Search

World Health Organization (WHO) recommends the use of first-line anti-tuberculosis drugs, that is, rifampicin (RIF) and isoniazid (INH) fixed-dose combination (FDC) therapies in tuberculosis (TB) d...

The main purpose of this work is to design a robust adaptive backstepping (RABS) control strategy for a pediatric exoskeleton system during passive-assist gait rehabilitation. The nonlinear dynamics of the exoskeleton system have ill-effects of uncertain parameters and external interferences. In this work, the designed robust control strategy is applied on the exoskeleton to assist children of 08–12 years, 25–40 kg weight, and 115–125 cm height. The dynamic model of the coupled human-exoskeleton system is established using the Euler–Lagrange principle. An appropriate Lyapunov function is selected to prove the uniform boundedness of the control signals. The “explosion of terms” is avoided by establishing a virtual control law without the dynamical system parameters. A Microsoft Kinect-LabVIEW experiment is carried out to estimate the desired gait trajectory. The robustness of the proposed control is validated by varying the limb segment masses and inducing the periodic external disturbances. The proposed control strategy is compared with the decentralized modified simple adaptive-PD (DMSA-PD) control strategy. From simulation results and performance improvement index, it is observed that RABS control outperforms the contrast control (DMSA-PD) to track the desired gait during passive-assist rehabilitation under the effect of model uncertainties and external disturbances.

In this work, a single degree of freedom system consisting of a mass and a Pneumatic Artificial Muscle subjected to time-varying pressure inside the muscle is considered. The system is subjected to hard excitation and the governing equation of motion is found to be that of a nonlinear forced and parametrically excited system under super- and sub-harmonic resonance conditions. The solution of the nonlinear governing equation of motion is obtained using the method of multiple scales. The time and frequency response, phase portraits, and basin of attraction are plotted to study the system response along with the stability and bifurcations. Further, the different muscle parameters are evaluated by performing experiments which are further used for numerically evaluating the system response using the theoretically obtained closed form equations. The responses obtained from the experiments are found to be in good agreement with those obtained from the method of multiple scales. With the help of examples, the procedure to obtain the safe operating range of different system parameters is illustrated.

This paper proposes an adaptive control strategy for multiple uncertain manipulators handling an object cooperatively in the presence of environmental forces and limited communication. To address the same, external and internal admittance models are imposed between the object/environment and manipulators/object to limit the excess interaction and internal forces. Thereafter, an adaptive backstepping approach is dedicated to follow the admittance-generated trajectory and deal with the dynamic uncertainties of the manipulators. Based on the Lyapunov analysis, an event-triggered (ET) mechanism is further designed to alleviate the controller-to-robot communication burden and preserve the system stability in the cooperative task. The performance of the proposed controller is compared with two admittance-based control strategies while manipulating the object through circular and lemniscate trajectories. The well-known triggering conditions, fixed and relative thresholds, are utilized further to investigate the effectiveness of the designed triggering condition. The obtained results prove the superiority of the proposed controller over the different time-triggered and even-triggered control strategies.

In the present investigation, AA 5083 foam structures were fabricated, and the quasi-static uniaxial loading behavior of AA 5083 foam with varying concentration of blowing agent (CaCO3) was studied. Also, the effect of the CaCO3 blowing agent on the foam features such as pore size, pore circularity, pore distribution, and cell wall thickness was also carried out. It was observed that with the increase in CaCO3 (wt%), the relative density of the foam and the plateau stress, and the energy absorption of the foam get reduced. The influence of blowing agent on the pore features such as pore size and distribution seemed to be minimal; therefore, no significant improvement in the pore circularity was found. The quasi-static compression test results have got affected due to the varying plastic strength of the foam that resulted due to changes in the pore size and circularity. However, a detailed analysis of the dependence of these AA 5083 foam features (porosity, pore size distribution, and circularity) on CaCO3 blowing agent is discussed in this article.

In this paper, an improved adaptive motion-force control approach is introduced to control the cooperative manipulators transporting a shared object under limited communication. The adaptive controller is designed based on the backstepping approach to control the motion of the handled object in the presence of uncertainties and external disturbances. Moreover, the force controller is established to maintain constant internal forces. An event-triggered (ET) mechanism is derived based on the Lyapunov analysis to deal with the bandwidth restrictions and maintain the system stability during the cooperative manipulation. The effectiveness of the proposed control scheme is investigated by comparing it with the existing variations of adaptive backstepping control (i.e., traditional and state augmented schemes). Moreover, the designed triggering mechanism is compared with different triggering conditions presented in the literature. The proposed control approach is further validated in a more realistic virtual robot experimentation platform (i.e., V-REP) using two SCORBOT-ER VPlus manipulators. From the TrueTime-based simulation runs, the proposed control scheme exhibits superior performance in tandem with efficient utilization of the network resources during the transportation task.

In this article, an adaptive tracking control strategy is designed for uncertain electrically driven end-effector type upper-limb rehabilitation robots subject to an input delay and a limited bandwidth channel. This control scheme is implemented to perform upper-limb passive rehabilitation training for different subjects. Primarily, dynamic analysis of the rehabilitation robot is carried out using the Euler–Lagrange principle, which incorporates motor dynamics to allow the voltage-based control commands as desirable in practical implementations. Thereafter, an adaptive backstepping control law with input delay compensation is designed to estimate the unknown dynamical parameters of the rehabilitation robot during the training sessions. Furthermore, a Lyapunov-based triggering mechanism is developed to deal with the limited bandwidth challenge and reduce the transmissions over the network. The experimental validation is conducted for different scenarios, and a comparison study is carried out with two time-triggered control schemes to investigate the potential of the proposed approach. From the experimental runs and the comparative analysis, the proposed control scheme is found to achieve a promising tracking performance with input delay compensation. Moreover, a significant saving in the network resources is attained during the passive rehabilitation training of the subjects.

The gait cycle is a study of human locomotion achieved by a combination of efforts made by the nervous system, muscles, and joints. Gait analysis has been extensively studied and applied in recent years for several applications including biometrics, healthcare, sports, and many more. It includes a large number of interrelated parameters, which are difficult to implement because of the high volume of data. The application of machine learning is a potential and promising solution to streamline this process. This work will review the latest developments in gait analysis performed by many researchers, with a primary focus on gait analysis using machine learning techniques. This review will briefly present the success of machine learning in data acquisition, detection of the disorders, and identification of the rehabilitation measures. Furthermore, the implementation of ML algorithms to correct gait abnormalities will be discussed. Finally, the possible opportunities of ML algorithms to improve the assessment of clinical gait analysis will be presented along with the concluding remarks.

In this work, the design, modeling, and development of a low-cost lower limb exoskeleton (LLES) system are presented for paediatric rehabilitation (age: 8–12 years, mass: 25–40 kg, height: 115–125 cm). The exoskeleton system, having three degrees-of-freedom (DOFs) for each limb, is designed in the SolidWorks software. A wheel support module is introduced in the design to ensure the user’s stability and safety. The finite element analysis of the hip joint connector along with the wheel support module is realized for maximum loading conditions. The holding torque capacity of exoskeleton joints is estimated using an affordable spring-based experimental setup. A working prototype of the LLES is developed with holding torque rated actuators. Thereafter, the dynamic analysis for the human-exoskeleton coupled system is carried out using the Euler-Lagrange principle and SimMechanics model. The simulation results of estimating joint actuator torques are obtained for two paraplegic subjects (Case I: 10 years age, 30 kg mass, 120 cm height and Case II: 12 years age, 40 kg mass, 125 cm height). The details of input parameters such as body mass, link lengths, joint angles, and contact forces are discussed. The simulation results of dynamic analysis have shown the potential of estimating the torques of joint actuators for the developed prototype during motion assistance and gait rehabilitation.

The objective of this work is to design a neuro-fuzzy compensated PID control for passive gait rehabilitation using a lower extremity exoskeleton system. A prototype of 6-DOFs exoskeleton device is...

In this work, theoretical and experimental analysis of a piezoelectric energy harvester with parametric base excitation is presented under combination parametric resonance condition. The harvester consists of a cantilever beam with a piezoelectric patch and an attached mass, which is positioned in such a way that the system exhibits 1:3 internal resonance. The generalized Galerkin’s method up to two modes is used to obtain the temporal form of the nonlinear electromechanical governing equation of motion. The method of multiple scales is used to reduce the equations of motion into a set of first-order differential equations. The fixed-point response and the stability of the system under combination parametric resonance are studied. The multi-branched non-trivial response exhibits bifurcations such as turning point and Hopf bifurcations. Experiments are performed under various resonance conditions. This study on the parametric excitation along with combination and internal resonances will help to harvest energy for a wider frequency range from ambient vibrations.

In the present analysis, the parametric instability regions of a three-layered sandwich plate with thin composite skins and leptadenia pyrotechnica rheological elastomer (LPRE) core under axial periodic compressive load is studied for five different boundary conditions. The governing equation of motion is derived using finite element method (FEM) which is in the form of a parametrically excited system. The instability regions of the sandwich plate are found using modified Hsu method. The shear storage modulus and loss modulus of the newly developed LPRE core is determined experimentally and used in this analysis. The dynamic properties of the LPRE based sandwich plates are observed to be better than those of the room temperature vulcanised elastomer core based sandwich plates. The critical dynamic loads and the corresponding frequencies are found which will find various applications in structural design.

The basic routine movements for elderly people are not easily accessible due to the weak muscles and impaired nerves in their lower extremity. In the last few years, many robotic-based rehabilitation devices, like orthosis and exoskeletons, have been designed and developed by researchers to provide locomotion assistance to support gait behavior and to perform daily activities for elderly people. However, there is still a need for improvement in the design, actuation and control of these devices for making them cost-effective in the worldwide market. In this work, a systematic review is presented on available lower limb orthosis and exoskeleton devices, to date. The devices are broadly reviewed according to joint types, actuation modes and control strategies. Furthermore, tabular comparisons have also been presented with the types and applications of these devices. Finally, the needful improvements for realizing the efficacy of lower limb rehabilitation devices are discussed along with the development stage. This review will help the designers and researchers to develop an efficient robotic device for the rehabilitation of the lower limb.

This paper presents the design and kinematic analysis of a novel robotic arm for the automation of manual operations performed by physiotherapists. Conventionally, a repetitive task is performed to visualize inflamed tendons, joints and ligaments with many patients. Therapeutic ultrasound techniques are further used to heal them by efficient energy transfer. During both, visualization and healing process, physiotherapists move the hand-held transducer knob for a set of specified trajectories. To perform such actions, a dedicated robotic arm can reduce manual working hours of physiotherapists and relax them. In this work, a 5-degrees of freedom (DOFs) robotic arm with three-fingered gripper is designed and modeled in SolidWorks software. The design specifications of the robotic arm are decided in accordance with therapist’s arm and available ultrasonic therapy unit of institute hospital. The detailed forward, inverse, and velocity kinematic analysis of the robotic arm are presented using Denavit-Hartenberg (D-H) parameters and Jacobian matrix. From the simulation runs in MATLAB, the joint variables and joint angular velocities are estimated for a specified set of trajectory responses viz., spiral and lemniscate curves in the x-y plane. A set of specified trajectories is selected in consultation with the institute physiotherapist. Furthermore, the linear and angular velocities of the end-effector are estimated using velocity kinematics. The smooth and small magnitude of variation in joint angles, joint angular velocities and end-effector linear and angular velocities establishes a framework for reliable design.

In the present work, both theoretical and experimental investigation of a vertical cantilever beam–based piezoelectric energy harvester are carried out under principal parametric resonance condition. A piezoelectric patch is attached near the fixed end of the cantilever beam along with an attached mass positioned at an arbitrary location. The extended Hamilton’s principle is used to derive the spatio-temporal equation of motion, and generalized Galerkin’s approximation is used to obtain the temporal nonlinear electromechanical governing equation of motion. The method of multiple scales is used to find the reduced modulation equations. Due to large transverse deflection and effect of rotary inertia of the attached mass, the system exhibits cubic and inertial nonlinearities. An experimental setup with slider crank mechanism–based shaker and a harvester consisting of a cantilever beam with piezoelectric patch and attached mass is designed and developed. The challenges posed by parametric resonance in crack development in the PZT and in the beam are reported. The theoretical and experimental output voltage and the power obtained are found to be in good agreement. Furthermore, a qualitative and quantitative comparative study of 17 energy harvesters has been carried out, and the normalized power densities have been compared.

The COVID-19 pandemic has led to the imminent collapse of medical supply chains across global economies at an unprecedented scale. Essential supplies such as personnel protective equipment (PPE), ventilator components, and face shields have witnessed a continuous rise in demand and eventually boost the role of 3D printing. Over the months following the spread of the pandemic, 3D printed alternatives of many medical devices were made more accessible to hospitals, mostly by community-sourced design and fabrication. However, with the high volume usage of additive methodologies, several challenges associated with the design, manufacturing, and deployment of medical products have now been brought to further attention. In this work, a systematic evaluation of such challenges along with few possible solutions are presented. The pandemic and its effects on the industry are introduced in the context of disruptions caused across the supply chains. The role of additive manufacturing to counter these effects is presented with an introduction of the technology itself. Employing 3D printed products to address the shortages of healthcare equipment are mentioned and visualized. Thereafter, a central discussion is followed on the issues arising from the shift in production methodology of such medical devices—from conventional manufacturing to additive one. The problems are highlighted by discussing two important types of COVID-19 related 3D printed medical equipments—mechanical ventilators and PPEs. Thereafter, few possible solution methodologies are discussed as case studies of two particular instances of having such problems. Finally, a conclusion is drawn to solve the issues raised using similar solutions followed by future opportunities.

In the present work, a two-link upper limb exoskeleton system is considered with harmonic drive actuators to track a semi-circular and L-shape path. The usage of harmonic drive actuators raises the problem of joint flexibility and produces substantial vibration at the tip of the exoskeleton system. The problem of joint flexibility in the system dynamics is considered using nonlinear spring model. Thereafter, the dynamics for two reduced cases, i.e., linear spring model and the rigid joint model are presented. At the last, transpose Jacobian control strategy is proposed to track the paths with different dynamic models. The controlled joint actuator torques for different cases are found and compared to analyze the system behavior.

In this paper, an adaptive motion-force control scheme is presented for a networked ultrasound robotic manipulator to perform a transversal abdomen scan. An adaptive backstepping position controller is designed to ensure the stability of the ultrasound robot in the presence of parametric uncertainties and external disturbances. A proportional-integral-derivative force controller is proposed to maintain a constant interaction force during the scan process. Rather than periodic time-triggered implementation, the Lyapunov-based triggering condition is derived to update the control inputs in an aperiodic manner, reduce the communication burden, and preserve the stability of the robotic system during the task. The effectiveness of the proposed control strategy is investigated based on a comparison study with different time-triggered adaptive control schemes. Moreover, the proposed event-triggered mechanism is compared with the most common triggering conditions in literature, i.e., fixed and relative thresholds. These schemes are devoted to carry out the transversal ultrasound scan in the simulation environment. Additional validation of the proposed control scheme is performed in the virtual robot experimentation platform (V-REP). From the results of simulation and experimental runs, the proposed event-triggered control scheme is found to be more promising and efficient in robot-assisted ultrasound imaging.

This work aims to estimate the lower-limb joint angles in the sagittal plane using Microsoft Kinect-based experimental setup and apply an efficient machine learning technique for predicting the same based on kinematic, spatiotemporal, and biological parameters. Ten healthy participants from 19 to 50 years (33 ± 11.24 years) were asked to walk in front of the Kinect camera. Based on the skeleton image, the biomechanical hip, knee, and ankle joint angles of the lower-limb were measured using ni-labview. Thereafter, two Bayesian regularization-based backpropagation multilayer perceptron neural network models were designed to predict the joint angles in the stance and swing phase. The joint angles of two individuals, as a testing dataset, were predicted and compared with the experimental results. The test correlation coefficient for predicted joint angles has shown a promising effect of the proposed neural network models. Finally, a qualitative comparison was presented between the joint angles of healthy people and unhealthy people of similar age groups.

In this paper, dynamic analysis of an active nonlinear vibration absorber using lead zirconate titanate (PZT) stack actuator has been carried out considering time delay in the acceleration feedback. Here the primary system is modelled as a harmonically base excited system with a nonlinear spring, damper and mass which is subjected to an external harmonic force. The smart absorber consists of a nonlinear spring, mass and damper system along with a linear spring connected in series with the PZT stack actuator. In the proposed model, the active control force is produced by the combination of spring and the PZT stack actuator which requires less voltage compared to that of the conventional system where the actuator is directly connected to the primary system and one can tune the frequency ratio of the absorber actively. The nonlinear governing equation of motion of the system is derived and solved by using a modified harmonic balance method. The steady-state response is obtained by using Newton’s method, and the stability of the system is studied using the reduced equations. It has been shown that the proposed novel vibration absorber which has inbuilt fail-safe design can absorb the vibration of the system more effectively with negligible damping than the available passive and active vibration absorbers. Also, the Den Hartog’s equal peaks are achieved when the primary system is subjected to both harmonic force and base excitation.

In this present work, the dynamic behavior of a pneumatic artificial muscle (PAM) has been studied by varying different muscle parameters and air pressure into it. The governing equation of motion has been derived using Newton’s law of motion to study the various responses in the system at principal parametric resonance condition. The temporal equation of motion contains various nonlinear parameters with forced and nonlinear parametric excitation. Then, the second-order method of multiple scales is used to find the approximate solutions and to study the dynamic stability and bifurcations of the system. The results are found to be in good agreement with the solutions obtained by solving the temporal equation of motion numerically. The instability regions by varying different system parameters have been plotted. The time responses and phase portraits have been plotted to study the system behavior with the nonlinearity. The influences of the different system parameters in the amplitude for the muscle have also been studied with the help frequency responses. In order to verify the solution, the basin of attraction has also been plotted. The obtained results will be very useful for designing the desired PAM use in different rehabilitation robotics and exoskeleton system.