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Prospects of implant with locking plate in fixation of subtrochanteric fracture: experimental demonstration of its potential benefits on synthetic femur model with supportive hierarchical nonlinear hyperelastic finite element analysis

Hadi Latifi — 2012-04-30T00:00:00Z

Background: Effective fixation of fracture requires careful selection of a suitable implant to provide stability and durability. Implant with a feature of locking plate (LP) has been used widely for treating distal fractures in femur because of its favourable clinical outcome, but its potential in fixing proximal fractures in the subtrochancteric region has yet to be explored. Therefore, this comparative study was undertaken to demonstrate the merits of the LP implant in treating the subtrochancteric fractures by comparing its performance limits against those obtained with the more traditional implants; angle blade plate (ABP) and dynamic condylar screw plate (DCSP).Materials and Methods: Nine standard composite femurs were acquired, divided into three groups and fixed with LP (n=3), ABP (n=3)and DCSP (n=3). The fracture was modeled by a 20 mm gap created at the subtrochanteric region to experimentally study the biomechanical response of each implant under axial static and dynamic loading paradigms. To confirm the experimental findings and to understand the critical interactions at the boundaries, the synthetic femur/implant systems were numerically analyzed by constructing hierarchical finite element models with nonlinear hyperelastic properties. The predictions from the analyses were then compared against the experimental measurements to demonstrate the validity of the numeric model, and to characterize the internal load distribution in the femur and load bearing properties of each implant. Results: The average measurements indicated that the constructs with ABP, DCPS and LP respectively had overall stiffness values of 70.9, 110.2 and 131.4 N/mm, and exhibited reversible deformations of 12.4, 4.9 and 4.1 mm when the applied dynamic load was 400 N and plastic deformations of 11.3, 2.4 and 1.4 mm when the load was 1000 N. The corresponding peak cyclic loads to failure were 1100, 1167 and 1600 N. The errors between the displacements measured experimentally or predicted by the nonlinear hierarchical hyperelastic model were less than 18 %. In the implanted femur heads, the principal stresses were spatially heterogeneous for ABP and DCSP but more homogenous for LP, meaning LP had lower stress concentration. Conclusion: When fixed with the LP implant, the synthetic femur model of the subtrochancteric fracture consistently exceeds in the key biomechanical measures of stability and durability. These capabilities suggest increased resistance to fatigue and failure, which are highly desirable features expected of implants make the LP implant potentially a viable alternative to the conventional ABP or DCSP in the treatment of the subtrochancteric femur fractures for the betterment of the clinical outcome.

In-vitro characterization of a cochlear implant system for recording of evoked compound action potentials

Christian Neustetter — 2012-04-25T00:00:00Z

Background: Modern cochlear implants have integrated recording systems for measuring electrically evoked compound action potentials of the auditory nerve. The characterization of such recording systems is important for establishing a reliable basis for the interpretation of signals acquired in vivo. In this study we investigated the characteristics of the recording system integrated into the MED-EL PULSARCI100 cochlear implant, especially its linearity and resolution, in order to develop a mathematical model describing the recording system. Methods: In-vitro setup: The cochlear implant, including all attached electrodes, was fixed in a tank of physiologic saline solution. Sinusoidal signals of the same frequency but with different amplitudes were delivered via a signal generator for measuring and recording on a single electrode.Computer simulations: A basic mathematical model including the main elements of the recording system, i.e. amplification and digitalization stage, was developed. For this, digital output for sinusoidal input signals of different amplitudes were calculated using in-vitro recordings as reference. Results: Using an averaging of 100 measurements the recording system behaved linearly down to approximately -60 dB of the input signal range. Using the same method, a system resolution of 10 μV was determined for sinusoidal signals. The simulation results were in very good agreement with the results obtained from in-vitro experiments. Conclusions: The recording system implemented in the MED-EL PULSARCI100 cochlear implant for measuring the evoked compound action potential of the auditory nerve operates reliably. The developed mathematical model provides a good approximation of the recording system.

Patient-oriented simulation based on Monte Carlo algorithm by using MRI data

Ching-Cheng Chuang — 2012-04-17T00:00:00Z

Background: Although Monte Carlo simulations of light propagation in full segmented three-dimensional MRI based anatomical models of the human head have been reported in many articles. To our knowledge, there is no patient-oriented simulation for individualized calibration with NIRS measurement. Thus, we offer an approach for brain modeling based on image segmentation process with in vivo MRI T1 three-dimensional image to investigate the individualized calibration for NIRS measurement with Monte Carlo simulation. Methods: In this study, an individualized brain is modeled based on in vivo MRI 3D image as five layers structure. The behavior of photon migration was studied for this individualized brain detections based on three-dimensional time-resolved Monte Carlo algorithm. During the Monte Carlo iteration, all photon paths were traced with various source-detector separations for characterization of brain structure to provide helpful information for individualized design of NIRS system. Results: Our results indicate that the patient-oriented simulation can provide significant characteristics on the optimal choice of source-detector separation within 3.3 cm of individualized design in this case. Significant distortions were observed around the cerebral cortex folding. The spatial sensitivity profile penetrated deeper to the brain in the case of expanded CSF. This finding suggests that the optical method may provide not only functional signal from brain activation but also structural information of brain atrophy with the expanded CSF layer. The proposed modeling method also provides multi-wavelength for NIRS simulation to approach the practical NIRS measurement. Conclusions: In this study, the three-dimensional time-resolved brain modeling method approaches the realistic human brain that provides useful information for NIRS systematic design and calibration for individualized case with prior MRI data.

Independent effects of adding weight and inertia on balance during quiet standing

Kerry Costello — 2012-04-16T00:00:00Z

Background: Human balance during quiet standing is influenced by adding mass to the body with a backpack, with symmetrically-applied loads to the trunk, or with obesity. Adding mass to the body increases both the weight and inertia of the body, which theoretically could provide counteracting effects on body dynamics and balance. Understanding the independent effects of adding weight and inertia on balance may provide additional insight into human balance that could lead to novel advancements in balance training and rehabilitation. Therefore, the purpose of this study was to investigate the independent effects of adding weight and inertia on balance during quiet standing. Methods: Sixteen normal-weight young adult participants stood as still as possible on a custom-built backboard apparatus under four experimental conditions: baseline, added inertia only, added weight only, and added inertia and weight. Results: Adding inertia by itself had no measurable effect on center of pressure movement or backboard movement. Adding weight by itself increased center of pressure movement (indicated greater effort by the postural control system to stand as still as possible) and backboard movement (indicating a poorer ability of the body to stand as still as possible). Adding inertia and weight at the same time increased center of pressure movement but did not increase backboard movement compared to the baseline condition. Conclusions: Adding inertia and adding weight had different effects on balance. Adding inertia by itself had no effect on balance. Adding weight by itself had a negative effect on balance. When adding inertia and weight at the same time, the added inertia appeared to lessen (but did not eliminate) the negative effect of adding weight on balance. These results improve our fundamental understanding of how added mass influences human balance.

Transfer Entropy Estimation and Directional Coupling Change Detection in Biomedical Time Series

Joon Lee — 2012-04-13T00:00:00Z

Background: The detection of change in magnitude of directional coupling between two non-linear time series is a commonsubject of interest in the biomedical domain, including studies involving the respiratory chemoreflex system.Although transfer entropy is a useful tool in this avenue, no study to date has investigated how different transferentropy estimation methods perform in typical biomedical applications featuring small sample size and presenceof outliers. Methods: With respect to detection of increased coupling strength, we compared three transfer entropy estimationtechniques using both simulated time series and respiratory recordings from lambs. The following estimationmethods were analyzed: fixed-binning with ranking, kernel density estimation (KDE), and the Darbellay-Vajda(D-V) adaptive partitioning algorithm extended to three dimensions. In the simulated experiment, sample sizewas varied from 50 to 200, while coupling strength was increased. In order to introduce outliers, the heavy-tailedLaplace distribution was utilized. In the lamb experiment, the objective was to detect increased respiratory-relatedchemosensitivity to O2 and CO2 induced by a drug, domperidone. Specifically, the separate influence of end-tidalPO2 and PCO2 on minute ventilation ( VE ) before and after administration of domperidone was analyzed. Results: In the simulation, KDE detected increased coupling strength at the lowest SNR among the three methods. In thelamb experiment, D-V partitioning resulted in the statistically strongest increase in transfer entropypost-domperidone for PO2 -> VE . In addition, D-V partitioning was the only method that could detect anincrease in transfer entropy for PCO2 -> VE , in agreement with experimental findings. Conclusions: Transfer entropy is capable of detecting directional coupling changes in non-linear biomedical time seriesanalysis featuring a small number of observations and presence of outliers. The results of this study suggest thatfixed-binning, even with ranking, is too primitive, and although there is no clear winner between KDE and D-Vpartitioning, the reader should note that KDE requires more computational time and extensive parameter selectionthan D-V partitioning. We hope this study provides a guideline for selection of an appropriate transfer entropy estimation method.

Stream-based Hebbian Eigenfilter for real-time neuronal spike discrimination

Bo Yu — 2012-04-10T00:00:00Z

Background: Principal component analysis (PCA) has been widely employed for automatic neuronal spike sorting. Calculating principal components (PCs) is computationally expensive, and requires complex numerical operations and large memory resources. Substantial hardware resources are therefore needed for hardware implementations of PCA. General Hebbian algorithm (GHA) has been proposed for calculating PCs of neuronal spikes in our previous work, which eliminates the needs of computationally expensive covariance analysis and eigenvalue decomposition in conventional PCA algorithms. However, large memory resources are still inherently required for storing a large volume of aligned spikes for training PCs. The large size memory will consume large hardware resources and contribute significant power dissipation, which make GHA difficult to be implemented in portable or implantable multi-channel recording micro-systems.MethodIn this paper, we present a new algorithm for PCA-based spike sorting based on GHA, namely stream-based Hebbian eigenfilter, which eliminates the inherent memory requirements of GHA while keeping the accuracy of spike sorting by utilizing the pseudo-stationarity of neuronal spikes. Because of the reduction of large hardware storage requirements, the proposed algorithm can lead to ultra-low hardware resources and power consumption of hardware implementations, which is critical for the future multi-channel micro-systems. Both clinical and synthetic neural recording data sets were employed for evaluating the accuracy of the stream-based Hebbian eigenfilter. The performance of spike sorting using stream-based eigenfilter and the computational complexity of the eigenfilter were rigorously evaluated and compared with conventional PCA algorithms. Field programmable logic arrays (FPGAs) were employed to implement the proposed algorithm, evaluate the hardware implementations and demonstrate the reduction in both power consumption and hardware memories achieved by the streaming computingResults and discussionResults demonstrate that the stream-based eigenfilter can achieve the same accuracy and is 10 times more computationally efficient when compared with conventional PCA algorithms. Hardware evaluations show that 90.3% logic resources, 95.1% power consumption and 86.8% computing latency can be reduced by the stream-based eigenfilter when compared with PCA hardware. By utilizing the streaming method, 92% memory resources and 67% power consumption can be saved when compared with the direct implementation of GHA. Conclusion: Stream-based Hebbian eigenfilter presents a novel approach to enable real-time spike sorting with reduced computational complexity and hardware costs. This new design can be further utilized for multi-channel neuro-physiological experiments or chronic implants.

Improved frequency resolution for characterization of complex fractionated atrial electrograms

Edward Ciaccio — 2012-04-03T00:00:00Z

Background: The dominant frequency of the Fourier power spectrum is useful to analyze complex fractionated atrial electrograms (CFAE), but spectral resolution is limited and uniform from DC to the Nyquist frequency. Herein the spectral resolution of a recently described and relatively new spectral estimation technique is compared to the Fourier radix-2 implementation. Methods: In 10 paroxysmal and 10 persistent atrial fibrillation patients, 216 CFAE were acquired from the pulmonary vein ostia and left atrial free wall (977 Hz sampling rate, 8192 sample points, 8.4 s duration). With these parameter values, in the physiologic range of 3-10 Hz, two frequency components can theoretically be resolved at 0.24 Hz using Fourier analysis and at 0.10 Hz on average using the new technique. For testing, two closely-spaced periodic components were synthesized from two different CFAE recordings, and combined with two other CFAE recordings magnified 2x, that served as interference signals. The ability to resolve synthesized frequency components in the range 3-4 Hz, 4-5 Hz, ..., 9-10 Hz was determined for 15 trials each (105 total). Methods: In 10 paroxysmal and 10 persistent atrial fibrillation patients, 216 CFAE were acquired from the pulmonary vein ostia and left atrial free wall (977Hz sampling rate, 8192 sample points, 8.4s duration). With these parameter values, in the physiologic range of 3-10Hz, two frequency components can theoretically be resolved at 0.24Hz using Fourier analysis and at 0.10Hz on average using the new technique. For testing, two closely-spaced periodic components were synthesized from two different CFAE recordings, and combined with two other CFAE recordings magnified 2x, that served as interference signals. The ability to resolve synthesized frequency components in the range 3-4Hz, 4-5Hz, ..., 9-10Hz was determined for 15 trials each (105 total). Results: With the added interference, frequency resolution averaged 0.29+/-0.22Hz for Fourier versus 0.16+/-0.10Hz for the new method (p<0.001). The misalignment error of spectral peaks versus actual values was +/-0.023Hz for Fourier and +/-0.009Hz for the new method (p<0.001). One or both synthesized peaks were lost in the noise floor 13/105 times using Fourier versus 4/105 times using the new method. Conclusions: Within the physiologically relevant frequency range for characterization of CFAE, the new method has approximately twice the spectral resolution of Fourier analysis, there is less error in estimating frequencies, and peaks appear more readily above the noise floor. Theoretically, when interference is not present, to resolve frequency components separated by 0.10Hz using Fourier analysis would require an 18.2s sequence duration, versus 8.4s with the new method.

Spatiotemporal representation of cardiac vectorcardiogram (VCG) signals

Hui Yang — 2012-03-30T00:00:00Z

Background: Vectorcardiogram (VCG) signals monitor both spatial and temporal cardiac electrical activities along three orthogonal planes of the body. However, the absence of spatiotemporal resolution in conventional VCG representations is a major impediment for medical interpretation and clinical usage of VCG. This is especially so because time-domain features of 12-lead ECG, instead of both spatial and temporal characteristics of VCG, are widely used for the automatic assessment of cardiac pathological patterns.Materials and methodsWe present a novel representation approach that captures critical spatiotemporal heart dynamics by displaying the real time motion of VCG cardiac vectors in a 3D space. Such a dynamic display can also be realized with only one lead ECG signal (e.g., ambulatory ECG) through an alternative lag-reconstructed ECG representation from nonlinear dynamics principles. Furthermore, the trajectories are color coded with additional dynamical properties of space-time VCG signals, e.g., the curvature, speed, octant and phase angles to enhance the information visibility. Results: In this investigation, spatiotemporal VCG signal representation is used to characterize various spatiotemporal pathological patterns for healthy control (HC), myocardial infarction (MI), atrial fibrillation (AF) and bundle branch block (BBB). The proposed color coding scheme revealed that the spatial locations of the peak of T waves are in the Octant 6 for the majority (i.e., 74 out of 80) of healthy recordings in the PhysioNet PTB database. In contrast, the peak of T waves from 31.79% (117/368) of MI subjects are found to remain in Octant 6 and the rest (68.21%) spread over all other octants. The spatiotemporal VCG signal representation is shown to capture the same important heart characteristics as the 12-lead ECG plots and more. Conclusions: Spatiotemporal VCG signal representation is shown to facilitate the characterization of space-time cardiac pathological patterns and enhance the automatic assessment of cardiovascular diseases.

A new LMS algorithm for analysis of atrial fibrillation signals

Edward Ciaccio — 2012-03-26T00:00:00Z

Background: A biomedical signal can be defined by its extrinsic features (x-axis and y-axis shift and scale) and intrinsic features (shape after normalization of extrinsic features). In this study, an LMS algorithm utilizing the method of differential steepest descent is developed, and is tested by normalization of extrinsic features in complex fractionated atrial electrograms (CFAE).MethodEquations for normalization of x-axis and y-axis shift and scale are first derived. The algorithm is implemented for real-time analysis of CFAE acquired during atrial fibrillation (AF). Data was acquired at a 977 Hz sampling rate from 10 paroxysmal and 10 persistent AF patients undergoing clinical electrophysiologic study and catheter ablation therapy. Over 24 trials, normalization characteristics using the new algorithm with four weights were compared to the Widrow-Hoff LMS algorithm with four tapped delays. The time for convergence, and the mean squared error (MSE) after convergence, were compared. The new LMS algorithm was also applied to lead aVF of the electrocardiogram in one patient with longstanding persistent AF, to enhance the F wave and to monitor extrinsic changes in signal shape. The average waveform over a 25 s interval was used as a prototypical reference signal for matching with the aVF lead. Results: Based on the derivation equations, the y-shift and y-scale adjustments of the new LMS algorithm were shown to be equivalent to the scalar form of the Widrow-Hoff LMS algorithm. For x-shift and x-scale adjustments, rather than implementing a long tapped delay as in Widrow-Hoff LMS, the new method uses only two weights. After convergence, the MSE for matching paroxysmal CFAE averaged 0.46 +/- 0.49 uV2/sample for the new LMS algorithm versus 0.72 +/- 0.35 uV2/sample for Widrow-Hoff LMS. The MSE for matching persistent CFAE averaged 0.55 +/- 0.95 uV2/sample for the new LMS algorithm versus 0.62 +/- 0.55 uV2/sample for Widrow-Hoff LMS. There were no significant differences in estimation error for paroxysmal versus persistent data. From all trials, the mean convergence time was approximately 1 second for both algorithms. The new LMS algorithm was useful to enhance the electrocardiogram F wave by subtraction of an adaptively weighted prototypical reference signal from the aVF lead. The extrinsic weighting over 25 s demonstrated that time-varying functions such as patient respiration could be identified and monitored. Conclusions: A new LMS algorithm was derived and used for normalization of the extrinsic features in CFAE and for electrocardiogram monitoring. The weighting at convergence provides an estimate of the degree of similarity between two signals in terms of x-axis and y-axis shift and scale. The algorithm is computationally efficient with low estimation error. Based on the results, proposed applications include monitoring of extrinsic and intrinsic features of repetitive patterns in CFAE, enhancement of the electrocardiogram F wave and monitoring of time-varying signal properties, and to quantitatively characterize mechanistic differences in paroxysmal versus persistent AF.

In vivo assessment of the host reactions to the biodegradation of the two novel magnesium alloys ZEK100 and AX30 in an animal model

Tim Huehnerschulte — 2012-03-20T00:00:00Z

Background: Most studies on biodegradable magnesium implants published recently use magnesium-calcium-alloys or magnesium-aluminum-rare earth-alloys.However, since rare earths are a mixture of elements and their toxicity is unclear, a reduced content of rare earths is favorable. The present study assesses the in vivo biocompatibility of two new magnesium alloys which have a reduced content (ZEK100) or contain no rare earths at all (AX30). Methods: 24 rabbits were randomized into 4 groups (AX30 or ZEK100, 3 or 6 months, respectively) and cylindrical pins were inserted in their tibiae. To assess the biodegradation μCT scans and histological examinations were performed. Results: The μCT scans showed that until month three ZEK100 degrades faster than AX30, but this difference is leveled out after 6 months. Histology revealed that both materials induce adverse host reactions and high numbers of osteoclasts in the recipient bone. The mineral apposition rates of both materials groups were high. Conclusions: Both alloys display favorable degradation characteristics, but they induce adverse host reactions, namely an osteoclast-driven resorption of bone and a subsequent periosteal formation of new bone. Therefore, the biocompatibility of ZEK100 and AX30 is questionable and further studies, which should focus on the interactions on cellular level, are needed.