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This study aims to demonstrate the feasibility of using a new wireless electroencephalography (EEG)-electromyography (EMG) wearable approach to generate characteristic EEG-EMG mixed patterns with mouth movements in order to detect distinct movement patterns for severe speech impairments. This paper describes a method for detecting mouth movement based on a new signal processing technology suitable for sensor integration and machine learning applications. This paper examines the relationship between the mouth motion and the brainwave in an effort to develop nonverbal interfacing for people who have lost the ability to communicate, such as people with paralysis. A set of experiments were conducted to assess the efficacy of the proposed method for feature selection. It was determined that the classification of mouth movements was meaningful. EEG-EMG signals were also collected during silent mouthing of phonemes. A few-shot neural network was trained to classify the phonemes from the EEG-EMG signals, yielding classification accuracy of 95%. This technique in data collection and processing bioelectrical signals for phoneme recognition proves a promising avenue for future communication aids.

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Obtaining the mechanical properties of soft tissues is critical in many medical fields, such as regenerative medicine and surgical simulation training. Although various tissue-characterization methods have been developed, such as AFM, indentation, and elastography, there remain some limitations on their accuracy and validity for measuring small and fragile soft tissues. This paper presents a tensile testing technique to measure the mechanical properties of soft tissues directly and accurately. Tensile testing was chosen as the primary method because of its simple procedure and ability to derive mechanical properties without requiring many assumptions or complicated models. However, tensile testing on soft tissues presents challenges related to gripping the tissue sample without affecting its inherent properties, applying minuscule forces to the sample, and measuring the cross-section area and strain of the sample. To solve these issues, this study presents a sub-micro scale tensile testing system that uses a flexure mechanism and a novel 3D-printed sample holder for gripping the tissue samples. The system also measures tested samples' cross-section area and strain using two high-resolution cameras. The system was validated by testing standard materials and used to characterize the elastic modulus, yield stress, and yield strain of lung tissue slices from six different mice. The results from the validation tests showed a less than 2.5% error for elastic modulus values measured using the tensile tester. At the same time, results from the mice lung tissue measurements revealed qualitative findings that closely matched those seen in the literature and displayed low coefficient of variation values, demonstrating the high repeatability of the system.

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The characterization of soft tissues remains a vital need for various bioengineering and medical fields. Developing areas such as regenerative medicine, robot-aided surgery, and surgical simulations all require accurate knowledge about the mechanical properties of soft tissues to replicate their mechanics. Mechanical properties can be characterized through several different characterization techniques such as atomic force microscopy, compression testing, and tensile testing. However, many of these methods contain considerable differences in ability to accurately characterize the mechanical properties of soft tissues. As a result of these variations, there are often discrepancies in the reported values for numerous studies. This paper reviews common characterization methods that have been applied to obtain the mechanical properties of soft tissues and highlights their advantages as well as disadvantages. The limitations, accuracies, repeatability, in-vivo testing capability, and types of properties measurable for each method are also discussed.

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In optical metrology, fringe projection and moire techniques have been widely used to measure the topography of objects. We can combine the advantages of the two techniques by applying a configuration of simultaneous dual projection in the fringe projection technique, which generates a superimposed fringe pattern containing a moire pattern that is phase modulated according to the topography. In this work, we present an analytic and comparative study of three methods to demodulate the phase of the moire pattern: the spatial, spatial-temporal, and temporal methods. Those methods consist of two steps: first, the moire pattern is extracted from the superimposed fringe pattern; next, the phase of the moire pattern is demodulated. The analytical results show that the resulting phase map has double phase sensitivity compared to that of the classical fringe projection technique. Experimental and numeric results prove the feasibility of this technique.

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PURPOSE: To determine expression levels of annexin I (lipocortin I) in patient-matched benign prostatic epithelium (BPE), high-grade prostatic intraepithelial neoplasia (HGPIN), and prostate cancer (CaP). EXPERIMETNAL DESIGN: Annexin I protein expression was examined with a standard immunohistochemical protocol in 69 radical prostatectomy specimens, 45 of which also contained HGPIN. Immunostained sections were scored visually by a genitourinary pathologist and mean optical density was measured with digital image analysis. Real-time fluorescence quantitative PCR was used to measure expression levels of annexin I mRNA in patient-matched CaP and BPE from 14 snap-frozen, radical prostatectomy specimens. RESULTS: Annexin I protein expression was reduced in 91% (41/45) of HGPIN lesions and 94% (65/69) of invasive CaP compared with BPE in the same histological section when assessed visually. Mean absorbance was reduced significantly (P < 0.05) in 97.7% (44/45) of HGPIN lesions and 98.5% (68/69) of CaP glands compared with BPE. In 79% of cases (11/14; P < 0.05), mRNA expression was reduced in CaP as compared with patient-matched BPE. Annexin I mRNA and protein expression levels did not correlate with Gleason grade, pathological stage, or race. CONCLUSIONS: Down-regulation of annexin I protein expression is a common finding in HGPIN and CaP, suggesting that annexin I dysregulation may be an important early event in CaP initiation. Because mRNA levels are reduced in a high proportion of cases, one likely mechanism for annexin I dysregulation occurs at the level of gene transcription. Results of these studies support a valuable role for a molecular profiling approach to CaP research.

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