Journal of Mechanics in Medicine and Biology

Diabetic neuropathy is one of the physical complications of diabetes mellitus (DM) patients with a long history of diabetes. An electromyography (EMG)-based assessment may be very useful for the management of diabetic neuropathy. In the present study, we aimed to summarize all of the findings and recommendations obtained from previous studies that investigated the application of EMG to the assessment of diabetic neuropathy. An extensive search of the prominent electronic databases PubMed, Google Scholar and Scopus was performed to evaluate the following areas: (i) what are the muscles to be evaluated by EMG for neuropathy assessment, (ii) what type of EMG methodologies have been used and (iii) what recommendation can be made for neuropathy detection. The major findings are summarized as follows: (i) very few studies have analyzed the correlation of the EMG signals acquired from peripheral muscles affected in neuropathy with those obtained with non-neuropathic complications, such as ankle sprain; (ii) EMG has been applied for the detection of diabetic neuropathy more than diabetes treatment; and (iii) neuropathy detection using an EMG-based assessment were mainly performed for type 2 DM patients aged at least 50 years.

Stress incontinence occurs due to the inability to control an urge to urinate, which affects the quality of daily life. Although there is an existing therapeutics with polymer mesh tape, it is hard to fix around the urethra to restore the function of the pubourethral ligament. Therefore, in this research, an infra-obturator tension (IOT) sling was introduced to minimize the mobility of the bladder and urethra against intra-abdominal pressure. To verify the IOT performance, two different hypotheses were formulated: The hardness and volume of the IOT support the urethra and help prevent it from deforming by intra-abdominal pressure. The rotatory motion of the IOT can bend the urethra at the contact point and help restore the function of pubourethral ligament to increase vaginal tension. For the first hypothesis, a finite element simulation was conducted using three-dimensional geometrical model obtained by the computed tomography images of patients. For the second hypothesis, surgeons performed an IOT insertion operation and analyzed the sling rotation from the patients’ CT images (mean: 21^∘). From the results, the mobility of the urethra was decreased because of IOT insertion. The mobility was also decreased because of the subsequent fibrotic changes from the encapsulation of the IOT.

Electrocardiogram (ECG) signals containing very important information about the cardiac are one of the most common tools for physicians in the diagnosis of various types of cardiac diseases. Low accuracy in positioning, limitation of time accuracy, the similarity of signals between some diseases and normal signals and probability of missing some aspect of data are the defect aspects of this method. Importance of cardiac signals and defects of current methods in diagnosis show the need of substituting a new method to show the activity of cardiac. One of the most dangerous defections is ischemia, which corrects and on time diagnose could avoid the latter effect of it. Each of common methods for diagnosis of this illness has their own advantages and disadvantages. In this paper, we consider describing a non-invasive method for ischemic episode detection based on mapping of ECG signals. With this method, we can present the signals with virtual colors and facilitate the diagnosis of ischemic disease. So, a new method of 12-lead cardiac presentation is described that in fact present the 12-lead signals in two images. The result of this paper will present the indicators of sensitivity, specificity and accuracy in the context of disease diagnosis. This paper proposed a novel ECG imaging algorithm for classifying the normal and ischemic signals and 95.35% specificity, 96.79% sensitivity and 95.76% accuracy were achieved which are very much promising compared to the other methods and doctor’s accuracy.

Medical catheters are widely used in various medical procedures, such as diagnostics, biopsies and air change. A desirable catheter needs to be flexible for low discomfort, and stiff in longitudinal direction for easy manipulation. Tubular braid is often employed as reinforcement structure for catheters, which plays an important role in the overall mechanical properties. Current tubular braids adopt identical braiding angles for all the yarns, resulting in limited longitudinal stiffness. In this paper, a novel hybrid braid with different braiding angles for the two sets of yarns is proposed and analyzed. Both experimental and numerical results show that the hybrid braid has a higher longitudinal stiffness than the uniform one due to the geometrical incompatibility generated by the hybrid braiding angles. The effects of design parameters are also investigated through a parametric study, and an increase of 418.3% is achieved in the optimum case. In addition, the bending flexibility of the hybrid braid is found to be comparable with the uniform one. The new structure shows great promise for engineering applications where high longitudinal stiffness is required.

Arrhythmia classification is useful during heart disease diagnosis. Although well-established for intra-patient diagnoses, inter-patient arrhythmia classification remains difficult. Most previous work has focused on the intra-patient condition and has not followed the Association for the Advancement of Medical Instrumentation (AAMI) standards. Here, we propose a novel system for arrhythmia classification based on multi-lead electrocardiogram (ECG) signals. The core of the design is that we fuse two types of deep learning features with some common traditional features and select discriminating features using a binary particle swarm optimization algorithm (BPSO). Then, the feature vector is classified using a weighted support vector machine (SVM) classifier. For a better generalization of the model and to draw fair comparisons, we carried out inter-patient experiments and followed the AAMI standards. We found that, when using common metrics aimed at multi-classification either macro- or micro-averaging, our system outperforms most other state-of-the-art methods.

In this paper, we propose an electrocardiogram (ECG) signal compression algorithm that is based on wavelet and a new modified set partitioning in hierarchical trees (SPIHT) algorithm. The proposed algorithm contains a preprocessing of the approximation subband before the coding step by mean removing. Three other modifications are also introduced to the SPIHT algorithm. The first one is a new initialization of the two lists of insignificant points (LIP) and insignificant sets (LIS), while the second is concerning the position of inserting new entries of type $A$ at the LIS, and in the last one, the redundancy in checking type $B$ entries in the original method was found and avoided. The new proposed coding algorithm is applied to ECG signal compression and the obtained numerical results on the MIT-BIH database show the efficient performances of the proposed SPIHT algorithm over the original method and other existing methods.

Diabetic ulcers can lead to infection and amputation. Using insole can help to reduce and prevent foot ulceration and amputation in a diabetic patient. The aim of this study was to analyze the effect of wearing an insole with different density on standing and walking plantar pressure distribution. Methods: A group of 10 diabetic patients participated in this one-grouped before-after trial. Plantar pressure distribution was measured during walking and standing. Repeated Measure was used to test differences. Results: Repeated measure test showed that use of insole decreased foot pressure while walking significantly ($P=0.023$). Pairwise comparison showed that wearing shoe insole with shore 30 decreased pressure compared to wearing shoe insole with shore 50 ($P=0.004$) and walking without insole respectively ($P=0.06$). Conclusion: The insole has more effect on plantar pressure during walking than standing, it also concluded that insole with shore 30 decreased pressure during walking more than that of the insole with shore 50. It could be said that patients who suffer from pain and discomfort on hind and forefoot may benefit insole with shore 30 to relieve from plantar pressure on the hindfoot and forefoot regions during standing and walking.

Flow-diverting stent is an ongoing embolization device to treat cerebral aneurysms, and it diverts the flow direction to reduce the flow velocity inside the aneurysmal sacs and promote the thrombus formation. However, its effect for aneurysm embolization is controversial. A hemodynamic-biomedical coupling model was constructed to describe the generation and transport of thrombin in arteries, and the model was applied to investigate the variation of thrombin concentration, which plays a key role in thrombus formation, in two patient-specific cerebral aneurysm models when they are treated with Pipeline flow diverting stents. It is observed from computational fluid dynamics simulations that thrombin concentration in the aneurysmal sac without collateral artery increases significantly after Pipeline implantation, however, it has hardly any variation in the aneurysmal sac without collateral artery or in the giant aneurysmal sac after Pipeline implantation. Therefore, we believe that single Pipeline is very effective to embolize a small aneurysm without collateral artery, but cannot embolize a giant aneurysm or a small aneurysm with a collateral artery on its sac effectively.

Ventricular tachycardia (VT) and ventricular fibrillation (VF) are the life-threatening ventricular arrhythmias that require treatment in an emergency. Detection of VT and VF at an early stage is crucial for achieving the success of the defibrillation treatment. Hence an automatic system using computer-aided diagnosis tool is helpful in detecting the ventricular arrhythmias in electrocardiogram (ECG) signal. In this paper, a discrete wavelet transform (DWT) was used to denoise and decompose the ECG signals into different consecutive frequency bands to reduce noise. The methodology was tested using ECG data from standard CU ventricular tachyarrhythmia database (CUDB) and MIT-BIH malignant ventricular ectopy database (VFDB) datasets of PhysioNet databases. A set of time-frequency features consists of temporal, spectral, and statistical were extracted and ranked by the correlation attribute evaluation with ranker search method in order to improve the accuracy of detection. The ranked features were classified for VT and VF conditions using support vector machine (SVM) and decision tree (C4.5) classifier. The proposed DWT based features yielded the average sensitivity of 98%, specificity of 99.32%, and accuracy of 99.23% using a decision tree (C4.5) classifier. These results were better than the SVM classifier having an average accuracy of 92.43%. The obtained results prove that using DWT based time-frequency features with decision tree (C4.5) classifier can be one of the best choices for clinicians for precise detection of ventricular arrhythmias.

We used the finite element method-based toolbox COMSOL Multiphysics to address the important question of biopolymer coronary stent mechanics. We evaluated the diameter of the stent, the immediate elastic recoil, the dogboning and the foreshortening during deployment while using an idealized model that took into account the presence of the balloon and the coronary artery wall (equivalent pressure hypothesis). We validated our model using the well-known mechanics of the Palmaz–Schatz metal stent and acquired new data concerning a poly-L-lactic acid (PLLA) stent and some other biodegradable co-polymer-based stents. The elastic recoil was relatively high (26.1% to 31.1% depending on the biopolymer used) when taking into account the presence of both the balloon and artery. The dogboning varied from 31% to 46% for the polymer stents and was 62% for the metal stent, suggesting that less arterial damage could be expected with biopolymer stents. Various strut thicknesses were tested for the PLLA stent (114, 180 and 250$\mu$m) and no significant improvement in elastic recoil was observed. We concluded that the stent geometry has a greater impact on the scaffolding role of the structure than the strut thickness, or even the mechanical properties of the stent.

Sleep deprivation has been reported to be a contributing factor for the epidemic of obesity. However, it is still largely unknown how sleep deprivation contributes to obesity at the transcriptional level. Here, we identified the significantly changed genes and pathways that may contribute to the sleep deprivation-induced obesity by analyzing two online datasets, including mouse obesity database and mouse sleep deprivation database. 298 differentially expressed genes (DEGs) were identified in high fat diet mice as compared to normal diet mice, while 541 DEGs were identified in mice with sleep deprivation when compared with mice with normal sleep. There are 12 common DEGs, such as Saa3 and Plin4, in both comparisons. And six of common DEGs were validated in other Gene Expression Omnibus (GEO) dataset. GO and KEGG pathway analyses revealed 19 common altered pathways, and most of them were metabolic processes, including steroid metabolic process, small molecule metabolic process and cholesterol metabolic process. Notably, we found that Aldoc, Cyp2b10, Nsdhl, Pcsk9, Saa3, Plin4 and Acss2 were involved in most of those altered pathways. Taken together, our study suggests that Saa3, Plin4, Aldoc, Cyp2b10, Nsdhl, Pcsk9 and Acss2 might be involved in sleep deprivation-induced obesity by regulating metabolic processes.

Delayed onset muscle soreness (DOMS) is a very common musculoskeletal problem in athletes involved in extreme competitions. The aim of this study is to compare the effect of diathermy, sham diathermy and massage on the knee proprioception of athletes treated for DOMS. Forty athletes were enrolled after the second day of a demanding ski mountaineering race. They were randomly assigned to four groups: no treatment $(n=10)$, massage $(n=10)$, diathermy $(n=10)$, and sham diathermy $(n=10)$. The knee reposition error was measured after the treatments in order to assess knee proprioception. Significant differences between the diathermy and sham diathermy groups were found ($p=0.01$) with an absolute effect size of $4.7^{\circ }$. No other significant differences were found among groups. This means that diathermy has a negative impact on joint proprioception and can be explained by the spindle desensitization consequent to deeper tissue heating. This information can be important in the DOMS management of athletes, since an altered proprioception may interfere with the athlete’s performance and can increase the risk of injury.

The mathematical algorithm of two parallel ultrasound beams on a one-dimensional (1D) cancer tissue model for hyperthermia treatment was created using Matlab software. Physically, the model incorporated two beams; the first beam was permanently placed at the center of the tumor, whereas the other was set between the first beam and the tumor. The computational implementation of this technique relies on the Crank–Nicolson method. This technique is a finite different method that offers an exact heat transfer calculation based on the heat analysis of the heat node structure from a 1D biological tissue model. The Matlab software implementation was composed of two stages: tissue temperature profile calculation and optimization computation. To obtain the tissue temperature profile, the beam heat was varied from 45^∘C to 75^∘C (seven different levels of heat from the same source), while the second beam was allowed to move between the first beam and the tumor to locations at distances of 1 to 9mm (nine positions). The obtained tissue temperature profiles were subsequently analyzed to achieve the optimal time, beam position, and beam heat of the treatment. As a result of the optimization, the best position for the second beam was determined to be 5mm from the center of the tumor. Further, all tumor cells were observed to have died, whereas all normal tissues were safe. The optimal time, beam position, and beam heat of the treatment were finally collected to create and fit a mathematical function for further hyperthermia treatment.

Fluid-mechanical and morphological parameters are recognized as major factors in the rupture risk of human aneurysms. On the other hand, it is well known that a lot of machine learning tools are available to study a variety of problems in many fields. In this work, fluid–structure interaction (FSI) simulations were carried out to examine a database of 60 real saccular cerebral aneurysms (30 ruptured and 30 unruptured) using reconstructions by angiography images. With the results of the simulations and geometric analyses, we studied the analysis of variance (ANOVA) statistic test in many variables and we obtained that aspect ratio (AR), bottleneck factor (BNF), maximum height of the aneurysms (MH), relative residence time (RRT), Womersley number (WN) and Von-Mises strain (VMS) are statically significant and good predictors for the models. In consequence, these ones were used in five machine learning algorithms to determine the rupture risk predictions of the aneurysms, where the adaptative boosting (AdaBoost) was calculated with the highest area under the curve (AUC) in the receiver operating characteristic (ROC) curve (AUC 0.944).

Biomechanical analyses can be used to better understand the rupture risk of abdominal aortic aneurysms (AAAs) on a patient-specific basis using vascular geometries obtained from medical imaging. Methodologies of varying complexity are used to estimate the unloaded state of the imaged vessel to provide a reference configuration for finite element simulations. In this work, we compare the implementation and results of two of these methods, one based on geometric scaling and the other using an iterative determination of unloaded vessel geometry. We find that the two methods result in significantly different stress predictions, and that the iterative method offers superior geometric accuracy. Our findings lend context to the variation in finite element results presented in the AAA stress analysis literature.