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.

Applications and limitations of regulatory RNA elements in synthetic biology and biotechnology.

Synthetic biology requires the design and implementation of novel enzymes, genetic circuits or even entire cells, which can be controlled by the user. RNA-based regulatory elements have many important functional properties in this regard, such as their modular nature and their ability to respond to specific external stimuli. These properties have led to the widespread exploration of their use as gene regulation devices in synthetic biology. In this review, we focus on two major types of RNA elements: riboswitches and RNA thermometers (RNATs). We describe their general structure and function, before discussing their potential uses in synthetic biology (e.g. in the production of biofuels and biodegradable plastics). We also discuss their limitations, and novel strategies to implement RNA-based regulatory devices in biotechnological applications. We close with a description of some common model organisms used in synthetic biology, with a focus on the current applications and limitations of RNA-based regulation.

Cognitive workload modulation through degraded visual stimuli: a single-trial EEG study.

OBJECTIVE: Our experiments explored the effect of visual stimuli degradation on cognitive workload. APPROACH: We investigated the subjective assessment, event-related potentials (ERPs) as well as electroencephalogram (EEG) as measures of cognitive workload. MAIN RESULTS: These experiments confirm that degradation of visual stimuli increases cognitive workload as assessed by subjective NASA task load index and confirmed by the observed P300 amplitude attenuation. Furthermore, the single-trial multi-level classification using features extracted from ERPs and EEG is found to be promising. Specifically, the adopted single-trial oscillatory EEG/ERP detection method achieved an average accuracy of 85% for discriminating 4 workload levels. Additionally, we found from the spatial patterns obtained from EEG signals that the frontal parts carry information that can be used for differentiating workload levels. SIGNIFICANCE: Our results show that visual stimuli can modulate cognitive workload, and the modulation can be measured by the single trial EEG/ERP detection method.

Increased electroencephalographic gamma activity reveals awakening from isoflurane anaesthesia in rats.

BACKGROUND: Animal studies often require reliable measures for anaesthetic drug effects. Lately, EEG-based depth of anaesthesia estimation has been widely applied to rat models. This study investigated the reliability of different EEG spectral properties in revealing awakening from isoflurane anaesthesia in rats. METHODS: Adult Wistar rats with previously implanted frontal epidural electrodes were anaesthetized using isoflurane. The anaesthesia was slowly lightened until awakening, as observed by the first spontaneous movement, after which anaesthesia was induced again by increasing the isoflurane concentration. EEG was recorded during the recovery and induction periods, and the spectrograms and 23 quantitative spectral parameters used in the depth of anaesthesia estimation were calculated from the signals. RESULTS: The awakening was accompanied by a decrease in EEG activity at frequencies below 25 Hz, while the activity at higher frequencies (25-150 Hz) was increased. Whereas the behaviour of parameters used to measure activity in the lower frequencies was subject to variability between animals, the increase in higher frequency activity was more consistent, resulting in a statistically significant change in the relative gamma power parameters at the moment of awakening. CONCLUSIONS: The increase in frontal relative gamma activity, especially in the 50-150 Hz frequency band, seems to be the most reliable EEG indicator for the awakening of a rat from isoflurane anaesthesia. A number of other spectral measures can also be used to detect this event. However, the role of gamma frequencies in the performance of these parameters is crucial.

Spinal cord integrity monitoring by adaptive coherence measurement.

OBJECTIVE: Injury during routine spinal cord procedures could result in devastating consequences for the surgical patient. Spinal cord monitoring through somatosensory evoked potentials (SEPs) remains a viable method for prevention of serious injury. METHODS: The adaptive coherence estimation (ACE) is a method to iteratively calculate signal match quality through successive filter entrainment. Here we compare the speed of detection with ACE to conventional amplitude measurements. Both absolute magnitude of ACE and amplitude as well as slope change detector algorithm (Farley-Hinich) was run as well to determine the earliest time when a significant change occurred. RESULTS: The standard error for the ACE algorithm is close to one tenth of the amplitude measure, Since the ACE algorithm achieved low variance during baseline measurement, we were able to achieve rapid detection of injury. For absolute magnitude detection ACE was faster than amplitude for the 20 g injury weight class. It took an average of 10 epochs to detect the injury with adaptive coherence and nearly 19 with standard amplitude metrics using absolute magnitude changes. Abrupt change detection methods using slope change show that ACE provides more favorable detection capabilities comparable to amplitude. Additionally, there was a significant increase in the ROC curve between ACE and amplitude alone (p<0.05). CONCLUSIONS: Because of its excellent detection capabilities, the adaptive coherence method provides an excellent supplement to traditional amplitude for capturing injury-related changes in SEPs. SIGNIFICANCE: Adaptive coherence remains a viable method for rapidly and accurately detecting spinal injury.

Wireless micropower instrumentation for multimodal acquisition of electrical and chemical neural activity.

The intricate coupling between electrical and chemical activity in neural pathways of the central nervous system, and the implication of this coupling in neuropathologies, such as Parkinson's disease, motivates simultaneous monitoring of neurochemical and neuropotential signals. However, to date, neurochemical sensing has been lacking in integrated clinical instrumentation as well as in brain-computer interfaces (BCI). Here, we present an integrated system capable of continuous acquisition of data modalities in awake, behaving subjects. It features one channel each of a configurable neuropotential and a neurochemical acquisition system. The electrophysiological channel is comprised of a 40-dB gain, fully differential amplifier with tunable bandwidth from 140 Hz to 8.2 kHz. The amplifier offers input-referred noise below 2 muV rms for all bandwidth settings. The neurochemical module features a picoampere sensitivity potentiostat with a dynamic range spanning six decades from picoamperes to microamperes. Both systems have independent on-chip, configurable DeltaSigma analog-to-digital converters (ADCs) with programmable digital gain and resolution. The system was also interfaced to a wireless power harvesting and telemetry module capable of powering up the circuits, providing clocks for ADC operation, and telemetering out the data at up to 32 kb/s over 3.5 cm with a bit-error rate of less than 10(-5). Characterization and experimental results from the electrophysiological and neurochemical modules as well as the full system are presented.

Micropower CMOS Integrated Low-Noise Amplification, Filtering, and Digitization of Multimodal Neuropotentials.

Electrical activity in the brain spans a wide range of spatial and temporal scales, requiring simultaneous recording of multiple modalities of neurophysiological signals in order to capture various aspects of brain state dynamics. Here, we present a 16-channel neural interface integrated circuit fabricated in a 0.5 mum 3M2P CMOS process for selective digital acquisition of biopotentials across the spectrum of neural signal modalities in the brain, ranging from single spike action potentials to local field potentials (LFP), electrocorticograms (ECoG), and electroencephalograms (EEG). Each channel is composed of a tunable bandwidth, fixed gain front-end amplifier and a programmable gain/resolution continuous-time incremental DeltaSigma analog-to-digital converter (ADC). A two-stage topology for the front-end voltage amplifier with capacitive feedback offers independent tuning of the amplifier bandpass frequency corners, and attains a noise efficiency factor (NEF) of 2.9 at 8.2 kHz bandwidth for spike recording, and a NEF of 3.2 at 140 Hz bandwidth for EEG recording. The amplifier has a measured midband gain of 39.6 dB, frequency response from 0.2 Hz to 8.2 kHz, and an input-referred noise of 1.94 muV rms while drawing 12.2 muA of current from a 3.3 V supply. The lower and higher cutoff frequencies of the bandpass filter are adjustable from 0.2 to 94 Hz and 140 Hz to 8.2 kHz, respectively. At 10-bit resolution, the ADC has an SNDR of 56 dB while consuming 76 muW power. Time-modulation feedback in the ADC offers programmable digital gain (1-4096) for auto-ranging, further improving the dynamic range and linearity of the ADC. Experimental recordings with the system show spike signals in rat somatosensory cortex as well as alpha EEG activity in a human subject.

Monitoring of global cerebral ischemia using instantaneous phase variation plots.

In this paper, the derivative of the instantaneous phase of electroencephalographic (EEG) signals is used as a basis for monitoring of global cerebral ischemia. Visual and quantitative results were obtained from six rodents that were subject to 3, 5 and 7 minutes of global ischemic brain injury by asphyxic cardiac arrest. Results show that the variations in the instantaneous phase are capable of amplifying the variations 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.

Contrast-enhanced imaging of cerebral vasculature with laser speckle.

High-resolution cerebral vasculature imaging has applications ranging from intraoperative procedures to basic neuroscience research. Laser speckle, with spatial contrast processing, has recently been used to map cerebral blood flow. We present an application of the technique using temporal contrast processing to image cerebral vascular structures with a field of view a few millimeters across and approximately 20 microm resolution through a thinned skull. We validate the images using fluorescent imaging and demonstrate a factor of 2-4 enhancement in contrast-to-noise ratios over reflectance imaging using white or spectrally filtered green light. The contrast enhancement enables the perception of approximately 10%-30% more vascular structures without the introduction of any contrast agent.

VLSI Potentiostat Array With Oversampling Gain Modulation for Wide-Range Neurotransmitter Sensing.

A 16-channel current-measuring very large-scale integration (VLSI) sensor array system for highly sensitive electrochemical detection of electroactive neurotransmiters like dopamine and nitric-oxide is presented. Each channel embeds a current integrating potentiostat within a switched-capacitor first-order single-bit delta-sigma modulator implementing an incremental analog-to-digital converter. The duty-cycle modulation of current feedback in the delta-sigma loop together with variable oversampling ratio provide a programmable digital range selection of the input current spanning over six orders of magnitude from picoamperes to microamperes. The array offers 100-fA input current sensitivity at 3.4-muW power consumption per channel. The operation of the 3 mm times3 mm chip fabricated in 0.5-mum CMOS technology is demonstrated with real-time multichannel acquisition of neurotransmitter concentration.

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.

Investigation of the effects of ischemic preconditioning on the HRV response to transient global ischemia using linear and nonlinear methods.

Ischemic preconditioning (IP) has been used as a strategy to prevent cell death in various organs, including the brain and the heart. Investigation of the effects of ischemic preconditioning mostly employed models with reduced complexity, such as cell cultures, tissue slices or perfused organ preparations. Although such models can provide valuable insight into the protective mechanism of preconditioning, the functional (re)organization of the control mechanisms at the level of the living organism cannot be assessed. The purpose of the present animal model study was to evaluate the effect of global ischemic preconditioning on the heart rate variability (HRV) response to the asphyxia insult. The data consisted of 4 h RR interval measurements recorded in five preconditioned and five non-preconditioned Wistar rats. Using linear (time and frequency domain) and nonlinear (approximate entropy and parameters of Poincare plots) measures, we evaluated the dynamic time course of the HRV response to the asphyxia insult and the effect of preconditioning on the autonomic neurocardiac control. Both the linear and nonlinear parameters indicate a faster recovery of the baseline HRV corresponding to the preconditioned groups, though only the spectral analysis identifies a statistically significant difference between the two groups. For the preconditioned group, at about 90 min after the asphyxic insult, the autonomic neural balance (measured by LF/HF ratio) appears fully recovered. The small variation of the rest of the parameters indicates the necessity of further investigation including the design of a larger study with a higher statistical power. Our results show for the first time that global ischemic preconditioning influences the HRV response to the asphyxia injury. The neuroprotective effect of preconditioning translates into a faster recovery of the basal HRV and the autonomic modulation of the heart.

MEMSurgery: an integrated test-bed for vascular surgery.

Many surgical procedures require skillful manipulations of blood vessels, especially in conventional invasive or minimally invasive surgical procedures. Current surgical methods do not allow the surgeon to receive any real time feedback of the tissue properties when operating on the vessel. As a result, the unintentional application of excessive force may damage the blood vessel. To minimize such trauma, and to study the interaction of surgical instruments with the vessel structure, we have developed an integrated surgical testbed called MEMSurgery (Microelectromechanical Sensory augmented Surgery). The test-bed integrates four elements: a) force sensors mounted on surgical appliances, b) a feedback control mechanism utilizing the intrinsic mechanical properties of the blood vessel, c) feedback of the force applied on the tissue back to the surgeon through a haptic feedback device, and d) visual feedback by a graphical computer model of the vessel. Finally, we evaluate the performance of MEMSurgery by testing the hypothesis that the combination of haptic feedback, feedback control based on vascular mechanical properties, and real-time visual representation of the vessel will help the surgeon decrease the probability of applying excess force while occluding the blood vessel. To this end, we designed a rodent experimental model to obtain the ideal minimum occlusion force (MOF). After a series of human performance studies, and subsequent comparison to direct application of force on the forceps (without feedback), the results show that the probability of applying reasonable MOF increases from 35.5% to 80%. After a brief training period, the probability increases to 90%.

Characterization of heart rate variability changes following asphyxia in rats.

OBJECTIVES: A non-invasive method to monitor the functioning of the autonomous nervous system consists in heart rate variability (HRV) analysis. The aim of this study was to investigate the changes on HRV after an asphyxia experiment in rats, using several linear (time and frequency domain) and nonlinear parameters (approximate entropy, SD1 and SD2 indices derived from Poincare plots). METHODS: The experiments involved the study of HRV changes after cardiac arrest (CA) resulting from 5 min of hypoxia and asphyxia, followed by manual resuscitation and return of spontaneous circulation. 5 min stationary periods of RR intervals were selected for further analysis from 5 rats in following distinct situations: 1) baseline, 2) 30 min after CA, 3) 60 min after CA, 4) 90 min after CA, 5) 120 min after CA, 6) 150 min after CA. The ANS contribution has been delineated based on time and frequency domain analysis. RESULTS AND CONCLUSIONS: The results indicate that the recovery process following the asphyxia cardiac arrest reflects the impaired functioning of the autonomic nervous system. Both linear and nonlinear parameters track the different phases of the experiment, with an increased sensitivity displayed by the approximate entropy (ApEn). After 150 min the ApEn RRI parameter recovers to its baseline value. The results forward the ApEn as a more sensitive parameter of the recovery process following the asphyxia.

Neural interfacing.

The problem of interfacing microsystems to neurons or brain has led to exciting developments in the fields of micro/nanotechnologies and integrated circuitry and systems. Neurons have been patterned using micro/nanotechnologies to form structural and functional networks. Micro-electrodes and integrated circuitry have been developed for large scale, multichannel measurements from brain tissue. Driving force for this technology comes from research and clinical interest in the emerging fields of neural prosthesis, deep brain stimulations and brain-machine interface. This review presents some examples of the work done in the field of neural patterning, tissue interfacing, electrodes, recording and system integration.

Time-dependent entropy estimation of EEG rhythm changes following brain ischemia.

Our approach is motivated by the need to generate a rigorous measure of the degree of disorder (or complexity) of the EEG signal in brain injury. Entropy is a method to quantify the order/disorder of a time series. It is the first time that a time-dependent entropy (TDE) is used in the quantification of brain injury level. The TDE was sensitive enough to monitor the significant changes in the subject's brain rhythms during recovery from global ischemic brain injury. Among the different entropy measures, we used Tsallis entropy. This entropy is parametrized and is able to match with the particular properties of EEG, like long-range rhythms, spikes, and bursts. The method was tested in a signal composed of segments of synthetic signals (Gaussian and uniform distributions) and segments of real signals. The real signal segments were extracted from normal EEG, EEG recordings from early recovery, and normal EEG corrupted by simulated spikes and bursts. Adult Wistar rats were subjected to asphyxia-cardiac arrest for 3 and 5 min. The TDE detected the pattern of ischemia-induced EEG alterations and was able to discriminate the different injury levels. Two parameters seem to be good descriptors of the recovery process; the mean entropy and the variance of the estimate followed opposite trends, with the mean entropy decreasing and its variance increasing with injury.

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.

Detection of asphyxia using heart rate variability.

The long-term aims of this study are to find a parameter derived from the ECG that has a high sensitivity and specificity to asphyxia and, once we know or suspect that asphyxia occurred, to estimate how severe it was. We carried out a pilot study in which 24 adult Wistar rats were anaesthetised and subjected to controlled asphyxia for specified durations. We measured the pH, 'neurological score' and the ECG, extracting from this heart rate and heart rate variability (HRV). We have developed a technique capable of detecting asphyxia in less than 1 min, based on monitoring the ECG and estimating HRV by measuring the standard deviation of normal RR intervals (the RR interval is the time interval between two consecutive R-points of the QRS complex). In all cases the heart rate decreased and HRV increased, by an average of 46 +/- 33 ms in relation to the baseline, at the onset of asphyxia. The comparison of the base level of HRV after and before asphyxia shows promise for the estimation of the severity of the episode; however, the limitations of this study should be noted as they include the small size of the cohort and the methods of analysis.

A short-time multifractal approach for arrhythmia detection based on fuzzy neural network.

We have proposed the notion of short-time multifractality and used it to develop a novel approach for arrhythmia detection. Cardiac rhythms are characterized by short-time generalized dimensions (STGDs), and different kinds of arrhythmias are discriminated using a neural network. To advance the accuracy of classification, a new fuzzy Kohonen network, which overcomes the shortcomings of the classical algorithm, is presented. In our paper, the potential of our method for clinical uses and real-time detection was examined using 180 electrocardiogram records [60 atrial fibrillation, 60 ventricular fibrillation, and 60 ventricular tachycardia]. The proposed algorithm has achieved high accuracy (more than 97%) and is computationally fast in detection.

Pathological analysis of myocardial cell under ventricular tachycardia and fibrillation based on symbolic dynamics.

Ventricular fibrillation (VF) is one of the most serious malignant arrhythmias usually resulting from immediate degeneration of ventricular tachycardia (VT). In order to analyse the nonlinear dynamics of the cardiac micro-mechanism under VT and VT rhythm, at the cellular level, myocardial cell action potentials are investigated under different rhythm, normal sinus rhythm, VT and VT. On the basis of nonlinear chaotic theory and symbolic dynamics, we put forward new definitions, complexity rate, etc, and obtained some useful properties for cellular electrophysiological analysis. The results of the experiments and computation show that the myocardial cellular signals under VT and VF rhythm are different kinds of chaotic signals in that the cardiac chaos attractor under VF is higher than that under VT. The analytical complexity theory has been promising in the clinical application.