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Sample preparation is a crucial step in single-molecule experiments and involves passivating the microfluidic sample chamber, immobilizing the molecules, and setting experimental ...buffer conditions. The efficiency of the experiment depends on the quality and speed of sample preparation, which is often performed manually and relies on the experience of the experimenter. This can result in inefficient use of single-molecule samples and time, especially for high-throughput applications. To address this, a pressure-controlled microfluidic system is proposed to automate single-molecule sample preparation. The hardware is based on microfluidic components from ElveFlow and is designed to be cost-effective and adaptable to various microscopy applications. The system includes a reservoir pressure adapter and a reservoir holder designed for additive manufacturing. Two flow chamber designs Ibidi µ-slide and Grace Bio-Labs HybriWell chamber are characterized, and the flow characteristics of the liquid at different volume flow rates V̇ are simulated using CFD-simulations and compared to experimental and theoretical values. The goal of this work is to establish a straightforward and robust system for single-molecule sample preparation that can increase the efficiency of experiments and reduce the bottleneck of manual sample preparation, particularly for high-throughput applications.
The human voice signal originates from the vibrations of the two vocal folds within the larynx. The interactions of several intrinsic laryngeal muscles adduct and shape the vocal folds to facilitate ...vibration in response to airflow. Three-dimensional vocal fold dynamics are extracted from in vitro hemilarynx experiments and fitted by a numerical three-dimensional-multi-mass-model (3DM) using an optimization procedure. In this work, the 3DM dynamics are optimized over 24 experimental data sets to estimate biomechanical vocal fold properties during phonation. Accuracy of the optimization is verified by low normalized error (0.13 ± 0.02), high correlation (83% ± 2%), and reproducible subglottal pressure values. The optimized, 3DM parameters yielded biomechanical variations in tissue properties along the vocal fold surface, including variations in both the local mass and stiffness of vocal folds. That is, both mass and stiffness increased along the superior-to-inferior direction. These variations were statistically analyzed under different experimental conditions (e.g., an increase in tension as a function of vocal fold elongation and an increase in stiffness and a decrease in mass as a function of glottal airflow). The study showed that physiologically relevant vocal fold tissue properties, which cannot be directly measured during in vivo human phonation, can be captured using this 3D-modeling technique.
Human voice originates from the three-dimensional (3D) oscillations of the vocal folds. In previous studies, biomechanical properties of vocal fold tissues have been predicted by optimizing the ...parameters of simple two-mass-models to fit its dynamics to the high-speed imaging data from the clinic. However, only lateral and longitudinal displacements of the vocal folds were considered. To extend previous studies, a 3D mass-spring, cover-model is developed, which predicts the 3D vibrations of the entire medial surface of the vocal fold. The model consists of five mass planes arranged in vertical direction. Each plane contains five longitudinal, mass-spring, coupled oscillators. Feasibility of the model is assessed using a large body of dynamical data previously obtained from excised human larynx experiments, in vivo canine larynx experiments, physical models, and numerical models. Typical model output was found to be similar to existing findings. The resulting model enables visualization of the 3D dynamics of the human vocal folds during phonation for both symmetric and asymmetric vibrations.
In this work a detection algorithm for mucosal wave propagation is presented. By incorporating physiological knowledge of mucosal wave properties and taking the segmented lateral movement of both ...vocal fold edges as a basis, the spatio-temporal position of the traveling mucosal wave is identified and quantitatively captured. The course of mucosal wave propagation can be successfully detected and analyzed with regard to discriminating different types of mucosal wave activity (in terms of spread velocity and symmetry). The preliminary results obtained for six exemplary laryngeal high-speed recordings are promising and demonstrate the potential of the proposed detection and objective description approach.
Abstract The clinical diagnosis of voice disorders is based on examination of the rapidly moving vocal folds during phonation (f0: 80–300 Hz) with state-of-the-art endoscopic high-speed cameras. ...Commonly, analysis is performed in a subjective and time-consuming manner via slow-motion video playback and exhibits low inter- and intra-rater reliability. In this study an objective method to overcome this drawback is presented being based on Phonovibrography, a novel image analysis technique. For a collective of 45 normophonic and paralytic voices the laryngeal dynamics were captured by specialized Phonovibrogram features and analyzed with different machine learning algorithms. Classification accuracies reached 93% for 2-class and 73% for 3-class discrimination. The results were validated by subjective expert ratings given the same diagnostic criteria. The automatic Phonovibrogram analysis approach exceeded the experienced raters’ classifications by 9%. The presented method holds a lot of potential for providing reliable vocal fold diagnosis support in the future.
Abstract Objective This work presents a computer-aided method for automatically and objectively classifying individuals with healthy and dysfunctional vocal fold vibration patterns as depicted in ...clinical high-speed (HS) videos of the larynx. Methods By employing a specialized image segmentation and vocal fold movement visualization technique – namely phonovibrography – a novel set of numerical features is derived from laryngeal HS videos capturing the dynamic behavior and the symmetry of oscillating vocal folds. In order to assess the discriminatory power of the features, a support vector machine is applied to the preprocessed data with regard to clinically relevant diagnostic tasks. Finally, the classification performance of the learned nonlinear models is evaluated to allow for conclusions to be drawn about suitability of features and data resulting from different examination paradigms. As a reference, a second feature set is determined which corresponds to more traditional voice analysis approaches. Results For the first time an automatic classification of healthy and pathological voices could be obtained by analyzing the vibratory patterns of vocal folds using phonovibrograms (PVGs). An average classification accuracy of approximately 81% was achieved for 2-class discrimination with PVG features. This exceeds the results obtained through traditional voice analysis features. Furthermore, a relevant influence of phonation frequency on classification accuracy was substantiated by the clinical HS data. Conclusion The PVG feature extraction and classification approach can be assessed as being promising with regard to the diagnosis of functional voice disorders. The obtained results indicate that an objective analysis of dysfunctional vocal fold vibration can be achieved with considerably high accuracy. Moreover, the PVG classification method holds a lot of potential when it comes to the clinical assessment of voice pathologies in general, as the diagnostic support can be provided to the voice clinician in a timely and reliable manner. Due to the observed interdependency between phonation frequency and classification accuracy, in future comparative studies of HS recordings of oscillating vocal folds homogeneous frequencies should be taken into account during examination.
Biomechanical modeling of laryngeal dynamics Dollinger, M.; Anxiong Yang; Stingl, M. ...
2008 First International Symposium on Applied Sciences on Biomedical and Communication Technologies,
2008-Oct.
Conference Proceeding
Interferences in the laryngeal area based on anatomical alterations or disturbances being only visible during vocal fold oscillations yield hoarseness. Most often, asymmetries caused by the vibrating ...vocal folds are the origin for this hoarseness. This work presents an enhancement of biomechanical models to simulate three dimensional vocal fold vibrations. The model consists of coupled mass-spring elements similar to Ishizaka and Flanagan (1972). The new model simulates the vibrations at 25 different positions for each vocal fold. The masses are arranged at 5 positions in longitudinal direction by 5 positions in vertical direction. The masses are capable to move in all three physical directions to better simulate human laryngeal vocal fold vibrations. The physical parameters applied in the model were chosen to visually fit real three-dimensional excised human vocal fold dynamics. Exemplarily, a symmetric dynamics simulation will be given.
For the diagnosis of pathological voices it is of particular importance to examine the dynamic properties of the underlying vocal fold (VF) movements occurring at a fundamental frequency of 100–300 ...Hz. To this end, a patient’s laryngeal oscillation patterns are captured with state-of-the-art endoscopic high-speed (HS) camera systems capable of recording 4000 frames/second. To date the clinical analysis of these HS videos is commonly performed in a subjective manner via slow-motion playback. Hence, the resulting diagnoses are inherently error-prone, exhibiting high inter-rater variability. In this paper an objective method for overcoming this drawback is presented which employs a quantitative description and classification approach based on a novel image analysis strategy called Phonovibrography. By extracting the relevant VF movement information from HS videos the spatio-temporal patterns of laryngeal activity are captured using a set of specialized features. As reference for performance, conventional voice analysis features are also computed. The derived features are analyzed with different machine learning (ML) algorithms regarding clinically meaningful classification tasks. The applicability of the approach is demonstrated using a clinical data set comprising individuals with normophonic and paralytic voices. The results indicate that the presented approach holds a lot of promise for providing reliable diagnosis support in the future.
A facile and large-scale fluidized bed reaction route was introduced for the first time to prepare crystalline embedded amorphous silicon nanoparticles with an average size of 50 nm as anode ...materials for lithium-ion batteries. By increasing the operating potential to control the electrochemically active degree, the resulting sample showed excellent cycle stability with a high capacity retention of 94.7% after 200 cycles at 1 A g-1 in the voltage range of 0.12-2.00 V.
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