Modeling and control of COVID-19 disease using deep reinforcement learning method.

The prevalence of epidemics has been studied by researchers in various fields. In the last 2 years, the outbreak of COVID-19 has affected the health, economy, and industry of communities around the world and has caused the death of millions of people. Therefore, many researchers have tried to model and control the prevalence of this disease. In this article, the new SQEIAR model for the spread of the COVID-19 disease is provided, which, compared to previous models, explores the effects of additional interventions on the outbreak and incorporates a wider range of variables and parameters to enhance its accuracy and alignment with reality. These modifications in the model lead to a more rapid eradication and control of the disease. This model includes six variables of the group of susceptible, quarantined, exposed, symptomatic, asymptomatic, and recovered individuals and includes three control inputs such as quarantine of susceptible, vaccination, and treatments. In order to minimize symptomatic infectious individuals and susceptible individuals and also to reduce treatment, vaccination, and quarantine costs, an optimal control approach using the Deep Deterministic Policy Gradient (DDPG) method has been applied to the system. This algorithm is applied to the model in different cases of control inputs, and for each case, optimal control inputs are obtained. In the following, the number of deaths due to the disease and the total number of symptomatic infectious individuals for each of these optimal control cases has been calculated. The results of the implemented control structure demonstrated a reduction of 60% in the number of deaths and 74% in the number of symptomatically infected individuals compared to the uncontrolled model. Finally, to test the performance of the control system, noise was applied to the system in various ways, including three methods: applying noise to observer variables, applying noise to control inputs, and applying uncertainty to model parameters. Therefore, we found that this control system was robust and performed well in different conditions despite the disturbance.

Modeling and Robust Control of a 5 DOF Model for Rowing Motion by Inverse Dynamics Method.

Background: Competitive sailing requires efforts pertinent to physiological limitations and coordination between different parts of the body. Such coordination depends on the torques applied by muscles to the joints. Objective: This study aims to simulate the motion and provide a control law for the joint torques in order to track the desired motion paths. Material and Methods: In this analytical study, an inverse dynamics based control is employed in order to simulate the motion by tracking the desired movement trajectories. First, the dynamics equations are obtained using Lagrange method for 5 degrees of freedom (5 DOF) model. In the following, a robust control scheme with inverse dynamics method based on the Proportional-Integral-Derivative (PID) approach is employed to track the desired joint angles obtained from the experiment. Results: The simulation results demonstrate the performance of the proposed control method. Low settling times are achieved for the entire joint, which is appropriate in comparison with the time period of each cycle (3.75 s). Also, the maximum torques required to be applied to the joints are in physiological range. Conclusion: This study provided an appropriate model for the analysis of human movement in rowing sport. The model can also be cited in terms of basic biological theories in addition to practical computational uses in biomechanical engineering. Accordingly, the generated control signals can help to improve the interactive body movements during paddling and in designing robotic arms for automatic rowing.

The comparison of stress and strain between custom-designed bone plates (CDBP) and locking compression plate (LCP) for distal femur fracture.

BACKGROUND: Distal femur fracture is considered one of the most common fractures due to high-energy traumas such as car accidents or low-energy traumas such as osteoporosis. Locking plates are orthopedic implants used for stabilized femur fracture. Thus, designing a bone plate fitted exactly with the patient's bone and correctly fixing bone segments are required for better fracture healing. OBJECTIVES: This study aims to design a bone plate based on anthropometric characteristics of patients' femurs and compare performing custom-designed bone plates (CDBP) with the locking compression plate (LCP) by finite element method. MATERIALS AND METHODS: In this analytical study, a 3D model of four patients' femur and CDBP were firstly designed in MIMICS 19.0 based on the patient's femur anatomy. After designing the bone plate, the CDBPs and LCP were fixed on the bone and analyzed by finite element method (FEM) in ANSYS, and stress and strain of bone plates were also compared. RESULTS: The maximum principal stress for all 3D models of patients' fracture femur by CDBPs was stabilized better than LCP with a decrease by 39.79, 12.54, 9.49, and 20.29% in 4 models, respectively. Also, in all models, the strain of CDBPs is less than LCP. Among the different thicknesses considered, the bone plate with 5 mm thickness showed better stress and strain distribution than other thicknesses. CONCLUSION: Customized bone plate designed based on patient's femur anatomical morphology shows better bone-matching plate, resulting in increasing the quality of the fracture healing and fails to any need for additional shaping. TRIAL REGISTRATION NUMBER: Design and analysis of an implant were investigated in this study. There was no intervention in the diagnosis and treatment of patients and the study was not a clinical trial.

An adaptive integral terminal sliding mode controller to track the human upper limb during front crawl swimming.

Injuries are inevitable during swimming. The main goal of athletes especially competitive ones and coaches is to do the most mechanically effective movement patterns. In this case, biomechanical assessments could be beneficial in the management and prevention of injuries and pain in swimmers' vulnerable joints. As the upper limb in swimming causes the highest propulsive force, the arm is exposed to more injuries. A skeletal model with 5 degrees of freedom is developed to simulate the swimmer's arm during front crawl swimming. This model includes shoulder and elbow joints with all of their degrees of freedom. An adaptive integral sliding mode (AITSM) controller is employed to track the desired joint trajectories during swimming. This controller can converge the tracking errors to zero in finite time. For tuning the controller gains regardless of the upper bounds of the system uncertainties, an adaptive controller is applied. The results demonstrate the performance of the AITSM strategy in tracking the desired trajectory of an underwater arm model during swimming. During the down sweep to catch phase, arm movements cause more stress in the shoulder than the elbow. The applied moment at the shoulder is almost triple of the elbow's moment. Therefore, the most vulnerable joint is the shoulder. By considering shoulder strength, the injury risk is predicted about 10% for the considered swimmer.HighlightsThe human upper limb during front crawl swimming is simulated.A 5-DOF skeletal model is considered to simulate the arm.An adaptive integral sliding mode (AITSM) controller is employed to track the desired trajectory.The results show that the controller has the proper performance to track the desired motion.The most vulnerable joint is the shoulder and higher moments are induced at this joint.

Comparison of Kinematic Movement Patterns Between 2 Subgroups of Females With Low Back Pain and Healthy Women During Sit-to-Stand and Stand-to-Sit.

The purpose of study was to compare the kinematic patterns of the thoracic, lumbar, and pelvis segments and hip joints between 2 low back pain subgroups and healthy women during sit-to-stand and stand-to-sit. Kinematic data of 44 healthy women and 2 subgroups of females with low back pain in 2 subgroups of movement system impairment model (rotation-extension [Rot.Ext] and rotation-flexion [Rot.Flex]) were recorded. Participants performed sit-to-stand and stand-to-sit at a preferred speed. Each task was divided into a pre buttock lifted off/on (pre-BOff/n) phase and a post-BOff/n phase. The Rot.Ext subgroup showed greater range of motion in the thoracic during pre-BOff phase of sit-to-stand (P < .001) and pre-BOn phase of stand-to-sit (P = .01) compared to the other 2 groups. The Rot.Flex subgroup displayed limited left hip joint excursion during sit-to-stand pre-BOff (P = .04) and stand-to-sit post-BOn phases (P = .02). The Rot.Flex subgroup showed greater pelvis tilt excursion during sit-to-stand post-BOff (P = .04) and stand-to-sit pre-BOn (P = .01) and post-BOn phases (P = .01). In subgroups of women with chronic low back pain, there were kinematic changes in adjacent body segments/joints of lumbar spine during sit-to-stand and stand-to-sit tasks.

Nonlinear analysis of dynamic stability in walking with toe-only rocker sole shoes in elderly.

BACKGROUND: Elderly subjects are at the risk of falling. One type of shoe intervention used for this group of the subjects is the shoe with rocker. The aim of this study was to investigate the effects of shoes with various degrees of rockers on dynamic stability of elderly subjects while walking. METHOD: 15 elderly subjects were recruited in this study. A motion analysis system was used to record the motions of body while walking on a treadmill. The local dynamic stability (LDS) was evaluated based on use of Lyapunov exponent of center of mass (COM) movement. The subjects were asked to walk barefoot, with shoe with no rocker and with shoe with various rockers (10, 20, 30 and 40°). RESULTS: The mean values of LDS (λmax-S) in anteroposterior direction were 0.95 ± 0.46, 0.78 ± 0.51 and 0.74 ± 0.54 in bare foot, shoes with no rocker and shoe with 10° rocker, respectively. The mean value of LDS (λmax-S) in vertical direction varied between 1.21 and 1.23. There was no significant difference between LDS of elderly subjects while walking with shoes with various rocker angles. DISCUSSION: Use of shoes with various rocker angles dose not influence on dynamic stability of elderly subjects while walking. Therefore, it is recommended to use this kind of shoe intervention for other trapeutic purposes.

Prediction of muscle activation for an eye movement with finite element modeling.

In this paper, a 3D finite element (FE) modeling is employed in order to predict extraocular muscles' activation and investigate force coordination in various motions of the eye orbit. A continuum constitutive hyperelastic model is employed for material description in dynamic modeling of the extraocular muscles (EOMs). Two significant features of this model are accurate mass modeling with FE method and stimulating EOMs for motion through muscle activation parameter. In order to validate the eye model, a forward dynamics simulation of the eye motion is carried out by variation of the muscle activation. Furthermore, to realize muscle activation prediction in various eye motions, two different tracking-based inverse controllers are proposed. The performance of these two inverse controllers is investigated according to their resulted muscle force magnitude and muscle force coordination. The simulation results are compared with the available experimental data and the well-known existing neurological laws. The comparison authenticates both the validation and the prediction results.

Modular neuromuscular control of human locomotion by central pattern generator.

The central pattern generators (CPG) in the spinal cord are thought to be responsible for producing the rhythmic motor patterns during rhythmic activities. For locomotor tasks, this involves much complexity, due to a redundant system of muscle actuators with a large number of highly nonlinear muscles. This study proposes a reduced neural control strategy for the CPG, based on modular organization of the co-active muscles, i.e., muscle synergies. Four synergies were extracted from the EMG data of the major leg muscles of two subjects, during two gait trials each, using non-negative matrix factorization algorithm. A Matsuoka׳s four-neuron CPG model with mutual inhibition, was utilized to generate the rhythmic activation patterns of the muscle synergies, using the hip flexion angle and foot contact force information from the sensory afferents as inputs. The model parameters were tuned using the experimental data of one gait trial, which resulted in a good fitting accuracy (RMSEs between 0.0491 and 0.1399) between the simulation and experimental synergy activations. The model׳s performance was then assessed by comparing its predictions for the activation patterns of the individual leg muscles during locomotion with the relevant EMG data. Results indicated that the characteristic features of the complex activation patterns of the muscles were well reproduced by the model for different gait trials and subjects. In general, the CPG- and muscle synergy-based model was promising in view of its simple architecture, yet extensive potentials for neuromuscular control, e.g., resolving redundancies, distributed and fast control, and modulation of locomotion by simple control signals.

Comparison of the trunk-pelvis and lower extremities sagittal plane inter-segmental coordination and variability during walking in persons with and without chronic low back pain.

Inter-segmental coordination can be influenced by chronic low back pain (CLBP). The sagittal plane lower extremities inter-segmental coordination pattern and variability, in conjunction with the pelvis and trunk, were assessed in subjects with and without non-specific CLBP during free-speed walking. Kinematic data were collected from 10 non-specific CLBP and 10 non-CLBP control volunteers while the subjects were walking at their preferred speed. Sagittal plane time-normalized segmental angles and velocities were used to calculate continuous relative phase for each data point. Mean absolute relative phase (MARP) and deviation phase (DP) were derived to quantify the trunk-pelvis and bilateral pelvis-thigh, thigh-shank and shank-foot coordination pattern and variability over the stance and swing phases of gait. Mann-Whitney U test was employed to compare the means of DP and MARP values between two groups (same side comparison). Statistical analysis revealed more in-phase/less variable trunk-pelvis coordination in the CLBP group (P<0.05). CLBP group demonstrated less variable right or left pelvis-thigh coordination pattern (P<0.05). Moreover, the left thigh-shank and left shank-foot MARP values in the CLBP group, were more in-phase than left MARP values in the non-CLBP control group during the swing phase (P<0.05). In conclusion, the sagittal plane lower extremities, pelvis and trunk coordination pattern and variability could be generally affected by CLBP during walking. These changes can be possible compensatory strategies of the motor control system which can be considered in the CLBP subjects.