Bio-Medical Materials and Engineering - Volume Pre-press, issue Pre-press
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Bio-Medical Materials and Engineering is to promote the welfare of humans and to help them keep healthy. This international journal is an interdisciplinary journal that publishes original research papers, review articles and brief notes on materials and engineering for biological and medical systems.
Articles in this peer-reviewed journal cover a wide range of topics, including, but not limited to: Engineering as applied to improving diagnosis, therapy, and prevention of disease and injury, and better substitutes for damaged or disabled human organs; Studies of biomaterial interactions with the human body, bio-compatibility, interfacial and interaction problems; Biomechanical behavior under biological and/or medical conditions; Mechanical and biological properties of membrane biomaterials; Cellular and tissue engineering, physiological, biophysical, biochemical bioengineering aspects; Implant failure fields and degradation of implants. Biomimetics engineering and materials including system analysis as supporter for aged people and as rehabilitation; Bioengineering and materials technology as applied to the decontamination against environmental problems; Biosensors, bioreactors, bioprocess instrumentation and control system; Application to food engineering; Standardization problems on biomaterials and related products; Assessment of reliability and safety of biomedical materials and man-machine systems; and Product liability of biomaterials and related products.
Abstract: BACKGROUND: Accelerated hydrothermal aging has long been one of the most widely accepted quality control tests for simulating low-temperature degradation (LTD) in zirconia-containing implants used in total hip arthroplasty (THA). However, it is still unclear how much consistency there is between the experimental prediction from the internationally-standardized tests and the actual measurements from surgically-removed implants after a long period of implantation. This question is fundamentally related to a lack of understanding of mechanical/tribological contribution to the in-vivo LTD kinetics. OBJECTIVE: The main purposes of this study are to validate the clinical relevance of standardized accelerated aging by…comparing between artificially-aged and in-vivo used prostheses, and to clarify the long-term effects of in-vivo mechanics/tribology on the LTD progression upon service in the body environment. METHODS: Surface magnitudes of phase transformation and residual stress in zirconia femoral head retrievals (13.1–18.4 yrs) were evaluated by using confocal Raman microspectroscopy. RESULTS: The long-term aging behavior in unworn head surface was in agreement with the experimental prediction estimated as 1h aging at 134 °C = 4 years in-vivo . However, the current aging protocols based on ASTM and ISO criteria were not accurately predictive for the worn surfaces, and the tribologically-induced phase transformation and tensile stress were up to 6.5-times and 3.3-times higher than the environmentally-induced ones. CONCLUSION: Our study suggests that wear/scratching, frictional heating, tribochemical reactions, and metal transfer may become far more intense triggers to phase transformation than the mere exposure to body fluid.
Abstract: BACKGROUND: Snoring source analysis is essential for an appropriate surgical decision for both simple snorers and obstructive sleep apnea/hypopnea syndrome (OSAHS) patients. OBJECTIVE: As snoring sounds carry significant information about tissue vibrations within the upper airway, a new feature entitled compressed histogram of oriented gradients (CHOG) is proposed to recognize vibration patterns of the snoring source acoustically by compressing histogram of oriented gradients (HOG) descriptors via the multilinear principal component analysis (MPCA) algorithm. METHODS: Each vibration pattern corresponds to a sole or combinatorial vibration among the four upper airway soft tissues of soft palate, lateral pharyngeal…wall, tongue base, and epiglottis. 1037 snoring events from noncontact sound recordings of 76 simple snorers or OSAHS patients during drug-induced sleep endoscopy (DISE) were evaluated. RESULTS: With a support vector machine (SVM) as the classifier, the proposed CHOG achieved a recognition accuracy of 89.8% for the seven observable vibration patterns of the snoring source categorized in our most recent work. CONCLUSION: The CHOG outperforms other single features widely used for acoustic analysis of sole vibration site.
Keywords: Snoring source analysis, vibration pattern recognition, compressed histogram of oriented gradients, multilinear principal component analysis
Abstract: Neurological disorders are one of the significant problems of the nervous system that affect essential functions of the human brain and spinal cord. Monitoring brain activity through electroencephalography (EEG) has become an important tool in the diagnosis of brain disorders. The robust automatic classification of EEG signals is an important step toward detecting any brain disorder in its earlier stages before status deterioration. Motivated by the computation capabilities of natural evolution strategies (NES), this paper introduces an effective automatic classification approach referred to as natural evolution optimized deep learning (NEDL). The proposed classifier that is included in a signal processing…chain comprises of other state-of-the-art methods in a single framework for EEG classification. Initially, the EEG signal is decomposed into a number of sub-bands by applying wavelet transform where a number of spectral and statistical features are extracted. These extracted features are examined using the approach of artificial bee colony to optimally select the best features. Finally, the selected features are processed using the proposed NEDL classifier, after which the proposed approach is evaluated using two benchmark datasets that address epilepsy disease and motor imagery. Several experiments are conducted where the proposed approach outperforms other deep learning models along with existing approaches.
Keywords: Deep learning, natural evolution strategies, artificial bee colony, L1- principal component analysis, neurological disorder, EEG signal classification
Abstract: Background: There are no studies on the scoliotic population in which lateral abdominal muscle (LAM) was measured. Objective: The aim of the study was to deliver the first results on LAM elasticity assessed by shear wave elastography (SWE) in right-side and left-side thoracolumbar scoliosis patients. Method: Twelve patients (mean age 12.25) with thoracolumbar scoliosis were included in the study. Muscle thickness and SWE of the obliquus external (OE), obliquus internal, and transversus abdominis (TrA) were measured with an ultrasound scanner. Measurements were taken at rest and during isometric contraction. Results: An analysis showed that…in right-side scoliosis, the OE muscle on the convex side was stiffer by 7.25 kPa compared to the concave side. The OE muscle on the convex side in right-side scoliosis was also stiffer by 11.6 kPa compared to the convex side in left-side scoliosis. In left-side scoliosis, the TrA muscle on the concave side was stiffer by 7.84 kPa compared to the convex side. Conclusion: Changes in LAM elasticity of thoracolumbar scoliosis were observed. A different pattern of LAM stiffness in different curve directions may be expected. OE and TrA shear moduli are the most sensitive to change in adolescent spinal deformation.