volume sensitivity of 0.7 µF/liter. Our system represents an efficient voiding solution that avoids overfilling and represents a technological solution to bladder impairment treatment, serving as a model for similar soft sensor-actuator integration with other organs.

Monitoring of global cerebral ischemia using wavelet entropy rate of change.

In this paper, the subband wavelet entropy (SWE) and its time difference are proposed as two quantitative measures for analyzing and segmenting the electroencephalographic (EEG) signals. SWE for EEG subbands, namely Delta, Theta, Alpha, Beta, and Gamma, is calculated and segmented using wavelet analysis. In addition, a time difference entropy measure was calculated because it does not require a baseline and equals to zero in all clinical bands as the initial condition. Visual and quantitative results were obtained from 11 rodents that were subjected to 3, 5, and 7 min of global ischemic brain injury by asphyxic cardiac arrest. We found that the time difference of SWE is capable of amplifying the variations between clinical bands during the various stages of the recovery process and may serve as a novel analytical approach to grade and classify brain rhythms during global ischemic brain injury and recovery.

Vulnerability of the thalamic somatosensory pathway after prolonged global hypoxic-ischemic injury.

The aim of this study was to test the hypothesis that under prolonged global ischemic injury, the somatosensory thalamus and the cortex would manifest differential susceptibility leading to varying degrees of thalamo-cortical dissociation. The thalamic electrical responses displayed increasing suppression with longer durations of ischemia leading to a significant thalamo-cortical electrical dissociation. The data also point to a selective vulnerability of the network oscillations involving the thalamic relay and reticular thalamic neurons. An adult rat model of asphyxial cardiac arrest involving three cohorts with 3 min (G1, n=5), 5 min (G2, n=5) and 7 min (G3, n=5) of asphyxia respectively was used. The cortical evoked response, as quantified by the peak amplitude at 20 ms in the cortical evoked potential, recovers to more than 60% of baseline in all the cases. The multi-unit responses to the somatosensory stimuli recorded from the thalamic ventral posterior lateral (VPL) nuclei consists typically of three components: (1). the ON response (<30 ms after stimulus), (2). the OFF response (period of inhibition, from 30 ms to 100 ms after stimulus) and (3). rhythmic spindles (beyond 100 ms after stimulus). Asphyxia has a significant effect on the VPL ON response at 30 min (P<0.025), 60 min (P<0.05) and 90 min (P<0.05) after asphyxia. Only animals in G3 show a significant suppression (P<0.05) of the VPL ON response when compared to the sham group at 30 min, 60 min and 90 min after asphyxia. There was no significant reduction in somatosensory cortical N20 (negative peak in the cortical response at 20 ms after stimulus) amplitude in any of the three groups with asphyxia indicating a thalamo-cortical dissociation in G3. Further, rhythmic spindle oscillations in the thalamic VPL nuclei that normally accompany the ON response recover either slowly after the recovery of ON response (in the case of G1 and G2) or do not recover at all (in the case of G3).We conclude that there is strong evidence for selective vulnerability of thalamic relay neurons and its network interactions with the inhibitory interneurons in the somatosensory pathway leading to a thalamo-cortical dissociation after prolonged durations of global ischemia.

Effect of varying pacing waveform shapes on propagation and hemodynamics in the rabbit heart.

The propagation characteristics of myocardium stimulated with anodal, cathodal, and equiphasic biphasic pacing pulses were examined in Langendorff-perfused rabbit hearts. Conduction velocity measurements were made using an array of bipolar extracellular electrodes, transmembrane potentials recorded using floating intracellular microelectrodes, and hemodynamics measured by fluid-filled catheter transducer systems. Anodal (A) stimulation pulses improved the electrical conduction at all the stimulus amplitudes tested in both longitudinal (e.g., 5 V 2-msec pulse: [A] 54.9 +/- 0.7 cm/sec; cathodal [C] 49.7 +/- 1.5 cm/sec) and transverse (e.g., 5 V 2 msec pulse: [A] 31.3 +/- 1.7 cm/sec; [C] 23.3 +/- 2.9 cm/sec) directions. Microelectrode recordings verified that increased conduction velocities of the anodal pulses were associated with faster upstrokes of the action potentials. The increased threshold associated with anodal pulses may be overcome by using a biphasic (B) waveform, in effect adding a second phase (e.g., 2-msec pulse: [A] 2.03 +/- 1.3 V; [C] 3.85 +/- 1.5 V; [B] 2.15 +/- 0.9 V). The conduction speeds achieved by the biphasic pulses were found to be comparable to the equivalent anodal pulses (e.g., 5 V 2-msec pulse: [B] 55.2 +/- 1.7 cm/sec longitudinal and 32.4 +/- 2.1 cm/sec transverse). It is postulated that the enhanced conduction by anodal and biphasic pulses may be due to preconditioning of the myocardium before stimulation, resulting in more vigorous action potential upstrokes. In preliminary experiments, it was observed that improved conduction elicited by these pulses also resulted in enhanced contractility as measured by shortened electromechanical delays and faster rate of rise of pressure development (dP/dtmax: [A] 25.4 +/- 0.4 mm Hg/sec; [C] 19.4 +/- 0.8 mm Hg/sec; [B] 25.7 +/- 1.2 mm Hg/sec, respectively). Use of novel hybrid pulses involving an anodal component may offer a way for implanted pacemakers to enhance the electro-mechanical response of the heart.

Effects of anodal vs. cathodal pacing on the mechanical performance of the isolated rabbit heart.

Previous studies have suggested that anodal pacing enhances electrical conduction in the heart near the pacing site. It was hypothesized that enhanced conduction by anodal pacing would also enhance ventricular pressure in the heart. Left ventricular pressure measurements were made in isolated, Langendorff-perfused rabbit hearts by means of a Millar pressure transducer with the use of a balloon catheter fixed in the left ventricle. The pressure wave was analyzed for maximum pressure (Pmax) generated in the left ventricle and the work done by the left ventricle (Parea). Eight hearts were paced with monophasic square-wave pulses of varying amplitudes (2, 4, 6, and 8 V) with 100 pulses of each waveform delivered to the epicardium. Anodal stimulation pulses showed statistically significant improvement in mechanical response at 2, 4, and 8 V. Relative to unipolar cathodal pacing, unipolar anodal pacing improved Pmax by 4.4 +/- 2.3 (SD), 5.3 +/- 3.1, 3.5 +/- 4.9, and 4.8 +/- 1.9% at 2, 4, 6, and 8 V, respectively. Unipolar anodal stimulation also improved Parea by 9.0 +/- 3.0, 12.0 +/- 6.0, 10.1 +/- 7.7, and 11.9 +/- 6.0% at 2, 4, 6, and 8 V, respectively. Improvements in Pmax and Parea indicate that an anodally paced heart has a stronger mechanical response than does a cathodally paced heart. Anodal pacing might be useful as a novel therapeutic technology to treat mechanically impaired or failed hearts.

Spectral analysis methods for neurological signals.

This paper reviews some novel spectral analysis techniques that are useful for neurological signals in general and EEG signals in particular. First, some drawbacks and limitations of the commonly used Fast Fourier transforms (FFTs) are presented, and then alternative algorithms are outlined. An auto-regressive (AR) modeling based spectral estimation procedure is presented to overcome the problems of lower resolution and 'leakage' effects inherent in the FFT algorithm. For signals which are transient in nature or rapidly time-varying, two alternative algorithms are presented. The first is an adaptive AR parameter estimation algorithm and the second is a wavelet based time-frequency representation algorithm. Finally, a Spectral Distance measure and the Itakura distance measure are presented to quantify the differences between the spectra of two signals in a succinct manner. The application and performance of all the algorithms is illustrated using electroencephalograms (EEGs) recorded in animals during hypoxic asphyxic injury to brain.

Adaptive Fourier modeling for quantification of tremor.

A new computational method for quantification of tremor, the weighted frequency Fourier linear combiner (WFLC), is presented. This technique rapidly determines the frequency and amplitude of tremor by adjusting its filter weights according to a gradient search method. It provides continual tracking of frequency and amplitude modulations over the course of a test. By quantifying time-varying characteristics, the WFLC assists in correctly interpreting the results of spectral analysis, particularly for recordings exhibiting multiple spectral peaks. It therefore supplements spectral analysis, providing a more accurate picture of tremor than spectral analysis alone. The method has been incorporated into a desktop tremor measurement system to provide clinically useful analysis of tremor recorded during handwriting and drawing using a digitizing tablet. Simulated data clearly demonstrate tracking of variations in frequency and amplitude. Clinical recordings then show specific examples of quantification of time-varying aspects of tremor.

Optical light scatter imaging of cellular and sub-cellular morphology changes in stressed rat hippocampal slices.

Optical imaging, such as transmission imaging, is used to study brain tissue injury. Transmission imaging detects cellular swelling via an increase in light transmitted by tissue slices due to a decrease in scattering particle concentration. Transmission imaging cannot distinguish sub-cellular particle size changes from cellular swelling or shrinkage. We present an optical imaging method, based on Mie scatter theory, to detect changes in sub-cellular particle size and concentration. The system uses a modified inverted microscope and a 16-bit cooled CCD camera to image tissue light scatter at two angles. Dual-angle scatter ratio imaging successfully discriminated latex microsphere suspensions of differing sizes (0.6, 0.8, 1 and 2 microm) and concentrations. We applied scatter imaging to hippocampal slices treated with 100 microM N-methyl-D-aspartate (NMDA) to model excitotoxic injury or -40 mOsm hypotonic perfusion solution to cause edema injury. We detected light scatter decreases similar to transmission imaging in the CA1 region of the hippocampus for both treatments. Using our system, we could distinguish between NMDA and hypotonic treatments on the basis of statistically significant (P<0.0003) differences in the scatter ratio measured in CA1. Scatter imaging should be useful in studying tissue injuries or activity resulting in brain tissue swelling as well as morphological changes in sub-cellular organelles such as mitochondrial swelling.

In vivo nitric oxide sensor using non-conducting polymer-modified carbon fiber.

Nitric oxide (NO) is emerging as a very important and ubiquitous gaseous messenger in the body. The response characteristics of NO sensors made of non-conducting polymer modified carbon fiber electrodes are investigated to determine their selectivity, sensitivity, and stability for in vivo use. A composite polymer, comprising Nafion, m-phenylenediamine, and resorcinol, showed the best selectivity and stability to amperometric NO detection. The non-conducting, self-limiting polymer film protects the electrode from interference and fouling by other biochemicals. Although the relative sensitivity to NO of the modified sensor is lower than that of the unmodified carbon fiber electrodes (less than 6%), the composite polymer electrode showed high selectivity against ascorbic acid (> 2000:1), nitrite (> 600:1), and dopamine (> 200:1). The stability of the NO sensor was maintained for at least 1 week. The NO sensitivity after in vivo experiments (n = 8) is 88.1 +/- 5.6% of initial sensitivity data obtained before in vivo experiments. Preliminary in vivo experiments done with this electrode are shown to capture elevated NO levels in brain following an ischemic injury.

A novel quantitative EEG injury measure of global cerebral ischemia.

OBJECTIVE: To develop a novel quantitative EEG (qEEG) based analysis method, cepstral distance (CD) and compare it to spectral distance (SD) in detecting EEG changes related to global ischemia in rats. METHODS: Adult Wistar rats were subjected to asphyxic-cardiac arrest for sham, 1, 3, 5 and 7 min (n=5 per group). The EEG signal was processed and fitted into an autoregressive (AR) model. A pre-injury baseline EEG was compared to selected data segments during asphyxia and recovery. The dissimilarities in the EEG segments were measured using CD and SD. A segment measured was considered abnormal when it exceeded 30% of baseline and its duration was used as the index of injury. A comprehensive Neurodeficit Score (NDS) at 24 h was used to assess outcome and was correlated with CD and SD measures. RESULTS: A higher correlation was found with CD and asphyxia time (r=0.81, P<0.001) compared to SD and asphyxia time (r=0.69, P<0.001). Correlation with cardiac arrest time (MAP<10 mmHg) showed that CD was superior (r=0.71, P<0.001) to SD (r=0.52, P=0.002). CD obtained during global ischemia and 90 min into recovery correlated significantly with NDS at 24 h after injury (Spearman coefficient=-0.83, P<0.005), and was more robust than the traditional SD (Spearman coefficient=-0.63, P<0.005). CONCLUSION: The novel qEEG-based injury index from CD was superior to SD in quantifying early cerebral dysfunction after cardiac arrest and in providing neurological prognosis at 24 h after global ischemia in adult rats. Studying early qEEG changes after asphyxic-cardiac arrest may provide new insights into the injury and recovery process, and present opportunities for therapy.

Detection of non-linearity in the EEG of schizophrenic patients.

OBJECTIVE: The aim of this study is to detect non-linearity in the EEG of schizophrenia with a modified method of surrogate data. We also want to identify if dimension complexity (correlation dimension using spatial embedding) could be used as a discriminating statistic to demonstrate non-linearity in the EEG. The difference between the attractor dimension of healthy subjects and schizophrenic subjects is expected to be interpreted as reflecting some mechanisms underlying brain wave by views of non-linear dynamics analysis may reflect mechanistic differences. METHODS: EEGs were recorded with 14 electrodes in 18 healthy male subjects (average age: 26.3; range: 20--35) and 18 male schizophrenic patients (average age: 30.6; range: 24--40) during a resting eye-closed state. Neither of two groups was taking medicines. All artificial epochs in the EEG records were rejected by an experienced doctor's visual inspection. RESULTS: Testing non-linearity with modified surrogate data, we showed that correlation dimension of EEG data of schizophrenia does refuse the null hypothesis that the data were resulted from a linear dynamic system. A decrease of dimension complexity was found in the EEG of schizophrenia compared with controls. We interpreted it as the result of the psychopath's dysfunction overall brain. The surrogating procedure results in a significant increase in D(s). CONCLUSIONS: Non-linearity of the EEG in schizophrenia was proven in our study. We think the correlation dimension with spatial embedding as a good discriminating statistic for testing such non-linearity. Moreover, schizophrenic patients' EEGs were compared with controls and a lower dimension complexity was found. The results of our study indicate the possibility of using the methods of non-linear time series analysis to identify the EEGs of schizophrenic patients.

Somatosensory stimulus entrains spindle oscillations in the thalamic VPL nucleus in barbiturate anesthetized rats.

This study reports the effect of external stimuli on spindle oscillations in the somatosensory thalamus of barbiturate anesthetized rats. Multi-unit responses to somatosensory stimuli were measured from the contralateral thalamic ventral posterior lateral (VPL) nucleus at different stimulus strengths and periods. Spindle oscillations could be entrained by the somatosensory stimuli at periods between 2 and 5 s. A resonance phenomenon described as a quiescent pre-stimulus period followed by entrained post-stimulus oscillations, was observed for somatosensory stimuli above the threshold for eliciting cortical evoked potentials and a stimulus period between 2 and 5 s. This study demonstrates an ascending pathway for localized modulation of spindle oscillations.

Adaptive estimation of latency changes in evoked potentials.

Changes in latency of evoked potentials (EP) may indicate clinically and diagnostically important changes in the status of the nervous system. A low signal-to-noise ratio of the EP signal makes it difficult to estimate small, transient, time-varying changes in latency, or delays. Here, we present an adaptive algorithm that estimates small delay (latency change) values even when EP signal amplitudes are time-varying. When the delay is time invariant, the adaptive algorithm produces an unbiased estimate with delay estimation error less than half of the sampling interval. A lower estimation error variance is obtained when, in a pair of signals, the adaptive algorithm delays the signal with the higher SNR. The adaptive algorithm delays the signal with the higher SNR. The adaptive delay estimation algorithm was tested on intra-operative recordings of somatosensory EP, and analysis of those recordings reveals that the anesthetic etomidate produces a step change in the amplitude and latency of the EP signals.

Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection.

Several adaptive filter structures are proposed for noise cancellation and arrhythmia detection. The adaptive filter essentially minimizes the mean-squared error between a primary input, which is the noisy ECG, and a reference input, which is either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input. Different filter structures are presented to eliminate the diverse forms of noise: baseline wander, 60 Hz power line interference, muscle noise, and motion artifact. An adaptive recurrent filter structure is proposed for acquiring the impulse response of the normal QRS complex. The primary input of the filter is the ECG signal to be analyzed, while the reference input is an impulse train coincident with the QRS complexes. This method is applied to several arrhythmia detection problems: detection of P-waves, premature ventricular complexes, and recognition of conduction block, atrial fibrillation, and paced rhythm.

Adaptive Fourier estimation of time-varying evoked potentials.

An estimation procedure for dealing with time-varying evoked potentials is presented here. The evoked response is modeled as a dynamic Fourier series and the Fourier coefficients are estimated adaptively by the least mean square algorithm. Approximate expressions have been developed for the estimation error and time constant of adaptation. A procedure for optimizing the estimator performance is also presented. The effectiveness of the estimator in dealing with simulated as well as actual evoked responses is demonstrated.

Estimation of the ventricular fibrillation duration by autoregressive modeling.

An accurate estimation of ventricular fibrillation (VF) duration could be critical in selecting the most effective therapeutic intervention. We test the hypothesis that changes in frequency content of VF signals can be quantified by using autoregressive (AR) modeling, and the duration since the onset of VF can be estimated by using this method. VF signals were recorded for up to 300 s in five isolated rabbit hearts. Fourth-order AR parameters of successive segments were estimated, and frequencies of the first poles (the pole with lower frequency) were pooled together and a curve was fitted: F(t) = A exp (-alpha t) + B, where F(t) is the estimated frequency of the first pole at t'th time instant, alpha is the decay constant, B is the offset frequency, and A is the frequency at time zero minus the offset frequency. The utility of this curve in estimating the VF duration was tested in four new experiments, and the difference between the actual and the estimated VF duration (estimation error) was calculated. F(t), the frequency of the first pole, decreased from 12 to 6 Hz with duration of:VF, while the frequency of the other pole decreased from 25 to 20 Hz. Parameters of the fitted curve were calculated as A = 7.8, alpha = 0.0041 and B was selected as four. Testing on a new set of VF signals produced very little estimation error for the first 100 s of VF, although this error increased with VF duration. For these new signals, the mean value of the absolute estimation error was 26 s. Results of this study show that changes in the frequency content of electrocardiogram (ECG) during VF can be quantified by AR modeling and that the frequency changes associated with a pole of this model can be used to estimate the VF duration.

Multiway sequential hypothesis testing for tachyarrhythmia discrimination.

A multiway sequential hypothesis testing (M-SHT) algorithm is proposed for simultaneous discrimination of cardiac tachyarrhythmias--supraventricular tachycardia (SVT) and ventricular tachycardia (VT)--from normal sinus rhythm (NSR). The M-SHT algorithm calculates a likelihood function from atrio-ventricular delay measurements, and compares this function with thresholds derived from specified error probabilities for the arrhythmias to be discriminated. Performance of this algorithm was evaluated on dual channel endocardial electrograms recorded in the cardiac electrophysiology laboratory. Two databases were developed, one for development of the algorithm and another for evaluation. The M-SHT algorithm accurately classified 26 out of 28 NSR (2 misclassified as SVT), 31 out of 31 cases of SVT, and 41 out of 43 VT (2 misclassified as NSR). The average length of time taken for classification of the three rhythms was: 3.6 s for NSR, 5.0 s for SVT, and 1.6 s for VT. Unique features of this algorithm are that acceptable error rates for each arrhythmia are independently specified and accuracy can be traded off for a faster detection time, and vice versa.

Higher-order spectral analysis of burst patterns in EEG.

Burst suppression patterns in electroencephalograms (EEG's) have been observed in a variety of situations including recovery of a subject from a traumatic brain injury. They are associated with grave prognostic outcomes in neonates. We study power spectral parameters and bispectral parameters of the EEG at baseline, during early recovery from an asphyxic arrest (EEG burst patterns) and during late recovery after EEG evolves into a more continuous activity. The bicoherence indexes, which indicate the degree of phase coupling between two frequency components of a signal, are significantly higher within the delta-theta band of the EEG bursts than in the baseline or late recovery waveforms. The bispectral parameters show a more detectable trend than the power spectral parameters. In the second part of the study, we looked into the possibility of higher (> 2)--order nonlinearities in the EEG bursts using the diagonal slices of the polyspectrum. The diagonal elements of the polyspectrum reveal the presence of self-frequency and self-phase coupling of orders higher than two in majority of the EEG bursts studied. The bicoherence indexes and the diagonal elements of the polyspectrum strongly indicate the presence of nonlinearities of order two and in many cases higher, in the EEG generator during episodes of bursting. This indication of nonlinearity in EEG signals provides a novel quantitative measure of brain's response to injury.

Nonlinear changes in brain's response in the event of injury as detected by adaptive coherence estimation of evoked potentials.

Injury-related changes in evoked potentials are studied with the aid of the coherence function, which effectively measures the degree of linear association between a pair of signals recorded during normal and abnormal states of the brain. The performance of an adaptive algorithm for estimating coherence function is studied, and the effects of additive noise on the estimated coherence function is discussed. Further, a linearity index is formulated and, through analysis and simulations, the index is shown to respond in a predictable manner to increasing nonlinearity while maintaining the robustness to the observation noise. Somatosensory evoked potentials are shown to be sensitive to injury resulting from acute cerebral hypoxia. We analyze the somatosensory evoked potentials recorded from anesthetized cats during inhalation of 8-9% oxygen gas mixtures and during recovery with 100% oxygen. Analyses of the experimental data show a very sharp drop in the magnitude coherence estimates during hypoxic injury and a corresponding rapid decline in the linearity index at the very early stages of the hypoxic injury. Thus, injury may lead to nonlinearities in the electrical response of the brain, and such measurements analyzed by the adaptive coherence estimation method may be used for diagnostic purposes.

Ventricular tachycardia and fibrillation detection by a sequential hypothesis testing algorithm.

An algorithm for detecting ventricular fibrillation (VF) and ventricular tachycardia (VT) by the method of sequential hypothesis testing is presented. The algorithm first generates a binary sequence by comparing the signal to a threshold. The probability distribution of the time intervals of the binary sequence is obtained, and Wald's sequential hypothesis testing procedure is next employed to discriminate the arrhythmias. Sequential hypothesis testing of 85 cases resulted in identification of 1) 97.64% VF and 97.65% VT episodes after 5 s, and 2) 100% identification of both VF and VT after 7 s. The desired false positive and false negative error probabilities can be preprogrammed into the algorithm. An important feature of the sequential method is that extra time for detection can be traded off for improved accuracy, and vice versa.