فصلنامه مهندسی پزشکی زیستی
سال پانزدهم شماره 2 (تابستان 1400)

Microneedles are a type of micron-sized needle that is the third most widely used delivery system after oral and injectable drug delivery, used in a variety of fields including drug release and rejuvenation. Optimizing the geometry of microneedles to reduce pain and inflammation has been important in recent years. Due to the high cost of microneedle fabrication, numerical simulation of microneedle penetration into the skin can be useful to evaluate the microneedle strength as well as its effect on the skin during penetration. In this study, first a new simulation method in Abaqus software with explicit method using cohesive elements to investigate the penetration of microneedles in the skin of the human forearm was presented. The skin was considered as Ogden and bilayer hyperelastic models. The microneedle was considered as a rigid body and a constant velocity of 0.6 mm/s was applied to it .The microneedle with bulk with bio-inspired titles was examined and its important parameters such as height, sharpness and bulk angle were evaluated. Finally, some proposed models of microneedles with longitudinal grooves are presented to increase the concentration of stress on the skin and prevent friction. A comparison of the designed microneedle with the barbless microneedle shows that the barbed microneedle concentrates more than twice as much stress on the skin, but reduces the penetration force by as much as 15%, making it easier to penetrate the skin. The results show that the reduction longitudinal grooves increase the tension created in the skin by about 10%, but have little effect on the penetrating force on the skin.

In cognition physiology and neuroscience, spatial memory is responsible for the maintenance and recall of information related to environmental details, orientation, and spatial navigation. The brain’s cognitive functions including navigation are executed through correlated and sequential activities of different regions. According to previous research, navigation is largely related to the activities of the Hippocampus(HPC) and the medial temporal lobe(MTL), and retrieval of spatial memories from these regions is controlled by the frontal region and specifically medial prefrontal cortex(mPFC). In this paper we attempt to provide a navigation cognitive model based on computational concepts focusing on bidirectional interaction between HPC and mPFC. This model is provided Considering 1. the lack of a comprehensive cognitive model of navigation on a previously learned path and ambiguities regarding the information transferring between the regions, and 2. disagreement between available models and the currently known actual information flow occurring within the brain. The model is inclusive of the active brain regions engaged in navigation using the cognitive map. Furthermore, we propose a computational model based on van-der-pol neuron pools and controlling rule-base, which is naturally related to the actual brain activity through the synchrony mechanism for information transfer and the mPFC rule-based control of the medial-temporal lobe. Finally, by analyzing and presenting evidence, we have shown that the model can be beneficial and practical for describing cognitive and functional disorders in navigation, also for design and prediction of the outcomes of therapeutic and rehabilitation protocols in diseases related to spatial navigation, such as the Alzheimer’s disease.

Coronavirus, or Covid 19, is a contagious disease caused by the coronavirus and is a threat to the health and economy of countries. Although vaccine production and distribution are currently underway, but non-pharmacological interventions are still being implemented as an important and fundamental strategy to control the spread of the virus in countries around the world. Now, according to the existing conditions, having a suitable dynamic model of this disease will provide information to the relevant authorities about the behavior, prevalence, speed of transmission, and other parameters. Various mathematical modeling methods have been proposed to analyze the transmission patterns of this new disease. In this paper, using fractional calculus, the dynamics of Covid 19 will be investigated. One of the major advantages of fractional calculus, which can be very effective in modeling and controlling epidemics, is its long-term memory property. With a dynamic model of virus transmission and prevalence, focusing on a control strategy based on non-pharmacological interventions can be important. In this paper, a new adaptive fractional order sliding mode controller is proposed for non-pharmacological decisions. The proposed method in this paper for controlling non-pharmacological interventions is an adaptive fractional order active sliding mode control, which can have a good performance due to its robustness against parameter uncertainty and system disturbances.

Balance in daily movements like as stair ascending is a challenge for the people with leg lengths discrepancy (LLD). These people change their pattern of movement to compensate the difference between legs’ length. Due to the changes in movement patter, body's center of mass which is one of the important factors in maintaining balance can be varied. Compensatory insoles are used to compensate for short legs. The aim of this study is to investigate changes in the center of mass, with and without using insoles in people with leg length when climbing stairs. In this practical cross-sectional study, the movement of 20 participants while climbing stairs in two groups of healthy people and people with LLD was recorded by a three-dimensional movement analysis system. Changes in pelvic, knee and ankle joint angles were calculated with the 7-member Euler method. Then the rotation and transferring matrixes were defined by using the joint angles to determine the torque arm of the limbs. By the total body torque method, the center of mass changes in three directions were obtained. Then, these changes were compared between the experimental and control groups using independent and paired t-test at 95% confidence level. The results showed that the displacement of the center of mass in all three directions was significantly higher for people with different leg length differences when comparing with healthy people (p<0.05). The results also showed that range of movement no significant different in the Vertical axis between normal and LLD people (p>0.05) when using insole. Based on the findings of this study, it can be concluded that the use of compensatory insoles alone cannot make changes in the center of mass as one of the indicators to measure the balance in climbing stairs like normal people.

Primary stability is the initial mechanical engagement of the implant with its neighboring bone, which is a prerequisite for successful implantation. Primary stability of dental implants can be investigated through in-vitro assessment of stiffness and the ultimate load of the bone-implant complex. Implantation and the following loading on an implant could cause mechanical damage in the peripheral bone, and subsequently, reduce the primary stability of the implant. This study aimed at finding the effects of damage induced in the bone through exerting compressive loading-unloading cycles on the primary stability of the bone-implant system. For this purpose, a dental implant was inserted into a bone sample extracted from the proximal part of a bovine tibia. The implant was undergone step-wise displacement-controlled loading-unloading cycles, and µCT images of the neighboring bone were obtained at each loading-unloading step. Then, the stiffness of the bone-implant structure was calculated after unloading the specimen in each step and the first maximum endured force during loading was considered as the ultimate load of the structure. The distribution of plastic stain in the bone due to loading-unloading of the construct was calculated using digital volume correlation, through correlating the µCT images after unloading in each step. Results of this work showed that increasing the step-wise displacement amplitude from zero to 0.96 mm caused a stiffness reduction of 40%, compared to the initial stiffness, and induced higher plastic strains in peri-implant bone. The results of this study can be used in optimizing the design of dental implants, with the approach of increasing primary stability.

Parkinson’s Disease (PD) is one of the most common neurodegenerative diseases that cause abnormal gait patterns by affecting central nervous system. Since this disease is incurable, the reliable diagnosis can lead to slowing disease progression, reducing the risk of physical injuries and improving the quality of patient's life. In this regard, the development of fast, cost-effective and reliable detection systems is essential. This study has therefore proposed a detection method using vertical ground reaction force signals, which provide a non-invasive and useful index of the motor control function. It is based on generalized singular value decomposition, K-Nearest Neighbor (KNN) and Probabilistic Neural Network (PNN). The performance of the algorithm has been evaluated by gait signal of 93 individuals with PD and 73 healthy controls. The results have demonstrated that the proposed new symmetric feature is able to achieve 96.19% and 95.67% accuracy rates, 97.22% and 93.35% sensitivity rates, 95.02% and 97.33% specificity rates using the KNN and PNN classifiers, respectively. Furthermore, average accuracy rates of 98.23% and 98.51%, sensitivity rates of 93.5% and 100%, specificity rates of 100% and 96.53% have been obtained for stage classification using these two classifiers. The obtained high average accuracy rates have confirmed the promising capability of the proposed non-invasive and cost-effectiv

Transcutaneous electrical stimulation of peripheral nerve fibers has always been an important field of research. Many studies indicate the possibility to block the conduction of nerve fibers by using high frequency alternating currents (HFAC). According to the fact that the stimulation of narrower fibers is always accompanied by activation of thicker fibers, in this study, current regions for selective stimulation of different nerve fibers without activating other fibers have been obtained. This success is achieved through the nerve conduction block using HFAC (5-20 KHz). Stimulation current regions is a part of the intensity-frequency diagram which by choosing the excitation parameters in this area, only some target fibers are stimulated according to their diameters. The McIntyre nerve fiber model was used to perform these simulations; The sodium-potassium pump model has also been added to it and its effects have been investigated. A unipolar electrode is considered which acts as a point current source at different distances from the nerve fibers, and selective excitation spaces are obtained for the Aδ and Aβ fibers. the appropriate frequency range for excitation of different fibers is 5 kHz and above, while the desired current for selective excitation of Aδ and Aβ fibers is given by two polynomial equations of order 2 and 3, respectively, which are fitted to the middle of selective parameter space of each nerve fiber. also, the excitation current varies from about 0.8 to 1.8 mA for Aδ fibers and from about 0.55 to 0.95 mA for Aβ fibers. in all of the simulations mentioned in this article, the sinusoidal waveform is used.