Model Of Human Arm Research Articles

Wearable frequency selective surface-based compact dual-band antenna for 5G and Wi-Fi applications

The ever-growing miniaturization of electronic devices is foremost due to a wide range of changes in shrinking the wearable devices. This article focuses on a small, wearable antenna with dual bands for 5G and Wi-Fi communications. The Frequency Selective Surface (FSS) is made of denim Jean and has a top- loaded stubs-inspired radiator and a modified ground plane structure to induce the resonance frequencies at 3.5 and 5.8 GHz within a compact 31.5 mm × 26 mm size. With the FSS integrated antenna, you can cover the N-78 5G band-width of 620 MHz (S11 × −10dB) in the 3.28–3.9 GHz range, as well as the Wi-Fi bandwidth of 600 MHz (S11 × −10 dB) in the range of 5.65–6.25 GHz. The antenna presented has a peak gain of 7.07 dB at 3.5 GHz and 6.02 dB at 5.8 GHz. This antenna is mounted near a human arm model lowering the Specific Absorption Rate (SAR) to 0.370W/kg at 3.5 GHz and 0.870W/kg at 5.8 GHz. The simulated values are validated with measured results and are suitable for body area communication. The designed FSS antenna provides stable impedance bandwidth for conformal applications with enhancing radiation performance.

Design and Characterization of a Self-Aligning End-Effector Robot for Single-Joint Arm Movement Rehabilitation

Traditional end-effector robots for arm rehabilitation are usually attached at the hand, primarily focusing on coordinated multi-joint training. Therapy at an individual joint level of the arm for severely impaired stroke survivors is not always possible with existing end-effector robots. The Arm Rehabilitation Robot (AREBO)—an end-effector robot—was designed to provide both single and multi-joint assisted training while retaining the advantages of traditional end-effector robots, such as ease of use, compactness and portability, and potential cost-effectiveness (compared to exoskeletons). This work presents the design, optimization, and characterization of AREBO for training single-joint movements of the arm. AREBO has three actuated and three unactuated degrees of freedom, allowing it to apply forces in any arbitrary direction at its endpoint and self-align to arbitrary orientations within its workspace. AREBO’s link lengths were optimized to maximize its workspace and manipulability. AREBO provides single-joint training in both unassisted and adaptive weight support modes using a human arm model to estimate the human arm’s kinematics and dynamics without using additional sensors. The characterization of the robot’s controller and the algorithm for estimating the human arm parameters were performed using a two degrees of freedom mechatronic model of the human shoulder joint. The results demonstrate that (a) the movements of the human arm can be estimated using a model of the human arm and robot’s kinematics, (b) AREBO has similar transparency to that of existing arm therapy robots in the literature, and (c) the adaptive weight support mode control can adapt to different levels of impairment in the arm. This work demonstrates how an appropriately designed end-effector robot can be used for single-joint training, which can be easily extended to multi-joint training. Future work will focus on the evaluation of the system on patients with any neurological condition requiring arm training.

Design of a compact sigma slotted dual-mode UWB antenna for wireless body area network applications

Abstract This article presents the design of a novel sigma slotted circular monopole antenna for wireless body area network applications. The design is proceeded with a sigma-shaped slot etched on the circular radiator with Rogers 4003C substrate. The size of the proposed antenna is 30 × 30 × 1 mm3. With partial ground plane, the bandwidth characteristics of the antenna have been enhanced. The designed antenna covers 2–10 GHz of the ultra wideband, thereby providing more than 106% bandwidth. The antenna exhibits high gain values of 1.95, 3.23, 3.46, and 5.95 dB at 2.45, 3.45, 5.8, and 9.5 GHz, respectively. The proposed design operates on off-body mode at 2.45 GHz and on-body mode at 5.8 GHz, thus acting as a dual-mode antenna. To ensure the health and safety measure, specific absorption rate analysis was done for both low and high values of input power and also with Cartesian and cylindrical human arm models. Bending analysis was also done. The time domain parameter group delay was also analyzed for the proposed antenna for on- and off-body scenarios. The prototype was fabricated, and validation of simulation results was done for free space and on-body scenarios.

Compact Ultra-­Wideband Planar Inverted F Antenna on Laminated Paper­-Based Substrate with Reduced Specific Absorption Rate

This paper presents a laminated paper-based Planar Inverted F Antenna (PIFA) for wireless body area network (WBAN) applications. The major challenges like providing adequate thickness, uniformity of surface, and water wet ability associated with paper substrate have been transcended in this antenna design by laminating the substrate with a transparent sheet. The simulated and measured reflection coefficients of the fabricated antenna in free space and on human arm are remarkably good, validating the prototype’s utility. It can operate effectively in GSM, WMTS, GPS, DCS, ISM, WiMAX, HIPERLAN, WLAN, and UWB frequency bands with S11 less than -10 dB and the gain ranging from 0.94 to 9.53 dB (free space) and 1.03 to 6.07 dB (on-body). The electrical size of the proposed antenna is 0.16 λg x 0.12 λg at 0.7 GHz with a group delay below 2.3 ns over the desired frequency bands. The performance characteristics are also investigated on-body and it encompasses most of the desired frequency bands for the body area network. This paper also analyses the specific absorption rate (SAR) of the designed antenna by placing it on a tissue-layered human arm model, which is 0.64 Watt/kg, complying with the SAR safety guidelines.

Wearable Directional Button Antenna for On-Body Wireless Power Transfer

For the future application of wireless power transfer on the human body, a wearable directional button antenna, composed of 2×3 artificial magnetic conductor (AMC) cells, is proposed, where the kinetic energy antenna is put on the elbow, which then charges the receiving communication antenna on the upper arm. The radiator of the button antenna is a monopole antenna, which is top-loaded by two cylindrical substrates with different radii to achieve a low profile, and it is fed by the microstrip line made by textiles, including 100% cotton substrate and conductive textile. The AMC cells are put close to the feeding microstrip line in order to realize directional radiation to the other side. Meanwhile, a real human arm model of a Chinese women is built to accurately analyze the corresponding wave propagations. Consequently, two identical antenna prototypes are fabricated, and the corresponding measurements are implemented, where an on-arm approximate measurement method for the radiation pattern is proposed. The measurements agree well with the simulations. Additionally, the influence of the communication antenna on the kinetic energy antenna and the interactions between the antenna and the arm are analyzed. Finally, the transmission efficiency and the SAR values are investigated.

Computational study and validation of a novel passive hand tremor attenuator

Tremors are a prevalent movement disorder due to a nervous system condition that leads to involuntary muscle movements observed in patients. This paper converts the tremorous anatomical human arm model to a single degree of freedom (SDOF) forced vibration problem. The mathematical modelling with Euler–Lagrange’s equation is performed for the SDOF human arm model with two different potential vibration absorbers. A computational study is conducted on MATLAB Simulink by MathWorks Inc. (Natick, MA) to compare two absorbers, and the results are verified on the multibody dynamics simulation solution software, MSC Adams by Hexagon AB. It is concluded that the T beam-shaped vibration absorber represented a higher amplitude reduction, up to 80%, compared to the inertial mass absorber, which had an amplitude reduction of 65% over the range of frequencies. Experiments conducted with the T beam absorber prototype also support the computational findings. Future research focuses on designing an ergonomic wearable device with a proposed T-beam absorber that can passively attenuate the tremor at various frequencies.

Analysis of tissue electrical properties on bio-impedance variation of upper limps

Upper limb loss has a significant impact on individual socioeconomic life. Human-machine interface (HMI) using surface electromyography (sEMG) establishes a link between the user and a hand prosthesis to recognize hand gestures and motions which allows the control of robotic machines and prostheses to perform dexterous tasks. Numerous methods aimed to enhance hand gesture and motion recognition toward an HMI. Bio-impedance analysis (BIA) is a noninvasive way of assessing body compositions and has been recently used for hand motion interpretation using `brute force? pattern recognition. The impedance variation in the body mostly depends on the precise stimulation using appropriate electrical features of the associated tissue layers. It has been reported that the electrical properties of these layers varied significantly. Thus, it is essential to investigate the influence of these variations on the stimulator design for the hand motion interpretation. This may not be possible using experimental approaches. Alternatively, using highly advanced computational models, this can be readily investigated by attaining the available range of the electrical properties of each tissue layer and applying appropriate boundary conditions and simulation settings. The computational models are composed of a volume conductor of the human arm model and electrode settings. Also, two different computational study methods were used to determine the influence of the tissues? dielectric properties on the results. The quasistatic approximation was used by only considering the resistivity of the anatomical layers and the transient simulation was used to analyze the capacitive impact on the results. Finite element (FE) models were developed to simulate the potential distribution inside the skin, muscle, and bone layers of the upper arm for given electrode settings. Then, simulation results were recorded for various electrical properties and different study types. It was shown that the capacitive influence of the tissue may not be ignored for certain conditions due to significant variation in the induced electrical potential variation along with the target muscle. Also, the influence of the individual tissue?s electrical properties was investigated using a set of dielectric parameters. The results showed that the skin and muscle layers have a significant impact on the electrical potential variation across the muscle length.

Wearable Blood Pressure Sensing Based on Transmission Coefficient Scattering for Microstrip Patch Antennas.

Painless, cuffless and continuous blood pressure monitoring sensors provide a more dynamic measure of blood pressure for critical diagnosis or continuous monitoring of hypertensive patients compared to current cuff-based options. To this end, a novel flexible, wearable and miniaturized microstrip patch antenna topology is proposed to measure dynamic blood pressure (BP). The methodology was implemented on a simulated five-layer human tissue arm model created and designed in High-Frequency Simulation Software “HFSS”. The electrical properties of the five-layer human tissue were set at the frequency range (2–3) GHz to comply with clinical/engineering standards. The fabricated patch incorporated on a 0.4 mm epoxy substrate achieved consistency between the simulated and measured reflection coefficient results at flat and bent conditions over the frequency range of 2.3–2.6 GHz. Simulations for a 10 g average specific absorption rate (SAR) based on IEEE-Standard for a human arm at different input powers were also carried out. The safest input power was 50 mW with an acceptable SAR value of 3.89 W/Kg < 4W/Kg. This study also explored a novel method to obtain the pulse transit time (PTT) as an option to measure BP. Pulse transmit time is based on obtaining the time difference between the transmission coefficient scattering waveforms measured between the two pairs of metallic sensors underlying the assumption that brachial arterial geometries are dynamic. Consequently, the proposed model is validated by comparing it to the standard nonlinear Moens and Korteweg model over different artery thickness-radius ratios, showing excellent correlation between 0.76 ± 0.03 and 0.81 ± 0.03 with the systolic and diastolic BP results. The absolute risk of arterial blood pressure increased with the increase in brachial artery thickness-radius ratio. The results of both methods successfully demonstrate how the radius estimates, PTT and pulse wave velocity (PWV), along with electromagnetic (EM) antenna transmission propagation characteristics, can be used to estimate continuous BP non-invasively.

On the Design and Development of Planar Monopole Antenna for Bone Crack/Void Detection

In this study, the design of a compact narrowband monopole antenna for bone crack detection is presented. The proposed antenna consists of a modified hexagon-shaped radiator with six triangular slits integrated on its bottom periphery, a rectangular-shaped ground plane, and a microstrip feed line of 50 Ω. The antenna is fabricated on the FR-4 substrate with a thickness of 1.6 mm, an overall size of 32 mm × 30 mm, and electrical dimensions of 0.13λ0 × 0.122λ0, where λ0 is the free space wavelength at 2.45 GHz. The resonant frequency of the designed antenna is 2.45 GHz. The antenna offers a gain of 1.68 dB and an efficiency of 85.3%. The presence of a crack in the bone is detected by observing the shift in the peak resonating frequency of the antenna. This method can detect bone fractures in a noninvasive manner. The human arm model is constructed, and the effect of bone cracks of different lengths on the resonating frequency is investigated. The pig bone and tissues are used to validate the simulated results. The simulated results are in agreement with the measured outcomes. Also, the specific absorption rate (SAR) of the antenna is calculated and found to be less than 0.57 W/kg. The designed monopole antenna has several advantages, including a small footprint, straightforward design, low cost, and easy integration with other devices. The proposed method is suitable for primary-level bone crack diagnosis.

Low-Profile All-Textile Multiband Microstrip Circular Patch Antenna for WBAN Applications

A compact low-profile all-textile multiband antenna operating in the 2.45&#x002F;5.8 GHz ISM bands, mobile WiMAX IEEE 802.16 2005 (3.3&#x2013;3.4 GHz), and 5G sub-6 NR frequency band n77 (3.85&#x2013;4.0 GHz) is proposed for wireless body-area network (WBAN) applications. Good broadside radiations are achieved by properly activating the inherent TM₁₁, TM_21, and TM₃₁ modes of a circular patch antenna. An elliptical slot and a C-shaped slot are employed to tune the three modes to the desired operating frequencies. A rectangular slot is used to reduce undesirable depression in the 5.8 GHz radiation pattern. The proposed antenna is fabricated from a conductive fabric layer integrated onto a single layer of denim, making it extremely low-profile and suitable for wearable applications. It has an overall size of 60 &#x00D7; 60 &#x00D7; 1.17 mm (0.64 <i>&#x03BB;_g</i> &#x00D7; 0.64 <i>&#x03BB;_g</i> &#x00D7; 0.0125 <i>&#x03BB;_g</i> at 2.45 GHz). The measured maximum realized gains and bandwidth at the four frequencies are &#x2212;0.81, &#x2212;2.81, &#x2212;1.16, 2.83 dBi, and 90, 190, 230, 570 MHz, respectively. Test results show that when the antenna is placed on and bent around a human arm model, the reflection coefficient has only slight influence. Since the antenna adopts full ground plane structure, the SAR values are far below the EU standard of 2 W&#x002F;kg limit. With merit characteristics, the proposed design indicates a promising candidate for WBAN applications.

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.

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.

Input Impedance Analysis of Wearable Antenna and Experimental Study with Real Human Subjects: Differences between Individual Users

In human body communication (HBC) systems, radio-frequency signals are excited in the human body through a wearable antenna comprised of electrodes that are in contact with the surface of the body. The input impedance characteristics of these antennas are important design parameters for increasing transmission efficiency and reducing signal reflection, similar to other wireless circuits. In this study, we discuss variations of input impedance characteristics of a wearable antenna prototype caused by differences among real human subjects. A realistic human arm model is used for simulations, and the analytical results obtained are compared to measured data obtained from real human subjects, in a range from 1 to 100 MHz. The simulations of input impedance characteristics from antennas worn on the wrists of male and female models with dry and wet skin conditions show that the impedance variation between genders is small. The moisture condition of the skin has little influence on frequencies exceeding several MHz. Measurements with a proto-type wearable antenna and 22 real human subjects reveal that HBC is robust against the variations of individual users from the viewpoint of the voltage standing wave ratio. Moreover, a simplified rectangular prism model is proposed to analyze the thickness of body tissues. Comparisons of measured input impedances indicate that individual differences in impedance are mainly due to differences in the thickness of skin and fat layers. The model also enables us to design the antenna prototype without multiple subject experiments.

Upper-Limb Kinematic Parameter Estimation and Localization Using a Compliant Robotic Manipulator

Assistive and rehabilitation robotics have gained momentum over the past decade and are expected to progress significantly in the coming years. Although relevant and promising research advances have contributed to these fields, challenges regarding intentional physical contact with humans remain. Despite being a fundamental component of assistive and rehabilitation tasks, there is an evident lack of work related to robotic manipulators that intentionally manipulate human body parts. Moreover, existing solutions involving end-effector robots are not based on accurate knowledge of human limb dimensions and their current configuration. This knowledge, which is essential for safe human-limb manipulation, depends on the grasping location and human kinematic parameters. This paper addresses the upper-limb manipulation challenge and proposes a pose estimation method using a compliant robotic manipulator. To the best of our knowledge, this is the first attempt to address this challenge. A kinesthetic-based approach enables estimation of the kinematic parameters of the human arm without integrating external sensors. The estimation method relies only on proprioceptive data obtained from a collaborative robot with a Cartesian impedance-based controller to follow a compliant trajectory that depends on human arm kinodynamics. The human arm model is a 2-degree of freedom (DoF) kinematic chain. Thus, prior knowledge of the arm's behavior and an estimation method enables estimation of the kinematic parameters. Two estimation methods are implemented and compared: i) Hough transform (HT); ii) least squares (LS). Furthermore, a resizable, sensorized dummy arm is designed for experimental validation of the proposed approach. Outcomes from six experiments with different arm lengths demonstrate the repeatability and effectiveness of the proposed methodology, which can be used in several rehabilitation robotic applications.

Upper body estimation of muscle forces, muscle states, and joint motion using an extended Kalman filter

This study synthesises modelling techniques and dynamic state estimation techniques for the simultaneous estimation of the muscle states, muscle forces, and joint motion states of a dynamic human arm model. The estimator considers both muscle dynamics and motion dynamics. The arm model has two joints and six muscles and contains dynamics both of the muscles and of the motion. We develop an optimally tuned extended Kalman filter using noisy measurements of joint angles with standard deviation 2.87 °, of joint velocities with standard deviation 6.9 °/s, and of muscle activations with standard deviation 10% of their peak values, and then simultaneously estimate joint angles, joint velocities, muscle forces, joint moments, and muscle states. The standard deviations of estimation errors (SDEE) are no more than 0.07° for joint angles, 1 °/s for joint velocities, 0.6 mm for muscle–tendon lengths, and 0.1 Nm for joint torques. The results are compared with a previously developed static optimisation method, and verify the effectiveness of the proposed estimator in providing lower SDEE for both muscle and motion dynamics of the human arm model compared to the static optimisation method.

Muscle Synergy Control During Hand Reach Task on Varying Shoulder Configuration.

Control of human arm in reaching task is a result of complex neural interaction involving central nervous and musculoskeletal system, where, group of muscle activation are planned through synergistic and coordinated recruitment, often to reach an optimal strategy. Aim of this paper is to explore muscle synergy distribution on several reaching task of similar elbow trajectory but changing shoulder configuration. A musculoskeletal model of human arm comprising shoulder, elbow and wrist joint have been designed and is used to calculate muscle activation required to perform three specific reaching tasks. Muscle synergy have been computed on the simulated activation to find a relation between synergy and energy requirement with the change of rotation and elevation of shoulder and its effect on the motion path of the elbow joint. These findings may help to define optimal joint configuration for a planned range of motion during rehabilitation exercises and also in developing neural prosthesis and myoelectric interfaces for efficient arm motion control.

A projected primal-dual gradient optimal control method for deep reinforcement learning

In this contribution, we start with a policy-based Reinforcement Learning ansatz using neural networks. The underlying Markov Decision Process consists of a transition probability representing the dynamical system and a policy realized by a neural network mapping the current state to parameters of a distribution. Therefrom, the next control can be sampled. In this setting, the neural network is replaced by an ODE, which is based on a recently discussed interpretation of neural networks. The resulting infinite optimization problem is transformed into an optimization problem similar to the well-known optimal control problems. Afterwards, the necessary optimality conditions are established and from this a new numerical algorithm is derived. The operating principle is shown with two examples. It is applied to a simple example, where a moving point is steered through an obstacle course to a desired end position in a 2D plane. The second example shows the applicability to more complex problems. There, the aim is to control the finger tip of a human arm model with five degrees of freedom and 29 Hill’s muscle models to a desired end position.

Design and Analysis of Fractal Based Monopole Antenna Backed with Modified Jerusalem Cross Frequency Selective Surface for Wireless Personal Area Communications

This paper presents a low profile Single-layer Modified Jerusalem Cross Frequency Selective Surface (SMJC FSS) which functions as a band-stop filter to shield the 2.45 GHz Industrial, Scientific and Medical (ISM) band with a unit cell size of 0.249λg × 0.249λg × 0.027λg. Compared to JC FSS, 50% size reduction is achieved by the effect of capacitive and inductive loading. The proposed FSS exhibits a fractional bandwidth of 14.69% and fractional bandwidth dimension ratio (FBDR) of 8775.4, which is one of the highest among the single layer FSS. The Koch curve inspired fractal monopole antenna is backed by 5 × 5 FSS array, which contributes enhanced gain and fractional bandwidth of 6.28 dB and 23.75% respectively and has a net dimension of 75 × 75mm ×31.2 mm. The specific absorption rate (SAR) is analyzed on human arm model where proposed antenna attains 0.183 W/Kg, which makes it appropriate for the application of body area communication. The measured results agree well with the simulated results and hence it is validated for wireless personal area communications in the ISM band at 2.45 GHz.

Electrical Impedance Myography Applied to Monitoring of Muscle Fatigue During Dynamic Contractions

Muscle fatigue, as a common physiological phenomenon, has attracted much attention in the fields of rehabilitation and athletic training. A wearable technology for monitoring the muscle fatigue anytime and anywhere is urgently needed. In this paper we apply Electrical impedance myography (EIM) technique, usually used for non-invasive detection of neuromuscular diseases with the four-electrode array, for evaluation of the local muscle fatigue status via the variation of electrical impedance. An equivalent multilayer inhomogeneous 3D finite element model of human arm was built in order to optimize the four-electrode configuration to improve EIM detection sensitivity. Current density in muscle layer and differential potential of induction electrodes were selected as the evaluation indexes for optimization. Then the in vivo experiments of dynamic contraction with different maximal voluntary contractions (MVC) were performed on the biceps brachii muscle of eight healthy volunteers. The results showed that muscle resistance ( $R$ ) decreased almost $8~\Omega $ from the completely relaxed muscle to exhaustion, which is the same trend as for the median frequency (MF) of measured surface electromyography (sEMG) signals. The model and experiments in this paper indicate the feasibility and efficiency of EIM for detection of muscle fatigue using wearable devices.

Combination of reinforcement learning and bee algorithm for controlling two-link arm with six muscle: simplified human arm model in the horizontal plane.

The aim of this study was to improve reinforcement learning algorithm by combining artificial bee colony algorithm. The traditional method of reinforcement learning algorithm has a very low convergence rate due to random choices. An ant algorithm will help to make random choices in reinforcement learning more appropriate. This hybrid algorithm called the bee colony reinforcement (BCR) algorithm. The tip of the arm must reach a predetermined purpose by BCR algorithm. The results show that the BCR algorithm in the model has been able to reduce the time to reach the goal than the reinforcement learning algorithm (In average 12 steps faster). Also, the path for reaching the goal in the BCR algorithm was far more direct and shorter than the reinforcement learning algorithm. This method also detects the optimal path towards the goal.