Model Of Arm Research Articles

SMC for Semi-Markov Jump Cyber-Physical Systems Subject to Randomly Occurring Deception Attacks

This brief investigates the sliding mode control (SMC) for semi-Markov jump cyber-physical systems (S-MJCPSs) under randomly occurring deception attacks (RODA). It is assumed that the adversaries inject false data into the control signal in probability. First, a mode-dependent sliding surface is designed under the framework of integral form. Second, the criteria to ensure stochastic stability (SS) of the corresponding system are proposed, which establishes the theoretical framework of semi-Markov Lyapunov function. Third, an appropriate SMC law under attacks and uncertainties is constructed to drive the states of S-MJCPSs onto the switching manifold in finite time. Finally, the simulation study on a single-link robot arm model (SLRAM) is provided to demonstrate the obtained results.

Genetic Algorithm-Based Sliding Mode Control of a Human Arm Model

Spinal cord injured patients cannot move their segments by their intact muscles. A suitable controller can be used to help them move their arm. In this study, the kinematics and dynamics of right-hand movement are modeled considering planar three links. A genetic algorithm-based sliding mode (GASM) controller is designed to move the human arm model for tracking a desired trajectory in the sagittal plane. The GA is used to tune the convergence rate of the sliding mode controller for having an appropriate tracking performance. The summation of errors is considered as a cost function and GA is proposed to find the controller gains to minimize the difference between the outputs of the model and nominal trajectories. To the best of the author's knowledge, it is for the first time that the GA-sliding mode controller has been used for controlling the human hand so as to have a particular movement. Simulation results are evaluated in upward and downward movements of the human arm to affirm the effectiveness of the proposed controller.

Application of Attribute Recognition model to assess sustainability in land use in Tay Ninh province

The purpose of the article is to apply the model of identifying attributes to assess the sustainability of 4 main types of arable land use in Tay Ninh province on the basis of selecting indicators, updating data and applying statistical principles. to divide the sustainability level, use the formulas of the ARM model to calculate the hierarchy of sustainability for each facet and for aggregate stability. The economic results show that sugarcane is the most sustainable type of farming with absolute probability 1.0 and the least sustainable type is tapioca with probability 0.5. Socially, rubber, tapioca and sugarcane are most clearly shown at the very stable level with probability 0.4, respectively; 0.48 and 0.42; In terms of resources and environment, most of the four types of land use are shown at the weak and medium levels of sustainability. As a result of the combined sustainability in all three aspects of economic, social and environmental resources, sugarcane is a crop that is clearly shown at the very sustainable level, rice - color is shown at the fairly sustainable level, rubber and medium sustainable cassava. The indicators of unsustainability need to be improved according to the roadmap, in addition to the indicators that need to be maintained at a fairly sustainable level, and also pointed out 6 unsustainable causes as the main relevant factors. books, markets, science and technology, economics, society and the environment. The research results of the article will be an important scientific basis in the management and use of agricultural land in Tay Ninh province in particular and other localities in the country in general.

Biomechanics of Ankle Sprains: A 3D Dynamic Analysis of Lateral Tensile Load

Category:Ankle; SportsIntroduction/Purpose:Lateral ankle sprains are the most frequent ankle trauma and may lead to chronic lateral ankle instability (CLAI). Studies have reported anterior talofibular (ATFL) and calcaneofibular (CFL) ligaments tensile strengths around 200N and 300N. Cone Beam Weight Bearing CT (WBCT) allows visualization of 3D bony anatomy in different functional positions. The primary objective of this study was to calculate 3D ATFL and CFL tensile loads in patients diagnosed with CLAI performing Forced Inversion stance during WBCT imaging (FI-WBCT) and wearing shoes, and to compare them with a population of non-CLAI ankles. The secondary objective was to evaluate the relative contribution of shoes. We hypothesized that ATFL and CFL calculated tensile loads (CTLs) would be close to previously published data with minimal contribution of shoes.Methods:This retrospective comparative Level III study included 20 CLAI ankles and 20 controls with known demographics and available FI-WBCT datasets. Patients under 18 or with a previous history of trauma or surgery which could affect ankle architecture were excluded. A mechanical lever arm model was calculated for each case using the spatial coordinates of the weight bearing surfaces of the shoe and foot (bony landmarks: 5th metatarsal head, base and calcaneus lowest points, distal tip of the medial malleolus, ATFL and CFL distal insertion points, distal tip of the fibula). The ATFL and CFL CTL were calculated respectively as the coronal force applied at the distal insertion landmarks of the ATFL on the talus and CFL on the calcaneus. Normality was assessed using the Shapiro-Wilk test, then variables were compared using the Student t-test (normally-distributed) or the Wilcoxon rank sum test (non normally-distributed variables). Chi-2 was used for categorical variables.Results:Mean age [42.4+-10.9 vs 40.8+-10.7 years; p=0.317], Body Mass Index [24.4+-3.3 vs 24.9+-4 kg.m-2; p=0.34], sex (p=0.75), side (p=0.75) and foot alignment (FAO -1.05%+-5.5 vs 0.08%+-3.6; p=0.22) were not different between CLAI ankles and controls. CTLs for ATFL were 194N+-149 in CLAI and 192N+-183 in controls (p=0.85), while for CFL they were 311N+-286 and 311N+-361, respectively (p=0.79). Using footwears, CTLs were 406N+-360 in CLAI vs 608N+-380 in controls (p<0.05) for ATFL, and 703N+-741 vs 958N+-779 (p=0.11) for CFL. Comparing barefoot and shod values, mean CTLs in the ATFL (193N+-164.8 vs 507N+-379.1, respectively; p<0.001) and in CFL (311.3N+-321 vs 830.8N+-761.5, respectively; p<0.001) were significantly different.Conclusion:We found that the Calculated Tensile Loads for ATFL and CFL using Forced Inversion-WBCT considering the barefoot weightbearing surface were close to values described in previous cadaveric studies for those ligaments' tensile strength. A 2.6 and 2.7 fold increase was found when the weight bearing surface of the shoe was considered, indicating a possible aggravating role of shoewear. The reduced shod ATFL-CTL values found in unstable cases as compared to controls could suggest a possible active self-protection mechanism during FI-WBCT in CLAI.

Trajectory Generation of DD Robot Arm Using Iterative Learning Control

Robot arms are equipped with several joints and it is possible to operate along any given trajectories. This flexibility is essential advantages and valuable studies are conducted for reference trajectory generation to effectively control robot arms. In this study, we propose a reference trajectory generation method based on a point-to-point iterative learning control scheme. The method utilizes a linearized robot arm model obtained by applying the conventional resolved-acceleration control. Its effectiveness is demonstrated through numerical example of a DD robot arm.

An Attachment Point for Meaningful Musculoskeletal Learning

A robust understanding of body systems is elusive for many students. For instance, musculoskeletal structures and mechanisms often remain abstract and difficult for students to truly understand, even when teachers provide visual representations and accurate anatomical and physiological information. This article (1) presents a lesson for teaching about the musculoskeletal system by having students develop and build a physical model of an arm and (2) describes how teachers can use this experience to promote a deep understanding of the role of muscles, ligaments, and tendons in movement. This concrete learning experience and resulting arm model establishes a foundation for developing a more robust understanding of anatomical, physiological, and general biological principles. This lesson sequence also embeds questions that overtly draw students’ attention to important features of scientific models, which is an important nature of science issue appearing in the Next Generation Science Standards. The instructional sequence has been utilized as the foundation of an entire musculoskeletal unit in an elective anatomy and physiology course for ninth grade students, and it can easily be adapted for use in a middle school life science class or a general high school biology course.

A Novel, Oriented to Graphs Model of Robot Arm Dynamics

Robotics is an interdisciplinary field and there exist several well-known approaches to represent the dynamics model of a robot arm. The robot arm is an open kinematic chain of links connected through rotational and translational joints. In the general case, it is very difficult to obtain explicit expressions for the forces and the torques in the equations where the driving torques of the actuators produce desired motion of the gripper. The robot arm control depends significantly on the accuracy of the dynamic model. In the existing literature, the complexity of the dynamic model is reduced by linearization techniques or techniques like machine learning for the identification of unmodelled dynamics. This paper proposes a novel approach for deriving the equations of motion and the actuator torques of a robot arm with an arbitrary number of joints. The proposed approach for obtaining the dynamic model in closed form employs graph theory and the orthogonality principle, a powerful concept that serves as a generalization for the law of conservation of energy. The application of this approach is demonstrated using a 3D-printed planar robot arm with three degrees of freedom. Computer experiments for this robot are executed to validate the dynamic characteristics of the mathematical model of motion obtained by the application of the proposed approach. The results from the experiments are visualized and discussed in detail.

Dual-resonance ultra-miniaturised textile antenna for ISM/wearable applications

ABSTRACT In this paper, an ultra-miniaturised textile antenna is designed and developed for 2.45/5.8 GHz industrial, scientific and medical (ISM) band applications. The proposed microstrip line-fed dual-band antenna consists of non-conducting (Felt) and conducting (Sheildit Super) textile materials. The size of the antenna is 20 mm×30 mm×1 mm, and its (S11≤–10) bandwidths in the lower and upper resonant bands are 14.2% and 27.5%, respectively. In addition, various fabrics are considered and characterised in order to investigate different possibilities for textile antennas. The proposed antenna configuration is simple, compact, easy to manufacture, and efficient for wearable/textile applications. The proposed textile antenna performance is studied for on-body situations using the three-layered human shoulder model and four-layered human arm model. The antenna offers consistent on-body performance even when subjected to deformations caused by bending.

Bayesian Sequential Learning for Clinical Trials of Multiple Correlated Medical Interventions

We propose and analyze the first model for clinical trial design that integrates each of three important trends intending to improve the effectiveness of clinical trials that inform health-technology adoption decisions: adaptive design, which dynamically adjusts the sample size and allocation of interventions to different patients; multiarm trial design, which compares multiple interventions simultaneously; and value-based design, which focuses on cost-benefit improvements of health interventions over a current standard of care. Example applications are to seamless phase II/III dose-finding trials and to trials that test multiple combinations of therapies. Our objective is to maximize the expected population health-economic benefit of health-technology adoption decisions less clinical trial costs. We show that unifying the adaptive, multiarm, and value-based approaches to trial design can reduce the cost and duration of multiarm trials with efficient adaptive look ahead policies that focus on value to patients and account for correlated rewards across arms. Features that differentiate our approach from much other work on stochastic optimization include stopping times that balance sampling costs and the expected value of information of those samples, performance guarantees offered by new asymptotic convergence proofs, and the modeling of arms’ potentially different sampling costs. Our proposed solution can be computed feasibly and can randomize patients. The class of trials for the base model assumes that health-economic data are collected and observed quickly. Related work from Bayesian optimization can enable the further inclusion of trials with intermediate duration delays between the time of treatment initiation and observation of outcomes.This paper was accepted by Stefan Scholtes, healthcare management.

Neural Encoding of Reaches in a Linear Cortical Model.

To effectively control the arm, motor cortical neurons must produce complex patterns of activation that vary with the position and orientation of the arm and reach direction. In order to better understand how such a finely tuned dynamical system could arise and what its basic organizing principles are, we develop a model of the motor cortex as a linear dynamical system with feedback coupled to a two-joint model of the macaque arm. By optimizing the connections between neural populations with respect to an objective function that penalizes error between hand and target, as well as neural and muscular energy use, we show that certain properties of the motor cortex, such as muscle synergies, can naturally be obtained. We also demonstrate that the optimization process produces a stable neural system in which targets in the physical space are mapped to attracting fixed points in the neural state space. Finally, we show that this optimization process produces neural units with complex spatial and temporal activation patterns.

Assistive Sliding Mode Control of a Rehabilitation Robot with Automatic Weight Adjustment.

There are approximately 13 million new stroke cases worldwide each year. Research has shown that robotics can provide practical and efficient solutions for expediting post-stroke patient recovery. This simulation study aimed to design a sliding mode controller (SMC) for an end-effector-based rehabilitation robot. A genetic algorithm (GA) was designed for automatic controller weight adjustment. The optimal weights were obtained by minimizing a cost function comprising the end-effector position error, robot input, robot input-rate, and patient input. To promote safe tuner optimization, a model of the human arm was incorporated to generate the human joint torque. A computed-torque proportional derivative controller (CTPD) was designed for the human arm to approximate the central nervous system (CNS) motor control. This controller was adjusted to simulate rehabilitation effects and patient adaptation. The tuner was optimized for a trajectory tracking task with an assistive high-level control scheme. The simulation results showed lower cost compared to seven manual weight settings. The optimal weights provided good tracking performance and suitable robot inputs. This research provides a framework to conduct various simulations before testing our controller on human subjects. The preliminary results of this study will be used as the starting point for online adaptive controller tuning, which will be examined in our future research.

Mechanical behavior analysis and structural improvement for the bracket arm of wrecker

A finite element model (FEM) of the bracket arm of wrecker is developed and the mechanical behavior under six representative conditions is studied in this paper. Stress test experiment is carried out to validate the presented FEM. Comparison analyses show that results predicted from the FEM are in good agreement with those obtained from the test experiment. Moreover, the mechanical behavior analyses also give the danger working conditions for each component of the bracket arm. Based on the stress distributions under the danger working condition, structural improvement is conducted for the component which is prone to material failure. Mechanical behavior analyses of the improved structures are also carried out in this paper. Numerical analysis results show that the maximum stresses of each improved component of the bracket arm are all reduced to close or below the allowable stress. This indicted that the load bearing capacities of each component are improved effectively and meet the requirements of engineering applications.

A Kiloparsec-scale Molecular Wave in the Inner Galaxy: Feather of the Milky Way?

Abstract We report the discovery of a velocity coherent, kiloparsec-scale molecular structure toward the Galactic center region with an angular extent of 30° and an aspect ratio of 60:1. The kinematic distance of the CO structure ranges between 4.4 and 6.5 kpc. Analysis of the velocity data and comparison with the existing spiral arm models support that a major portion of this structure is either a subbranch of the Norma arm or an interarm giant molecular filament, likely to be a kiloparsec-scale feather (or spur) of the Milky Way, similar to those observed in nearby spiral galaxies. The filamentary cloud is at least 2.0 kpc in extent, considering the uncertainties in the kinematic distances, and it could be as long as 4 kpc. The vertical distribution of this highly elongated structure reveals a pattern similar to that of a sinusoidal wave. The exact mechanisms responsible for the origin of such a kiloparsec-scale filament and its wavy morphology remains unclear. The distinct wave-like shape and its peculiar orientation makes this cloud, named as the Gangotri wave, one of the largest and most intriguing structures identified in the Milky Way.

Impedance matching control between a human arm and a haptic joystick for long-term

AbstractAn impedance matching control framework between a human and a haptic joystick for long-term teleoperation is proposed in this research. An impedance model of the human arm is established analyzing the characteristics of human perception, decision, and action. The coefficients of the human arm’s impedance have been identified using a least squares method. The human arm’s impedance matching algorithm generates a corresponding motion vector for the human arm, which is determined by the interaction force measured by a force/torque sensor considering the impedance modeling of the human arm. The impedance control has been adopted for the haptic joystick to match the desired impedance to that of the human arm, which is aimed to minimize the energy consumption of the human arm for long-term teleoperation. By minimizing the fatigue of the operator, the remote control accuracy of the teleoperation can be improved. A PD control with gravity compensation algorithm has been adopted to maintain desired trajectory for the joystick by the operator more conveniently. The effectiveness of matching control has been demonstrated by trajectory following experiments for a mobile robot.

An uncertainty inversion technique using two-way neural network for parameter identification of robot arms

Due to structural complexity of robot arms, constraints of experiments, especially uncertainty of design parameters, numerical models for dynamics analysis of robot arms can produce erroneous results, which can seriously affect the performance of the designed robot arms. Reliable parameter uncertainty identification for robot arms becomes important. The current methods for uncertainty analysis have double-layered processes, in which the inner layer is for uncertainty propagation and the outer layer is an iterative optimization process. Such a nested double-layered approach limits computational efficiency. This work proposes a novel inverse method for parameter uncertainty identification using a two-way neural network. First, an element (FE) model of a robot arm is established and validated experimentally. Sensitivity analysis is then conducted using the FE model to determine a set of major parameters to be identified. A two-way neural network is next established, and the explicit formulae of direct weight inversion (DWI) use to inverse these parameters of the robot arm. Finally, the inverse result is validated by experiments. Our study show that the present inverse method can greatly improve the computational efficiency. It provides a new avenue to tackle complex inverse problems in engineering and sciences.

Planning to Minimize the Human Muscular Effort during Forceful Human-Robot Collaboration

This work addresses the problem of planning a robot configuration and grasp to position a shared object during forceful human-robot collaboration, such as a puncturing or a cutting task. Particularly, our goal is to find a robot configuration that positions the jointly manipulated object such that the muscular effort of the human, operating on the same object, is minimized while also ensuring the stability of the interaction for the robot. This raises three challenges. First, we predict the human muscular effort given a human-robot combined kinematic configuration and the interaction forces of a task. To do this, we perform task-space to muscle-space mapping for two different musculoskeletal models of the human arm. Second, we predict the human body kinematic configuration given a robot configuration and the resulting object pose in the workspace. To do this, we assume that the human prefers the body configuration that minimizes the muscular effort. And third, we ensure that, under the forces applied by the human, the robot grasp on the object is stable and the robot joint torques are within limits. Addressing these three challenges, we build a planner that, given a forceful task description, can output the robot grasp on an object and the robot configuration to position the shared object in space. We quantitatively analyze the performance of the planner and the validity of our assumptions. We conduct experiments with human subjects to measure their kinematic configurations, muscular activity, and force output during collaborative puncturing and cutting tasks. The results illustrate the effectiveness of our planner in reducing the human muscular load. For instance, for the puncturing task, our planner is able to reduce muscular load by \( 69.5\% \) compared to a user-based selection of object poses.

Approach for Calibrated Measurement of the Frequency Response for Characterization of Compliant Interface Elements on Vibration Test Benches

In vibration tests, the behavior of the structure depends on its mechanical boundary conditions, which are represented in physical tests by connecting elements with mechanical properties. Adjustable impedance elements are machine elements fulfilling the task of an adjustable connection on a vibration test bench and therefore represent a variety of properties. Their mechanical properties must be known over wider ranges than comparable compliant structures tested in the literature. This paper is dedicated to vibration testing of the adjustable impedance elements themselves, taking the influences of fixtures and measuring devices of the test bench into account. Different approaches for measuring the frequency response functions are applied to freely vibrating masses at a hydraulic and an electrodynamic test bench. Mass cancellation and the frequency-dependent measurement systems function have shown their usefulness in characterizing the biodynamic response of hand–arm models before. This measurement method is extended to be transferable to machine elements to obtain reliable results under a wider range of test conditions. The necessity for dynamically calibrated measurement of the frequency response functions is demonstrated for different free vibration masses and for two compliant elements on two different test benches to provide results over a wide range of test conditions.

Using classical Cepheids to study the far side of the Milky Way disk

In an effort to improve our understanding of the spiral arm structure of the Milky Way, we use classical Cepheids (CCs) to increase the number of young tracers on the far side of the Galactic disk with accurately determined distances. We used a sample of 30 CCs that were discovered using near-infrared photometry from the VISTA Variables in the Vía Láctea survey (VVV) and classified based on their radial velocities and metallicities. We combined them with another 20 CCs from the literature for which VVV photometry is available. We used the compiled sample of CCs with homogeneously computed distances based on VVV infrared photometry as a proof of concept to trace the spiral structure in the poorly explored far side of the disk. Although the use of CCs has some caveats, these variables are currently the only available young tracers on the far side of the disk for which a numerous sample with accurate distances can be obtained. Therefore, a larger sample could allow us to make a significant step forward in our understanding of the Milky Way disk as a whole. We present preliminary evidence that CCs favor the following: a spiral arm model with two main arms (Perseus and Scutum-Centaurus) that branch out into four arms at Galactocentric distances, RGC ≳ 5−6 kpc; the extension of the Scutum-Centaurus arm behind the Galactic center; and a possible connection between the Perseus arm and the Norma tangency direction. The current sample of CCs on the far side of the Galaxy are in the mid-plane, which argues against the presence of a severely warped disk at small Galactocentric distances (RGC ≲ 12 kpc) in the studied area. The discovery and characterization of CCs at near-infrared wavelengths appears to be a promising tool to complement studies based on other spiral arm tracers and extend them to the far side of our Galaxy.

Design and kinematic modeling of an origami-inspired cable-driven flexible arm

The cable-driven flexible arm based on the principle of origami is a new type of non-articulated compliant actuator with high integration, high environmental adaptability, large workspace/large deployment ratio. The forward/reverse kinematic models of joint space, operation space and driving space along with trajectory error model of the cable-driven flexible arm were proposed in this paper. The prototype of the flexible arm was developed capable of realizing bending, torsion and expansion/contraction. The simulation and experiment results of the cable-driven foldable flexible arm verified feasibility of the kinematic models and driving method proposed in this paper. Above research achievements lay necessary foundation for the next step to realize the key service functions of grasping/manipulation, three-dimensional precise movement, non-structural environment interaction/adaptation of the flexible arm with variable stiffness, variable configuration and variable size.

Race/ethnicity and response to blood pressure lowering treatment after intracerebral hemorrhage.

It is unknown if race/ethnicity modifies the response to blood pressure (BP) lowering treatment after intracerebral hemorrhage (ICH). We aimed to examine the race/ethnicity differences in the response to BP lowering treatment after ICH. This is a post hoc analysis of the Antihypertensive Treatment of Acute Cerebral Hemorrhage II (ATACH-2) trial. The primary outcome is good outcome, defined as 90-day modified Rankin Scale 0-3. The primary predictor is race/ethnicity for which we included non-Hispanic categories of White, Black, Asian, and the category of Hispanic. We fit adjusted logistic regression models with the predictor of race/ethnicity and models with the interaction term of treatment*race/ethnicity. We included a total of 953 patients in our analysis (White = 213, Black = 112, Asian = 554, and Hispanic = 74). In the models with the interaction between race/ethnicity and treatment, we found that White patients assigned to the intensive treatment arm had lower predicted probability of good outcome than those assigned to the standard treatment arm (Model 1: 56.2% vs. 68.1%, p = .027; Model 2: 53.4% vs. 68.3%, p = .009). When divided into White and non-White groups, intensive treatment was associated with higher odds of serious adverse events in White group but not in the non-White group. In addition, there was an association between intensive treatment and higher risk of hematoma expansion in White patients and lower risk of hematoma expansion in non-White patients. In the ATACH-2, there was an interaction between race/ethnicity and response to BP lowering treatment after ICH, with White patients having an association between intensive blood pressure reduction and worse outcome.