Showing papers in "Biomedical Engineering: Applications, Basis and Communications in 2015"
TL;DR: RLS method is much more effective and powerful than other methods in ECG noise cancellation, and even better than UNANR, and the introduced optimized method with adaptive threshold value would have great potential in biomedical application of signal processing and other fields.
Abstract: The electrocardiogram (ECG) is generally used for the diagnosis of cardiovascular diseases. In many of the biomedical applications, it is necessary to remove the noise from ECG recordings. Several adaptive filter structures have been proposed for noise cancellation. Compared to the least mean square (LMS) method, the unbiased and normalized adaptive noise reduction (UNANR) algorithm has better performance, as mentioned in previous investigations. In this paper, we review various kinds of ECG noise reduction algorithms. To provide a detailed and fair comparison, all normalized LMS (NLMS), Block LMS (BLMS), recursive least squares (RLS) and UNANR algorithms are implemented and their performance have been assessed using the same dataset and compared to different state-of-the-art approaches. Then, the performance analysis of all five algorithms is presented and compared in term of mean squared error (MSE), computational complexity and stability. The obtained results revealed that RLS method is much more effective and powerful than other methods in ECG noise cancellation, and even better than UNANR. Then, in order to reach the best performance of the mentioned filter and also, to minimize the output signal error, the optimized parameters of the algorithm were defined and results were investigated. The obtained outcomes show that the best Lambda (λ) occurs between 0.05 and 0.9, so that the convergence rate of the optimized RLS filter is faster than others. It not only decreases the noise, but also the ECG waveform is better conserved. Furthermore, the introduced optimized method with adaptive threshold value would have great potential in biomedical application of signal processing and other fields.
26 citations
TL;DR: The objective of the present study is to investigate the combined effects of aneurysm and curvature on flow characteristics in S-shaped bends with sweep angle of 90° at Reynolds number of 900 and to study the fluid mechanics of blood flow in a curved artery with abnormal aortic.
Abstract: Abdominal aortic aneurysm (AAA) is a degenerative disease defined as the abnormal ballooning of the abdominal aorta (AA) wall which is usually caused by atherosclerosis. The aneurysm grows larger and eventually ruptures if it is not diagnosed and treated. Aneurysms occur mostly in the aorta, the main artery of the chest and abdomen. The aorta carries blood flow from the heart to all parts of the body, including the vital organs, the legs, and feet. The objective of the present study is to investigate the combined effects of aneurysm and curvature on flow characteristics in S-shaped bends with sweep angle of 90° at Reynolds number of 900. The fluid mechanics of blood flow in a curved artery with abnormal aortic is studied through a mathematical analysis and employing Cosmos flow simulation. Blood is modeled as an incompressible non-Newtonian fluid and the flow is assumed to be steady and laminar. Hemodynamic characteristics are analyzed. Grid independence is tested on three successively refined meshes. It is observed that the abrupt expansion induced by AAA results in an immensely disturbed regime. The results may have implications not only for understanding the mechanical behavior of the blood flow inside an aneurysm artery but also for investigating the mechanical behavior of the blood flow in different arterial diseases, such as atherosclerosis.
15 citations
TL;DR: This work compared extensional and shear stress flow fields within the contraction of a short capillary with sharp versus tapered entrances to support extensional stress as the primary mechanical force involved in hemolysis.
Abstract: Artificial prostheses create non-physiologic flow conditions with stress forces that may induce blood cell damage, particularly hemolysis. Earlier computational fluid dynamics (CFD) prediction models based on a quantified power model showed significant discrepancies with actual hemolysis experiments. These models used the premise that shear stresses act as the primary force behind hemolysis. However, additional studies have suggested that extensional stresses play a more substantial role than previously thought and should be taken into account in hemolysis models. We compared extensional and shear stress flow fields within the contraction of a short capillary with sharp versus tapered entrances. The flow field was calculated with CFD to determine stress values, and hemolysis experiments with porcine red blood cells were performed to correlate the effects of extensional and shear stress on hemolysis. Our results support extensional stress as the primary mechanical force involved in hemolysis, with a threshold value of 1000 Pa under exposure time less than 0.060 ms.
14 citations
TL;DR: The present research paper undertakes the study of the different techniques used for reducing and enlarging images, whose combination will be a new protocol (REPro) for the transmission of medical images.
Abstract: Despite their frequent use in our daily life, the expansion and reduction of images are among the least studied research areas in the literature. That is why the present research paper undertakes the study of the different techniques used for reducing and enlarging images, whose combination will be a new protocol (REPro) for the transmission of medical images. The proposed approach consists in reducing the image when sent and enlarging it when received, which allows for consumption saving of the bandwidth allocated to the diagnostics service. To do so, the performance of our new protocol was tested for the transfer of scars images (color images) and ultrasound images (grayscale images) in terms of the resemblance between the original image, on one hand, and the reduced and then enlarged one, on the other hand.
11 citations
TL;DR: The results show that HRV synchronization is directly related to sleep respiratory signals.
Abstract: In the present study, "obstructive sleep apnea (OSA) patients" and "non-OSA patients" were classified into two groups using with two synchronic heart rate variability (HRV) series obtained from electrocardiography (ECG) and photoplethysmography (PPG) signals. A linear synchronization method called cross power spectrum density (CPSD), commonly used on HRV series, was performed to obtain high-quality signal features to discriminate OSA from controls. To classify simultaneous sleep ECG and PPG signals recorded from OSA and non-OSA patients, various feed forward neural network (FFNN) architectures are used and mean relative absolute error (MRAE) is applied on FFNN results to show affectivities of developed algorithm. The FFNN architectures were trained with various numbers of neurons and hidden layers. The results show that HRV synchronization is directly related to sleep respiratory signals. The CPSD of the HRV series can confirm the clinical diagnosis; both groups determined by an expert physician can be 99...
10 citations
TL;DR: In this paper, the authors performed an experimental study to evaluate the linear elastic and nonlinear hyperelastic mechanical properties of the tennis ball under compressive loading, which revealed the mean elastic modulus, maximum stress, and strain of 336.69 kPa, 410.15 kPa and 66% for the tennis balls, respectively.
Abstract: Tennis is almost a newly born sport (1859) that can be played individually against a single opponent (singles) or between two teams of two players each, namely doubles. Materially, tennis balls were made of cloth strips stitched together from thread. They have also been made of hollow rubber with a felt coating appearing in different colors from traditionally white to yellow in the recent years to permit their visibility. Although the most common injuries associated with tennis have been reported to be related to rotator cuff, elbow, wrist, anterior knee pain, and ankle, the injury that a tennis ball can cause, for example, for eye is still not clear. However, as the tennis ball can reach to a speed of 260 km/h, it seems vital to understand its mechanical properties to have a deep insight into the injury that can happen during playing. Therefore, this study aimed to perform an experimental study to evaluate the linear elastic and nonlinear hyperelastic mechanical properties of the tennis ball under compressive loading. To do this, 40 numbers of approved tennis balls by international tennis federation (ITF) were prepared and subjected to a series of compressive loadings. The strain of the balls was measured via a pair of CCD cameras using digital image correlation (DIC) technique. The results revealed the mean elastic modulus, maximum stress, and strain of 336.69 kPa, 410.15 kPa, and 66%, for the tennis balls, respectively. The nonlinear mechanical behavior of the tennis balls were also computationally investigated through a hyperelastic material model, namely Ogden. Finally, a finite element (FE) model was executed to verify the hyperelastic data with that of experimental and, interestingly, the numerical data were in good agreement with experimental ones. The findings of this study may have implications not only for understanding the compressive mechanical properties of the tennis ball, but also for investigating the injury that can occur in the human body by tennis ball, especially the eye.
9 citations
TL;DR: The results indicated that the rigid instrumentation resulted in greater fixation stability but also a greater risk of adjacent segment degeneration and implant failure, and the dynamic instrumentation was closer to that of the intact spine model compared with the rigid and semi-rigid instrumentations.
Abstract: Fusion has been the gold standard treatment for treating lumbar degenerative disc disease. Many clinical studies have demonstrated that adjacent segment degeneration was observed in patients over time. Various instrumentations of pedicle screw-based stabilization systems have been investigated using numerical approaches. However, numerical models developed in the past were simplified to reduce computational time. The aim of this study was to evaluate and to compare the biomechanical performance of rigid, semi-rigid, and dynamic posterior instrumentations using a more realistic numerical model. Three-dimensional nonlinear finite element models of the T11-S1 multilevel spine with various posterior instrumentations were developed. The intersegmental rotation, the maximum disc stress, and the maximum implant stress were calculated. The results indicated that the rigid instrumentation resulted in greater fixation stability but also a greater risk of adjacent segment degeneration and implant failure. The biomechanical performance of the dynamic instrumentation was closer to that of the intact spine model compared with the rigid and semi-rigid instrumentations. The results of this study could help surgeons understand the biomechanical characteristics of different posterior instrumentations for the treatment of lumbar degenerative disc diseases.
8 citations
TL;DR: This work focuses on the absorption characteristics of hemoglobin derivatives in the wavelength range of 520–600 nm to give the best estimates of SmO2 to help improve optical monitoring of mean blood oxygen saturation.
Abstract: We present the use of Extended Modified Lambert–Beer model for optical monitoring of mean blood oxygen saturation (SmO2) via a fitting procedure. This work focuses on the absorption characteristics of hemoglobin derivatives in the wavelength range of 520–600 nm to give the best estimates of SmO2. The study of the feasibility of applying this analytic method to skin oximetry is via spectroscopy data collected from fingertips of four healthy volunteers both at rest and during arterial blood occlusion condition. The results revealed a decrease in the mean of mean and standard deviation of SmO2 value of fingertips from 94.5 ± 2.19% when volunteers were at rest to 56.76 ± 5.8% during the arterial blood occlusion measurement. The larger variation in the value estimated for blood occlusion condition could be a result of differences in volunteers' physical fitness and hypertension status. These estimated SmO2 values agreed reasonably well with the value reported in most of the previous studies. This work concluded that the proposed technique can potentially be used as a complementary technique to clinical assessment of skin grafts and burnt skin.
8 citations
TL;DR: In this article, the effect of sidebarbone spacing on the fracture line under axial loading was analyzed using AnsysWorkbench software, and the von-Mises stress and strain values were calculated to understand this effect according to the vonMises criteria.
Abstract: Many unwanted traumas occur in daily life, the result of which may be intertrochanteric fractures in the musculoskeletal system. An intertrochanteric femoral fracture is a serious trauma which can lead to pneumonia, pulmonary embolism or death. Therefore, accurate and stable fixation of these fractures is necessary. Schanz screws with a pertrochanteric fixator body are used for the stabilization of intertrochanteric fractures. The stability of fractures created by external fixators is dependent on the frame and bone interaction. The distance between the fixator body and the bone, called "sidebar-bone spacing", is one of the most important aspects of fracture stability. The primary objective in the treatment of these fractures is to maintain the stability of the fracture in the reduction position to allow early mobilization. In this study, an intertrochanteric femoral fracture was fixed with a pertrochanteric fixator, then the effect of sidebar-bone spacing on the fracture line under axial loading was analyzed using AnsysWorkbench software. Stress and strain values on the fracture line and schanz screws were calculated to understand this effect according to the von-Mises criteria. The sidebar-bone spacing was selected as 8, 6 and 4 cm. The von-Mises stress value on the fracture line decreased as the distance between the fixator body and the bone decreased, although strain values increased. In conclusion, decreasing the sidebar-bone spacing in the pertrochanteric fixator used on hip fractures provides stronger stabilization, and demonstrates safer axial loading.
6 citations
TL;DR: This preliminary study indicates that FIM in combination with conventional spirometry could be used to detect localized ventilation defects.
Abstract: Conventional spirometry gives information on the overall ventilation of a person's lung; it cannot detect localized disorders in ventilation as occurring in pulmonary edema, pneumonia, tumor, TB, etc. Here we propose a new technique involving the recently developed focused impedance method (FIM) in combination with conventional spirometry to detect localized lung ventilation disorders. Electrical impedance of lung tissue changes as a function of air content and FIM provides a measurement of localized electrical impedance with sensitivity down to reasonable depths inside the body using a few surface electrodes; here we used a six-electrode version. At least four quadrants of the lungs in the frontal plane can be separately measured using a hand-held probe with spring backed skin surface electrodes. Firstly, spatial sensitivity distribution of the six-electrode FIM was obtained using finite element simulation which verified the focusing effect and its depth sensitivity. Percent change in impedance between maximum inspiration and expiration were measured at four quadrants of the chest of a healthy male subject giving four different values; that at the lower right quadrant was found to be the maximum, as also expected based on anatomy. Changes in impedance at this quadrant of the same subject were found to vary proportionately with exhaled air volumes, measured using a bellows-type spirometer. Similar FIM measurements at lower right lung of seven healthy subjects were found to be almost proportional (R2 = 0.7) to the total exhaled air volumes (vital capacity). This was the basis of the new technique. For a healthy individual, the ratio of the local impedance change to vital capacity (VC) will fall within a certain range for each of the four lung quadrants. A lower value at any quadrant would indicate disorder within that quadrant, while a larger value would indicate disorder in a region outside the particular quadrant. The FIM electrode probe can then be moved to take measurements at the other quadrants to locate the region of disorder. This preliminary study indicates that FIM in combination with conventional spirometry could be used to detect localized ventilation defects.
6 citations
TL;DR: Overall, both systems demonstrated an adequate ability to track dynamic motion and high intra-day and inter-day repeatability was demonstrated by both systems during the sit-to-stand task.
Abstract: Few studies have concurrently investigated the accuracy and repeatability of an optical and electromagnetic (EM) system during dynamic motion. The purposes of this study were to: (1) assess the accuracy of both an EM and optical system when compared to a gold standard and (2) to compare the intra- and inter-day repeatability during 3D kinematic motion of both systems. The gold standard used for accuracy assessment was a robot programmed to manipulate a carbonber beam through pre-dened motions within the capture volume of both systems at 30, 45 and 60� /s. A total of 12 healthy young adults were tested for intra- and inter-day repeatability of hip, knee and ankle joint angles during a sit-to-stand movement. Marker trajectories were captured using an 8-camera Motion Analysis system and a Polhemus Liberty system. Optical markers for both portions of the study were precisely marked to allow for digitization by the EM system, with collections taken at 120Hz. Accuracy and repeatability were assessed using the RMS error and coe±cient of multiple correlations (CMC), respectively. The optical system demonstrated a 1-2.5� lower RMS error in tracking the robot movements in the transverse and sagittal planes when compared to the EM system. However, it was possible that metal interference a®ected the accuracy of the EM system. High intra-day and inter-day repeatability was demonstrated by both systems during the sit-to-stand task. The optical system did dem- onstrate slightly higher CMC values for between day trials, though skin motion artifact might have a®ected the EM system to a greater extent. Overall, both systems demonstrated an adequate ability to track dynamic motion.
TL;DR: A real-time extended Kalman filtering framework for extracting motion and electromyography artifacts from a single-channel ECG in wearable systems as different from other offline studies is presented.
Abstract: In this paper, a prototype of wearable and wireless electrocardiography (ECG) monitoring system is developed and implemented on DSP and PDA. We present a real-time extended Kalman filtering framework for extracting motion and electromyography (EMG) artifacts from a single-channel ECG in wearable systems as different from other offline studies. Realized prototype is a good example for the usage of the Kalman filter in biomedical real-time system. The average SNR advancement of 9.1430 dB was achieved for denoising, which is average 1 dB more than the other methods such as MABWT, EKF2 by using MIT-BIH database. Additionally, the usability and performances of conductive textile electrodes were evaluated with disposable Ag–AgCl electrodes by using daily activities. A novel textile electrode gave approximately 25.23% better results compared to Ag–AgCl electrodes. Also, UDP, TCP and Web Socket communication protocols have been tested. UDP has been the fastest method for the ECG signal transferring from the patie...
TL;DR: This work proposes simplified PD models for warfarin dose-response relationship, motivated by ideas from control theory, and shows that all models have a similar predictive ability, but the simplified models are most parsimonious.
Abstract: Warfarin is a frequently used oral anticoagulant for long-term prevention and treatment of thromboembolic events. Due to its narrow therapeutic range and large inter-individual dose–response variability, it is highly desirable to personalize warfarin dosing. However, the complexity of the conventional kinetic-pharmacodynamic (K-PD) models hampers the development of the personalized dose management. To avert this challenge, we propose simplified PD models for warfarin dose-INR response relationship, which is motivated by ideas from control theory. The simplified models were further applied to longitudinal data of 37 patients undergoing anticoagulation treatment using the standard two-stage approach and then compared with the conventional K-PD models. Data analysis shows that all models have a similar predictive ability, but the simplified models are most parsimonious.
TL;DR: The performance of the computer-aided diagnosis (CAD) system for pulmonary nodule detection in computed tomography can be improved by combining multiple classifiers, and the majority voting method achieved higher performance levels than other combination methods and all individual classifiers.
Abstract: The purpose of this study was to investigate the usefulness of various classifier combination methods for improving the performance of a computer-aided diagnosis (CAD) system for pulmonary nodule detection in computed tomography (CT). We employed 85 CT scans with 110 nodules in the publicly available Lung Image Database Consortium (LIDC) dataset. We first applied our CAD scheme trained previously to the LIDC cases for identifying initial nodule candidates, and extracting 18 features for each nodule candidate. We used eight individual classifiers for false positives (FPs) reduction, including linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), Naive Bayes, simple logistic, artificial neural network (ANN) and support vector machines (SVMs) with three different kernels. Five classifier combination methods were then employed to integrate the outputs of the eight individual classifiers for improving detection performance. The five combination methods included two supervised (a likelihood ratio (LR) method and a probability method based on the output scores of the eight individual classifiers) and three unsupervised ones (the sum, the product and the majority voting of the output scores from the eight individual classifiers). Leave-one-case-out approach was employed to train and test individual classifiers and supervised combination methods. At a sensitivity of 80%, the numbers of FPs per CT scan for the eight individual classifiers were 6.1 for LDA, 19.9 for QDA, 10.8 for Naive Bayes, 8.4 for simple logistic, 8.6 for ANN, 23.7 for SVM-dot, 17.0 for SVM-poly, and 23.4 for SVM-anova; the numbers of FPs per CT scan for the five combination methods were 3.3 for the majority voting method, 5.0 for the sum, 4.6 for the product, 65.7 for the LR and 3.9 for the probability method. Compared to the best individual classifier, the majority voting method reduced 45% of FPs at 80% sensitivity. The performance of our CAD can be improved by combining multiple classifiers. The majority voting method achieved higher performance levels than other combination methods and all individual classifiers.
TL;DR: In this paper, a multidisciplinary project that applied the concept of reverse engineering using computer-aided design (CAD) tools to develop a three-dimensional printing (3DP)-based prosthetic socket for transtibial amputees by combining the concepts of patellar tendon-bearing (PTB) socket design principle and total surface bearing (TSB) sockets casting method.
Abstract: This paper describes a multidisciplinary project that applied the concept of reverse engineering using computer-aided design (CAD) tools to develop a three-dimensional printing (3DP)-based prosthetic socket for transtibial amputees by combining the concepts of patellar tendon-bearing (PTB) socket design principle and total surface-bearing (TSB) socket casting method. Using contemporary tools such as a handheld 3D scanner and an entry-level 3DP machine, together with an in-house prosthetic socket design system and a stump forming device, allowed us to fabricate prosthetic sockets with a consistent quality, and to shorten the learning process time-frame to fabricate them. The results of a case study of two participants demonstrated that the proposed CAD/3DP process of fabrication of transtibial sockets can be easily applied by an unskilled prosthetist to fabricate a socket with the required quality at the first fitting.
TL;DR: The findings demonstrated that different visual attention tasks lead to distinct modifications on obstacle crossing behaviors, similar to how different attention tasks affect motor function differently.
Abstract: Dual-task obstacle crossing gait paradigms are commonly adopted to examine how attentional demands are associated with sensory-motor processing during obstacle crossing. Various attention tasks have been used with mixed findings. This raises a question whether and how different attention tasks would affect motor function differently. Therefore, we examined and compared the effects of two visual attention tasks on obstacle crossing in healthy young adults. In the first experiment, 10 young adults responded to a 200ms visuospatial attention task during the approaching phase of obstacle crossing. In the second experiment, another 10 young adults responded to a visual Stroop task while approaching and crossing an obstacle. In both experiments, subjects completed an obstacle crossing only, a visual attention only, or a dual-task obstacle crossing condition in a random order. Dual-task costs were calculated for each visual attention task on the accuracy rates, toe-obstacle clearances and gait velocities. Two tripping incidences occurred only in the dual-task condition with visuospital attention task. Trailing toe-obstacle clearance reduced in the dual-task condition with visuospital attention task, but toe-obstacle clearances of both limbs increased in the dual-task condition with Stroop task. Gait velocities were not affected by the visuospatial attention task but were significantly reduced when concurrently performing the Stroop task. Dual-task costs were significantly different between two experiments on the gait velocity and toe clearances, but not on the accuracy rate. Our findings demonstrated that different visual attention tasks lead to distinct modifications on obstacle crossing behaviors.
TL;DR: The results show that the wavelet transform-fractal algorithm provides a new way to research human gastrointestinal activities and provides a reference for the diagnosis of gastrointestinal disease.
Abstract: Background: Gastrointestinal tract pressure information can reflect the dynamic disorder of gastrointestinal tract physiological and pathological changes, which is important in early diagnosis and treatment of gastrointestinal diseases. However, the rule of human gastrointestinal activities under his normal state is still not clear. The purpose of this paper is to find some rules of gastrointestinal activities using wavelet transform-fractal algorithm and provides a reference for the diagnosis of gastrointestinal disease. Methods: Data from 16 healthy subjects (13 men and three women) aged 18–35 years were analyzed. The key challenges on the data processing were filtering, features extraction, information evaluation and providing the reference conclusion which were resolved by employing wavelet decomposition, fractal algorithm etc. Key Results: About 94% of the subjects gastrointestinal activities follow the rule that the colonic activities in the digestive period are the roughest with the largest box dimension, closely followed by small intestinal activities with gastric activities ranking third with the smallest box dimension, which is never revealed before. Moreover, for the same person the gastrointestinal activities in the digestive period are rougher than in the inter-digestive period, as the box dimension of gastrointestinal activities in the digestive period is larger than in the inter-digestive period. Conclusions and Inferences: The results show that the wavelet transform-fractal algorithm provides a new way to research human gastrointestinal activities.
TL;DR: In this article, a finite element method (FEM) was used to analyze the biomechanical dental implant system behavior, determining von Mises stress distribution induced by functional loads, varying parameter as load direction and geometric characteristic of the implant (taper, length, abutment angulation, thread pitch and width pitch).
Abstract: Objective: To propose a methodology based on virtual simulation to assist in the design proposals of dental implants. Methods: The finite element method (FEM) was used to analyze the biomechanical dental implant system behavior, determining von Mises stress distribution induced by functional loads, varying parameter as load direction and geometric characteristic of the implant (taper, length, abutment angulation, thread pitch and width pitch). A final design was obtained by considering the parameters that showed improved performance. The estimated lifetime of the final design was calculated by reproducing in a virtual way the experimental fatigue test required by the ISO:14801 standards. Results: For all the studied cases, the maximum stresses were obtained in the connecting screw under oblique loads (OLs). The estimated lifetime for this critical part is at least 5 × 106 cycles, which meets the requirement of the ISO:14801. In bone tissue, the largest stresses were concentrated in cortical bone, in the zone surrounding the implant, in good agreement with previous reports. Conclusions: A dental implant design was obtained and validated through a simple and efficient methodology based on the application of numerical methods and computer simulations.
TL;DR: The overall hypothesis that different spine levels will have altered kinematics during various activities of daily living was supported and the first steps in understanding how the trunk responds on a daily basis and how those responses could lead to back pain are taken.
Abstract: Back pain can affect up to 65% of the American population and cost the health care system approximately fifty billion dollars each year. Due to the difficulty with recording spine/trunk movement, several methods and models exist. The myriad of methods and the need for understanding of spine/trunk motion has led to a lack in a ‘gold-standard’ of treatment for individuals with back pain. Therefore, the purpose of this study was to examine the effect of different activities of daily living on the kinematics of individual trunk segments in young adults to determine how common ambulatory tasks will alter trunk motion compared to level walking. Young healthy adults completed, in a random order, four activities of daily living: level walking, obstacle crossing, stair ascent and descent using a previously validated model. Subjects were outfitted with a full body marker set which included a segmented trunk. Multi-segmented trunk angles between the three inferior segments, sacrum to lower lumbar [SLL], lower lumbar to upper lumbar [LLUL] and upper lumbar to lower thorax [ULLT], were calculated and compared between tasks. Peak flexion angles, instance of peak angle and range of motion were analyzed. The overall hypothesis that different spine levels will have altered kinematics during various activities of daily living was supported. Stair descent had smaller peak flexion angles than obstacle crossing and stair ascent. The instance of peak angle were different depending on trunk angle and daily task. The most inferior trunk angle — Sacrum-to-Lower Lumbar — had the largest range of motion during all four tasks in all three (sagittal, frontal and transverse) planes of motion. This study was able to show how various activities of daily living produce different motions in the three inferior segments of a multi-segmented trunk method. The results of this study are the first steps in understanding how the trunk responds on a daily basis and how those responses could lead to back pain.
TL;DR: The proposed select visible-nipple mammograms (SVNM) algorithm with the ability of generalization has achieved a 99% selection rate for automatic clustering of nipples in a mammography database, besides automatically detecting the breast border and nipple positions in mammograms.
Abstract: Mammogram registration is an important preprocessing technique, which helps in finding asymmetrical regions in left and right breast. However, correct nipple position is the crucial key point of mammogram registration since it is the only consistent and stable landmark upon a mammogram. To locate the nipple coordinates accurately in mammogram images, this work improves previous algorithms such as maximum height of the breast border (MHBB) and proposes a novel method consisting of local spatial-maximum mean intensity (LSMMI), local maximum zero-crossing (LMZC) based on the second-order derivative, and a combined approach dependent on LSMMI and LMZC. The proposed method is tested on 413 mammogram images from MIAS and DDSM databases. Consequently, the mean Euclidean distance (MED) between the ground truth identified by the radiologist and the detected nipple position is 0.64 cm, within 1 cm of the gold standard, for estimating the proposed method. The experimental results hence indicate that our proposed method can detect the nipple positions more accurately than other previous methods. Furthermore, the proposed select visible-nipple mammograms (SVNM) algorithm with the ability of generalization has achieved a 99% selection rate for automatic clustering of nipples in a mammography database, besides automatically detecting the breast border and nipple positions in mammograms.
TL;DR: A three-dimensional model of the tibial component has been generated using computerized tomographies (CT) reconstruction and CAD software and stresses distribution at the interface bone-implant considering several combinations of stem lengths and stem inclinations have been analyzed.
Abstract: Mechanical loosening, instability, mechanical fractures and poor quality of bone are some factors that strongly influence the deterioration of knee implants. After a total knee replacement (TKR), proximal tibial bone suffers a resorption due to stress-shielding caused by the implant. The formation of weakening bone zones and loss of bone is one of the most clinical concerns. The aim of this work is to evaluate the geometry of the implant stem to improve the implant lifespan. A three-dimensional model of the tibial component has been generated using computerized tomographies (CT) reconstruction and CAD software. Stresses distribution at the interface bone-implant considering several combinations of stem lengths and stem inclinations have been analyzed using finite element analysis (FEA). High levels of resorption risk have been observed, when using different stem-lengths and varus inclination.
TL;DR: The concept of TIMI risk score is adopted, while adding every index of HRV measured when subjects are hospitalized to provide emergency physicians as a basis for an early prognosis and subsequently a better hospital-discharging assessment of patients with chest pain.
Abstract: According to statistics, up to 40% of emergency admissions are due to chest tightness or chest pain. However, merely based on the patient’s current symptoms such as chest pain, it is difficult for a physician to give an instant diagnosis as most cardiovascular diseases are chronic. To address this issue, it is necessary to provide a set of tools to indicate the patient’s status during hospitalization to help the physician in diagnosis. It is thus our primary objective to design and develop a wearable heart rate monitoring system and prediction tool that can measure the patient’s heart rate parameters, allow him/her to move around easily, and which also can effectively improve the medical personnel’s working efficiency. This research utilizes conductive filament to design textile to integrate electric circuit with clothing. Using a conductive vest and chest belt that can be worn comfortably, our system can continuously record patients’ physiological index parameters during their hospitalization. Physiological index parameters of multiple patients can then be transmitted wirelessly and recorded in a physician-end computer. At the end of their hospitalization, the patient’s original physiological indices together with the recorded heart rate variability (HRV) parameters can then be summarized to assess the risk score of their discharging from hospital. This paper adopts the concept of TIMI risk score, while adding every index of HRV measured when subjects are hospitalized. The risk score can hence be used to provide emergency physicians as a basis for an early prognosis and subsequently a better hospital-discharging assessment of patients with chest pain. The accuracy of the proposed prognosis has been verified with the 3-day and 30-day recall rate of the patients and the result has been shown to be promising for chest pain patients in emergency admission units.
TL;DR: The wearable heart rate monitoring system can be deemed as effective to provide a platform for measurement of group heart rates and for assessment of cardiorespiratory fitness.
Abstract: According to statistics in Taiwan, the proportion of students engaged in regular exercise has declined drastically with the increase in education level. This study thus aims to provide a platform for monitoring of group cardiorespiratory fitness to allow users such as teachers or coaches to easily monitor a group’s exercise condition, intensity and duration to increase exercise efficiency, promote exercise motivation and reduce exercise risk. Based on group measurement concept and wearable chest strap textiles integrated with heart rate monitoring devices, teachers or coaches can immediately acquire and display all heart rate information on a notebook computer together with synchronous field projection display. The acquired heart rate data can also be automatically recorded and analyzed to assist in assessing the physical fitness. Our proposed platform aims to monitor the cardiorespiratory fitness in group mainly for college students and young office worker. To validate the stability of our platform in the long term, we recruited the college students in a physical fitness class, 35 in total, as the subjects for long term observation. In the experiments the subjects are divided into “varsity group” and “sedentary group” according to whether they are with or without regular exercise habits. Subjects wearing chest straps were instructed to take the 3-minute Step Test and the 5-minute constant intensity exercise test. The results show that the “varsity group” has a lower resting heart rate (67.8±6.1bpm vs. 80.6±2.4bpm), a lower exercise heart rate (138.8±9.2bpm vs. 179.1±6.7bpm) and a lower mean heart rate (131.5±8.2bpm vs. 160.1±7.8bpm). The “Varsity group” also has a higher heart rate recovery percentage at the first minute (33.8±5.0% vs. 19.0±2.5%) and the second minute (43.9±5.1% vs. 30.4±2.7%). Moreover, all these indexes have a high correlation with the fitness index in the 3-minute Step Test, among which the percentage of heart rate recovery in the first minute shows the highest positive correlation (r=0.948, p<0.05). Our wearable heart rate monitoring system can thus be deemed as effective to provide a platform for measurement of group heart rates and for assessment of cardiorespiratory fitness.
TL;DR: An ex vivo heart lung perfusion system (EVHLPS) was designed and constructed in order to facilitate the study of hemodynamic and mechanical phenomena associated with the equine pulmonary vascular system.
Abstract: An ex vivo heart lung perfusion system (EVHLPS) was designed and constructed in order to facilitate the study of hemodynamic and mechanical phenomena associated with the equine pulmonary vascular system. Fresh en bloc heart and lung preparations collected from adult horses were placed in an enclosed chamber in normal anatomic orientation and perfused with isotonic phosphate buffered saline (PBS) via a closed loop, pulsatile perfusion system. Pulmonary artery (PA) pressure, left atrial pressure and perfusate temperature were regulated. Lungs were ventilated by static lung inflation and dynamic positive pressure ventilation (PPV). Instrumentation was introduced into the pulmonary arterial system via an instrument chamber incorporated in the perfusate flow piping upstream from the cranial vena cava. Key physiologic parameters (mean [SD]); PA flow (1.57 [0.61] L/min); systolic pressure (SAP) (42.5 [6.83] mmHg); diastolic pressure (DAP) (30.3 [3.86] mmHg); and perfusate temperature (37.1 [0.46]°C) were observed with en bloc heart and lung preparations (n = 5). PA pulse wave velocity (PWV) was found to vary from 1.72 to 12.50 m/s (n = 2) and appeared to have directly proportional relationships with mean arterial pressure (MAP) and distance within the PA.
TL;DR: The proposed methods outperform the existing state-of-the-art method for better classification in terms of sensitivity, specificity, and accuracy with greater consistence of ictal and interictal period of epilepsy for benchmark dataset from different brain locations.
Abstract: Electroencephalogram (EEG) is a record of ongoing electrical signal to represent the human brain activity. It has great potential for the diagnosis to treatment of mental disorder and brain diseases such as epileptic seizure. Features extraction and classification is a crucial task to detect the stage of ictal (i.e. seizure period) and interictal (i.e. period between seizures) EEG signals for the treatment and precaution of the patient. However, existing seizure and non-seizure feature extraction techniques are not good enough for the classification of ictal and interictal EEG signals considering their non-abrupt phenomena and inconsistency in different brain locations. In this paper, we present new approaches for feature extraction using high-frequency components from discrete cosine transformation (DCT) and intrinsic mode function (IMF) extracted from empirical mode decomposition (EMD). These features are then used as an input to least square-support vector machine (LV-SVM) to classify ictal and interictal EEG signals. Experimental results show that the proposed methods outperform the existing state-of-the-art method for better classification in terms of sensitivity, specificity, and accuracy with greater consistence of ictal and interictal period of epilepsy for benchmark dataset from different brain locations.
TL;DR: In this paper, a hybrid intelligent controller based on adaptive neural network (NN) predictive control has been developed for unexpected drug responses related to cardiac output and arterial pressure, and the hybrid intelligent controllers were compared with the previous PID or NN controller, and they realized robust and quick control regardless of unexpected responses.
Abstract: Regulating the dynamic responses to multiple therapeutic agents in cases of heart failure is difficult owing to time-variant changes in drug sensitivity and interaction. To address this problem, a multiple controller based on adaptive neural network (NN) predictive control has been developed for unexpected drug responses related to cardiac output and arterial pressure. However, the control speed may be slower than that in traditional controllers because of the real-time learning process for the NN. Moreover, a proportional-integral-derivative (PID) controller alone cannot automatically update the PID parameters during drug administration. This study, therefore, aimed to make hybrid intelligent (fuzzy or NN-based PID) controllers and to evaluate the control performance during multiple drug therapy in unexpected physiological responses of heart failure. The hybrid intelligent controllers were compared with the previous PID or NN controller, and they realized robust and quick control regardless of unexpected responses and acute disruptions.
TL;DR: Comparative analysis shows that edge-based active contours models are able to segment abdomen disease more accurately than region-based level set active contour model.
Abstract: Precise segmentation of abdomen diseases like tumor, cyst and stone are crucial in the design of a computer aided diagnostic system. The complexity of shapes and similarity of texture of disease with the surrounding tissues makes the segmentation of abdomen related diseases much more challenging. Thus, this paper is devoted to the segmentation of abdomen diseases using active contour models. The active contour models are formulated using the level-set method. Edge-based Distance Regularized Level Set Evolution (DRLSE) and region based Selective Binary and Gaussian Filtering Regularized Level Set (SBGFRLS) are used for segmentation of various abdomen diseases. These segmentation methods are applied on 60 CT images (20 images each of tumor, cyst and stone). Comparative analysis shows that edge-based active contour models are able to segment abdomen disease more accurately than region-based level set active contour model.
TL;DR: In this article, a failed compass hinge external fixator for fingers has been analyzed using finite element analysis (FEA) to investigate the principal stresses in the device under different loading conditions.
Abstract: A failed compass hinge external fixator for fingers has been analyzed. The device consists of polymer parts manufactured from polyetherimide. Finite element analysis (FEA) was used to investigate the principal stresses in the device under different loading conditions. Scanning electron microscopy (SEM) was used to investigate the fracture surfaces. The FEA showed that the maximum principal stress was greater than the fatigue strength of polyetherimide. The SEM fractographs confirm that failure was by brittle fatigue.
TL;DR: The proposed Human Computer Interactive system to assist individuals having low reading speed to increase their reading speed by the analysis of eye movements may also be used for training and assisting children with dyslexia or other similar reading disabilities children.
Abstract: Dyslexia is a well-known reading disorder that involves difficulty in fluent reading, decoding and processing of words despite adequate intelligence. It is common that the reading speed of dyslexic patients is lower than their normal counterparts, because of slow letter and word processing. Eye movements in dyslexic patients are significantly different from that of normal individuals, in terms of the presence of frequent fixations and stares in the former. This work proposes a Human Computer Interactive system to assist individuals having low reading speed to increase their reading speed by the analysis of eye movements. Eye movement data for different reading speeds is recorded using a laboratory developed Electrooculogram acquisition system. From the data, Adaptive Autoregressive (AAR) parameters, Band Power Estimates and Wavelet Coefficients are extracted as signal features. Reading speeds are classified using different pattern classifiers from which an average accuracy of 94.67% over all classes and participants is obtained using Radial Basis Function (RBF) Support Vector Machine (SVM) Tree classifier and AAR Parameters as features. Friedman test is done to select the best classifier. The trained classifier is used to recognize the reading speeds of a set of new normal individuals. If the reading speeds are less than a preset threshold, that individual is trained repeatedly for 10 days for improvement. An improvement of reading speed is observed by the decrease in the misclassification rate from 45.1% to 9.92% in 10 days for the fastest speed (1 sentence/2 s) over all the subjects. This work is carried out on healthy individuals. However, the results reveal that the proposed system may also be used for training and assisting children with dyslexia or other similar reading disabilities children.
TL;DR: This method is not meant to replace the clinician but can assist him for his diagnosis and reinforce his decision and is compared with those obtained in other studies for the same dataset.
Abstract: Wavelet transform decomposition of electroencephalogram (EEG) signals has been widely used for the analysis and detection of epileptic seizure of patients. However, the classification of EEG signals is still challenging because of high nonstationarity and high dimensionality. The aim of this work is an automatic classification of the EEG recordings by using statistical features extraction and support vector machine. From a real database, two sets of EEG signals are used: EEG recorded from a healthy person and from an epileptic person during epileptic seizures. Three important statistical features are computed at different sub-bands discrete wavelet and wavelet packet decomposition of EEG recordings. In this study, to select the best wavelet for our application, five wavelet basis functions are considered for processing EEG signals. After reducing the dimension of the obtained data by linear discriminant analysis and principal component analysis (PCA), feature vectors are used to model and to train the efficient support vector machine classifier. In order to show the efficiency of this approach, the statistical classification performances are evaluated, and a rate of 100% for the best classification accuracy is obtained and is compared with those obtained in other studies for the same dataset. However, this method is not meant to replace the clinician but can assist him for his diagnosis and reinforce his decision.