Journal of Mechanics in Medicine and Biology

In this paper, problems concerning the uniaxial experimental investigation of the human abdominal aortic aneurysm (AAA) biomechanical characteristics, concomitant values of the associated Cauchy stress, failure (ultimate) stress in AAA, and the constitutive modeling of AAA are considered. The aim of this paper is to review and compare the disposable experimental data, to reveal the reasons for the high dissipation of the results between studies, and to propound some unification criteria. We examined 22 literature sources published between 1994 and 2017 and compared their results, including our own results. The experiments in the reviewed literature have been designed to obtain the stress–strain characteristics and the failure (ultimate) stress and strain of the aneurysmal tissue. A variety of forms of the strain–energy function (SEF) have been applied in the considered studies to model the biomechanical behavior of the aneurysmal wall. The specimen condition and physical parameters, the experimental protocols, the failure stress and strain, and SEFs differ between studies, contributing to the differences between the final results. We propound some criteria and suggestions for the unification of the experiments leading to the comparable results.

This paper presents a new urethral valve to deal with severe urinary incontinence (UI) caused by sphincter injury or dysneuria. This valve consists of a wireless power transfer system and a valve body structure driven by SMA (shape memory alloy) spring. The mechanical model of SMA spring and coupling model of wireless energy transfer are derived. Special attention is also given to the biological effects of electromagnetic filed as the proposed device is powered by wireless power transfer system. This valve is validated by simulation experiment and the models are used to investigate the influence of SMA spring parameters, control parameters and coil parameters on the driving characteristics of the proposed urethral valve.

This paper proposed a novel real-time algorithm for electrocardiogram (ECG) signal analysis using the first derivative and automatic threshold to locate the R-peaks. First, the ECG signals are filtered by Butterworth low pass filter to reduce the high frequency noise. Then, the first 10s datasets of the first derivative of ECG signal are analyzed to search the maximum value. Three process thresholds are computed using this maximum value, which is used to avoid the missed and false peak detections. Thus, a threshold is automatically calculated using these searched maximum values, and divide the differentiated ECG to obtain two intersection points. Recording the time of these two intersection points, a time interval is formed for the differentiated ECG. Delaying this time interval for specific sampling periods, a new time interval is acquired for the corresponding ECG cycle. Finally, the local maximum in an ECG cycle is narrowed down in this new time interval such that the R-peak can be located. The MIT-BIH Arrhythmia Database of 48 ECG recordings is used to verify the proposed algorithm. On this dataset, the proposed algorithm yielded mean sensitivity of 99.17%, positive predictivity of 97.37% and average time error of 1.01ms.

Background: Several analytical models have been developed in the past to analyze the specific role of osteocytes in the process of bone remodeling, which can be considered as the response of bone material to functional requirements. Most of them considered both the number of osteocytes and their spatial distribution in one area of influence, while others suggested in addition to include considerations of the size of the basic multi-cellular unit. Methods: Taking advantage of previous works, the standard model equation is revisited by incorporating two complementary parameters: (a) the possibility of resorption of osteocytes, apoptosis or function inhibition during remodeling process triggered by the transduction phase of osteocytes embedded within the bone matrix and; (b) the interference of influence zones for the same osteocyte. Results: Bone density evolution has been calculated starting with a medical imaging of an implanted femur. It is shown that the management of interference zone and the possibility of resorption or inhibition of osteocytes have a direct impact upon the value of the mechanical stimulus and hence on the recruitment of Bone Multicellular Units (BMUs). From a mathematical point of view, this effect has been considered by modifying mechanical stimulus of the standard model such that it is impacted by a scalar factor ranged in the interval (0.5–1). Conclusion: It is clearly demonstrated that predicted of the added bone mass amount shows that the new model is more active in low density regions where requiring rapid adaptation to the behavior of the implant, and that the standard model takes the lead in the regions with high density.

In recent years, the number of cardiac disease patients has been increasing. Modern medical research has shown that the complexity of electrocardiogram (ECG) signals is related to cardiovascular diseases. This paper investigates the difference in complexity of ECG data from the people with different cardiovascular diseases, such as atrial fibrillation (AF), ventricular arrhythmia (VA) and congestive heart failure (CHF). The empirical mode decomposition (EMD) and multiscale entropy method are used to analyze the ECG data, and a mathematical model established by a support vector machine is used to identify different diseases. The accuracy recognition rate of the AF recognition is 96.25%, and that of the CHF and VA reach 90.26% and 92.20%, respectively. The experimental results show that the recognition method proposed in this paper is successful.

Rehabilitation of major mandibular defects after tumor resection has become a serious challenge for surgeons. In this research, four various models were designed to repair a critical mandibular lateral defect. Biomechanical behavior of the models was assessed by Finite Element Method. These models are including Fibular-Free Flap (FFF), Customized Prosthesis (CP), Tray Implant without Bone Graft (TI-wo-BG), and Tray Implant with Bone Graft (TI-w-BG). FFF is a subset of microvascular free flap technique in which some segments of patient’s fibula bone are used to restore mandibular defects. CP is a hollow and light prosthesis which is fabricated using Additive Manufacturing technology from Ti alloy powder. TI-wo-BG is similar to a crib which is designed according to the geometry of the patient’s mandible. TI-w-BG, in fact, is a TI-wo-BG which is filled with small cortico-cancellous chips in order to benefit potential profit of bone grafting. The chewing operation and loading on the mandible was simulated considering the three mandibular muscular forces including masseter, medial pterygoid, and temporalis.

The result of FEM analysis of TI-wo-BG and TI-w-BG showed that in both models, screw number 6 endured a strain of 5684 and 2852$\mu$m/m which exceeded pathological and mild overload risk, respectively. This may increase the probability of screw loosening and system failure. The results proved the stability of the FFF and CP models. In addition, it can be concluded that stress and strain on the screw’s interfaces can decrease by improving the plate and increasing the friction at the interface of plate, bone and screw.

Multi-channel mechanomyography (MMG) signals were acquired from the forearm when the subjects were performing eight classes of hand movements related to rehabilitation training. Ten time domain (TD) features and wavelet packet node energy (WPNE) features were extracted from each channel of MMG, and the hand movements were classified by support vector machine (SVM), extreme learning machine (ELM), linear discriminant analysis (LDA) and $K$-nearest neighborhood (KNN) and the classifying results of three methods of collecting MMG (sensors directly on skin, sensors on cotton fabric and sensors on acrylic fiber) were compared. When all TD features were selected and SVM was adopted as the classifier, the total recognition rates of hand movements were 94.0%, 93.9% and 93.6%, respectively, of three collection methods. Using ELM can obtain similar results as SVM, with the recognition rates of 94.3%, 94.3% and 94.1%, respectively, better than using LDA (88.5%, 88.6% and 88.0%) or KNN (88.9%, 89.4% and 89.0%). For each algorithm, using TD features can acquire the highest recognition rates. Once the feature set and the classifier were selected, the total recognition rates were almost equally among three collection methods (especially for some feature sets, the differences are smaller than 1%). The results confirmed that satisfactory effects could be acquired even when the MMG was collected from sensors on fabrics with specific material, thus indicating that MMG has a unique potential value for developing wearable devices.

This paper deals with the numerical simulation of a model of blood glucose level control of a diabetic person using an electrodynamic transducer. Two mathematical models describing the dynamics of the couple glucose–insulin are used: the Bergman’s and the Cheng’s models. First, the adaptive control is applied on the dynamics of a reservoir opener by an electrodynamic transducer. Then it is applied on the two models of the glucose–insulin dynamics. It is found that the control of the reservoir opener and that of the glycemia of a diabetic patient are efficient for some values of the control parameters.

Objectives: This study will evaluate the results of parameters measured during a treadmill exercise test to predict marathon performances. Methods: We studied 171 Chinese recreational athletes who participated in marathons or half-marathons (42.2k or 21.1k, respectively) between October 2016 and December 2017. The participants completed a survey that included questions about demographics and training, and they underwent a treadmill exercise test according to the Bruce protocol. The number of years in training, mean weekly hours of training, mean weekly training volume, and performance time in subsequent marathon events were recorded and analyzed in this study. Results: The total exercise times achieved on the treadmill test were significantly longer for men compared to women ($P<0.01$). The performance times in the half-marathons were significantly shorter for men compared to women ($P<0.01$). Training volume was the only independent predictor of total exercise time on the treadmill and performance time in marathons and half-marathons (all $P<0.05$). The value of the total exercise time on the treadmill to predict performance times in half-marathons ($R^2=50.4$) was superior to full marathons ($R^2=31.4$) and significantly better in study subjects aged 30–39 years ($r=-0.72$, $P<0.01$) and 40–49 years ($r=-0.82$, $P<0.01$) compared to study subjects aged 20–29 years and 50–59 years. The percentage of decrease in the maximal heart rate (MHR) at the end of one minute of recovery time was negatively correlated with performance times in marathons. Conclusions: The total exercise time achieved during an exhaustive treadmill exercise test and percentage of decrease in the MHR at the end of one minute of recovery time are accessible parameters that can help athletes manage their expectations and adjust their training plans. A large study that includes additional countries is needed to confirm the value of treadmill exercise test results for predicting marathon performance.