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Upper limb rehabilitation robot can assist stroke patients to complete daily activities to promote the recovery of upper-limb motor functions. However, the robot uncertainty and the patient’s unconscious disturbance impose great difficulties on the high-performance trajectory tracking of the rehabilitation robot. In this paper, an uncertainty compensated high-order adaptive iterative learning controller (UCHAILC) is proposed to reduce the impact of uncertainty from inside and outside of the robot during the rehabilitation process. The nonlinear system is converted into a dynamic linearization model with uncertainty compensation, and the optimization criterion method is adopted to estimate the pseudo-partial derivative (PPD) parameters and the uncertainty respectively, then the previous iterations are used to update the current parameters through a high-order learning scheme. The convergence of UCHAILC is theoretically proved. Simulation and control experiments on a rehabilitation robot are given to validate the effectiveness of the proposed method, which is significant to improve the training security and physiotherapy effect of robot-assisted rehabilitation. Note to Practitioners—This paper was motivated by the need to assist stroke patients to restore motor function for executing daily activities. The inherent difficulties lie in reducing the tracking errors of rehabilitation robots caused by uncertainty and involuntary disturbance from patients to avoid secondary injury. The proposed UCHAILC can transform the complex nonlinear system into a dynamic linear model with uncertainty compensation, then the PPD parameters and uncertainty are estimated through high-order learning law. Theoretical analysis, simulation, and experiments verified the feasibility of the method. Furthermore, the proposed controller is not limited to the dynamic model and hardware driving mode of the robot system, which can be easily transplanted to other nonlinear control systems with uncertainties.

Gait phase detection holds great importance in the field of human activity detection and medical rehabilitation, but at present, gait recognition technology still has the disadvantages of insufficient portability and high cost. Gait recognition based on pressure pad measurement limits the subjects to a small space, while gait recognition based on inertial measurement units (IMUs) or electromyography (EMG) sensing is difficult to improve recognition performance due to single-sensor or single-feature extraction model. Besides, complex neural networks also have some problems, such as lack of timeliness and redundant parameters. In this study, multisensor data and multiple classifiers are utilized to extract abundant gait features. We have developed a flexible insole utilizing fiber Bragg grating (FBG), combined with acceleration sensors and EMG sensors to accurately recognize various gait phases, including loading response (LR), mid-stance (MS), terminal stance (TS), preswing (PSw), and swing. Feature extraction from plantar pressure data and inertial data was performed using an error-correcting output coding support vector machine (ECOC-SVM) model. In addition, a deep convolutional neural network with a squeeze-excitation module (DCNN-SE) was employed for feature extraction from EMG data. Finally, gait phase detection based on multisensor data and multiple classifiers was achieved through weighted discrimination algorithms. Experimental results demonstrate that the prepared flexible insole effectively detects changes in plantar pressure with exceptional robustness and maintainability. Furthermore, the fusion model significantly enhances gait phase detection accuracy up to 96.00%, which lays a foundation for intention perception during human walking and robot walking control.

With the constant evolution of information technology, the paradigm of human-computer interaction has progressively transitioned from emphasizing command behavior to a novel approach that prioritizes natural language and emotional communication. In response to this trend, the development of an effective model for emotion recognition has become imperative. Consequently, this article introduces a novel multi-axis EEG channel attention model (MECAM) designed for emotion recognition. To enhance the model’s capabilities, we employ a split depth-wise convolution with a larger convolutional kernel, resulting in the creation of four parallel branches. This not only reduces the computational complexity but also expands the receptive field of the model. The incorporation of a multi-axis attention mechanism, capturing both global and local information from the output features of parallel branches, further elevates the network’s receptive field through the MBConv block. The primary objective of MECAM is to adeptly extract discriminative features from electroencephalogram (EEG) data, thereby enhancing the performance of emotion recognition. The model underwent rigorous validation using multiple datasets, including database for emission analysis using physical signals (DEAPs), SJTU emission EEG dataset (SEED), and SJTU emission EEG dataset with four emission (SEED-IV). In subject-dependent experiments, the accuracy of binary and ternary emotion classification tasks exceeded 95%, while the accuracy of the quaternary classification task surpassed 93%. In subject-independent experiments, the accuracy of most emotion classification tasks also exceeded 90%, with the exception of quaternary classification on DEAP, achieving an accuracy of 86.64%. The experimental results unequivocally underscore the superior performance of MECAM in EEG-based emotion recognition tasks.

Robot-assisted rehabilitation, which can provide repetitive, intensive, and high-precision physics training, has a positive influence on the motor function recovery of stroke patients. Current robots need to be more intelligent and more reliable in clinical practice. Machine learning algorithms (MLAs) are able to learn from data and predict future unknown conditions, which is of benefit to improve the effectiveness of robot-assisted rehabilitation. In this article, we conduct a focused review on machine learning-based methods for robot-assisted upper limb rehabilitation. First, the current status of upper rehabilitation robots is presented. Then, we outline and analyze the designs and applications of MLAs for upper limb movement intention recognition, human–robot interaction control, and quantitative assessment of motor function. Meanwhile, we discuss the future directions of MLAs-based robotic rehabilitation. This review article provides a summary of MLAs for robotic upper limb rehabilitation and contributes to the design and development of future advanced intelligent medical devices.

While newer designs and control approaches are being proposed for rehabilitation robots, vital information from the human musculoskeletal system should also be considered. Incorporating knowledge about joint biomechanics during the development of robot controllers can enhance the safety and performance of robot-aided treatments. In this article, the optimal path or trajectories of a parallel ankle rehabilitation robot were generated by minimizing joint reaction moments and the tension along ligaments and muscle-tendon units. The simulations showed that using optimized robot paths, user efforts could be reduced to 80%, thereby ensuring less strain on weaker or stiffer ligaments, etc. Additionally, to limit the moments applied by the robot in stiff or constrained directions, the intended robot path was modified to move the commanded position in the direction opposite to that of the position error. Such online modification of the robot path can lead to a reduction in forces applied by a robot to the subject. Simulation results and experimental findings with healthy subjects using an ankle rehabilitation robot prototype and subsequent statistical analysis further validated that path modification based on ankle joint biomechanics results in a reduction in undesired forces experienced by human users during treatment.

Steady state visual evoked potentials (SSVEP) are less vulnerable to noise than other kinds of electroencephalography (EEG) signals and have therefore recently become popular in brain computer interface (BCI) applications. This paper firstly demonstrates an online asynchronous analogue (variable level) SSVEP-based BCI for lower limb rehabilitation in which the movement of robotic exoskeleton is continuously controlled by the user's intent. Such patient participation has proved to be one of the most important factors for rehabilitating the neural system after injury or stroke. Three new and different training protocols are developed specially for rehabilitation exercise and tested with the proposed adjacent narrow band-pass filter (ANBF) method. Results with six participants are presented with accuracy to within a knee angle of 1° after simple training. For the ANBF method with 0.3 Hz filter spans, the overall average recognition accuracy is 95.98% ± 4.15% and the overall average net latency is 2.84 ± 0.61 seconds. For the ANBF method with 0.1 Hz filter spans, the overall average recognition accuracy is 98.91% ± 1.50% and the overall average net latency is 4.29% ± 0.50% seconds. This gives much promise to future development of brain controlled rehabilitation devices.

Iterative feedback tuning (IFT) is a model-free tuning method that has been proven to work well in various applications since its introduction in 1994. Several factors affect the performance of the optimization process, and one of which is the design criterion. Historically, the weighting factor for each element in the design criterion is chosen by trial and error and results in a different value for each system tested. In this paper, a normalized design criterion is presented with a weighting factor that allows the tuning performance to be assessed across different systems. This new design criterion is then applied to various test systems using the Monte Carlo method to determine the optimal range of values of this normalized weighting factor in tuning for step input responses.

A precise and robust controller has been developed and implemented on a novel ionic polymer–metal composite (IPMC) actuated micro–manipulator to demonstrate its ability to enable safe and reliable manipulation of biological cells. A 2 degree–of–freedom (2DOF) control structure was employed to enable the system to be optimised for both the disturbance response (DR) and set–point (SP) tracking. The controller is adaptively tuned using a model–free iterative feedback tuning (IFT) approach which is ideal for operation in unknown cellular environments and handling the time–varying behaviour of the IPMCs themselves. IFT experiments have tuned the IPMCs to an 87% and 81% performance improvement in DR and SP respectively. Experiments then reveal that the tuned controller has equipped the manipulator with an accuracy of <7.1% of full scale, with up to 7° of motion in both axes. The controller has also demonstrated its ability to naturally cope with load disturbances up to 10 mN.

This paper proposes a vision-based embedded motion control system that is developed in our research group. The system is an integration of three subsystems including, an embedded positioning platform, a vision system for inspection and a crystal reorientation system. The system is used as a positioning platform and crystal reorientation system to automate the crystal reorientation process. This process is important in ensuring that the units are correctly oriented for production processes. The focus of this research is placed on how to develop the embedded positioning platform, the crystal reorientation system, and how to improve the system performances including positioning and reorientation accuracy in high speed operation and quality of inspection. A distributed control architecture has been developed using PIC18F4520 microcontrollers. Tests run on the complete system have shown that the system is capable of a minimum indexing time of 1.53 units per second and a reorientation time of 1.42 seconds.

This paper presents the design, fabrication and experimental characterization of a valveless micropump actuated by an ionic-polymer-metal-composite (IPMC) soft actuator. The performance of the IPMC varies over time, therefore on-line iterative feedback tuning (IFT) is used to adaptively tune the PID controller to control the bending deflection of the IPMC to ensure a constant pumping rate. The pump rate is higher at lower frequencies for a given applied voltage to the IPMC. A maximum flow rate of 130 l/min is achieved at 0.1 Hz.

The demand for single cell manipulation to allow scientist to carry out medical researcher is fast increasing. To facilitate this advanced manipulation systems are required to permit both precise and safe handling of the biological cells. Current devices can achieve a high level of precision at the micro/nano scale but as a consequence are highly rigid and this stiffness puts the target cells at risk as there is no compliance or back-drivability. Ionic polymer-metal composites (IPMCs) are naturally compliant, giving them a 'soft touch', and now with recent advances in their fabrication and control IPMCs are showing major promise as safe and accurate cell manipulators. This paper presents the development of an optimally tuned force controller for a 2 degree-of-freedom (2DOF) IPMC actuated micro-manipulator. The control system has been implemented to demonstrate the ability to control the manipulator's applied force as a step towards implementing a truly safe system with active compliance control. The controller is adaptively tuned using a model-free iterative feedback tuning (IFT) approach which is ideal for operation in unknown cellular environments as well as for controlling the complex time-varying behavior of the IPMC actuators themselves. The IFT algorithm tunes the force controller by minimizing the design criteria, a least squares error, by 25% in the horizontal direction and 46% in the vertical direction. Experiments then show that the manipulator can accurately track a reference trajectory up to 4gf or ~40mN in both DOF.

AbstractThis paper uses a discrete event simulation model to compare a number of different maintenance policies applied to high-value, repairable assets subject to age-related failure modes with particular reference to aero-engines on civil aircraft. The policies considered range from one of allowing components to fail before doing any maintenance through various forms of opportunistic maintenance to full preventative maintenance by setting hard lives to drive assets into maintenance. The conclusions reached are that setting soft lives tends to be more cost effective than hard lives but using target build lives (a method described in more detail within) tends to be even better. Simply waiting for parts to fail is only sensible if the cost of arisings is negligible. For airlines, engine failures are likely to result in diversions, delays and cancellations as well as customer dissatisfaction and potentially litigation, all of which can be extremely expensive.

This paper uses a discrete event simulation model to compare a number of different maintenance policies applied to high-value, repairable assets subject to age-related failure modes with particular reference to aero-engines on civil aircraft. The policies considered range from one of allowing components to fail before doing any maintenance through various forms of opportunistic maintenance to full preventative maintenance by setting hard lives to drive assets into maintenance. The conclusions reached are that setting soft lives tends to be more cost effective than hard lives but using target build lives (a method described in more detail within) tends to be even better. Simply waiting for parts to fail is only sensible if the cost of arisings is negligible. For airlines, engine failures are likely to result in diversions, delays and cancellations as well as customer dissatisfaction and potentially litigation, all of which can be extremely expensive.

Immobilized pH gradients isoelectric focusing (IPG-IEF) is the first dimension typically used in two-dimensional gel electrophoresis (2-DE). It can also be used on its own in conjunction with tandem mass spectrometry (MS/MS) for the analysis of proteins. Here, we described a strategy combining isoelectric focusing in immobilized pH gradient strips, and mass spectrometry to create a new high-throughput and sensitive detection method. Protein mixture is separated by in-gel IEF, then the entire strip is cut into a set of gel sections. Proteins in each gel section are digested with trypsin, and the resulted peptides are subjected to reversed-phase high performance liquid chromatography followed by electrospray-linear ion-trap tandem mass analysis. Using this optimized strategy, we have identified 744 distinct human proteins from an IPG strip loaded only 300 μg of plasma proteins. When compared with other works in published literatures, this study offered a more convenient and sensitive method from gel to mass spectrometry for the separation and identification proteins of complex biological samples. Keywords: plasma • immobilized pH gradients • isoelectric focusing • proteomics • linear ion trap mass spectrometry

Due to the complexity of proteomes, developing methods of sample fractionation, separation, concentration, and detection have become urgent to the identification of large numbers of proteins, as well as the acquisition of those proteins in low abundance. In this work, liquid isoelectric focusing (LIEF) combined with 2D-LC−MS/MS was applied to the proteome of Saccharomyces cerevisiae. This yielded a total of 1795 proteins that were detected and identified by 30 fractions of protein prefractioantion. Categorization of these hits demonstrated the ability of this technology to detect and identify proteins rarely seen in proteome analysis without protein fractiontion. LIEF-2D-LC−MS/MS also produced improved resolution of low-abundance proteins. Furthermore, we analyzed the characteristics of proteins obtained by LIEF-2D-LC−MS/MS. 1103 proteins with CAI under 0.2 were identified, allowing us to specifically obtain detailed biochemical information on these kind proteins. It was observed that LIEF-2D-LC−MS/MS is useful for large-scale proteome analysis and may be specifically applied to systems with wide dynamic ranges. Keywords: large-scale proteome • fractionation • liquid isoelectric focusing (LIEF) • 2D-LC−MS/MS • low-abundance proteins

The proteomes of the severe acute respiratory syndrome-associated coronavirus (SARS-CoV) and its infected Vero E6 cells were detected in the present study. The cytosol and nucleus fractions of virus-infected cells as well as the crude virions were analyzed either by one-dimensional electrophoresis followed by ESI−MS/MS identification or by shotgun strategy with two-dimensional liquid chromatography-ESI−MS/MS. For the first time, all of the four predicted structural proteins of SARS-CoV were identified, including S (Spike), M (Membrane), N (Nucleocapsid), and E (Envolope) proteins. In addition, a novel phosphorylated site of M protein was observed. The combination of these gel-base and non-gel methods provides fast and complimentary approaches to SARS-CoV proteome and can be widely used in the analysis of other viruses. Keywords: coronavirus • proteome • mass spectrometry • glycosylation • phosphorylation

Motivation: Gibbs sampling has become a method of choice for the discovery of noisy patterns, known as motifs, in DNA and protein sequences. Because handling noise in microarray data presents similar challenges, we have adapted this strategy to the biclustering of discretized microarray data.
Results: In contrast with standard clustering that reveals genes that behave similarly over all the conditions, biclustering groups genes over only a subset of conditions for which those genes have a sharp probability distribution. We have opted for a simple probabilistic model of the biclusters because it has the key advantage of providing a transparent probabilistic interpretation of the biclusters in the form of an easily interpretable fingerprint. Furthermore, Gibbs sampling does not suffer from the problem of local minima that often characterizes Expectation-Maximization. We demonstrate the effectiveness of our approach on two synthetic data sets as well as a data set from leukemia patients.
Contact: qizheng.sheng@esat.kuleuven.ac.be

Abstract: The thermogenic curves of the aerobic metabolism of the three strains of Bacillus thuringiensis B.t. A, B.t. B and B.t. C have been determined by using an LKB-2277 BioActivity Monitor. B.t. A was the host bacterium without foreign gene. B.t. B and B.t. C were constructed by transforming different foreign genes into the host B.t. A, respectively. B.t. B expressed erythromycin resistant gene, while B.t. C expressed both erythromycin resistant gene and tyrosinase gene. The heat flow rate of these strains is B.t. A> B.t. B >B.t. C. These results indicated that there is obvious interrelation between expression of foreign genes and heat flow rate of B.t. strains.

In this paper, a promoter-probe plasmid pKK232-8 was used as a vector, which functioned in Escherichia coliTG1host. The plasmid DNA fragments from Pseudomonas maltophiliaAT18 chromosome DNA active as promoter inEscherichia coliTG1, the promoter function was studied by means of microcalorimetry, the promoter is about 800 bp DNA, it can promote the chloramphenicol (Cm) gene in plasmid pKK232-8, the Cm resistance level is about 80 μg mL–1, the promoter activity is high. It implicates that there are probably many promoters in Pseudomonas maltophiliaAT18 chromosome. All these information is readily obtained by an LKB 2277-204 heat conduction microcalorimeter. Microcalorimetry is a quantitative, inexpensive, and versatile method for microbiological genetic research.

This paper is concerned with a new conservative finite difference method for solving the generalized nonlinear Schrödinger (GNLS) equation iut+uxx+f(⊢u⊢2)u=0. The numerical scheme is constructed through the semidiscretization and an application of the quartic spline approximation. Central difference and extrapolation formulae are used for approximating the Neumann boundary conditions introduced. Both continuous and discrete energy conservation and the stability property are investigated. The numerical method provides an efficient and reliable way for computing long-time solitary solutions given by the GNLS equation. Numerical examples are given to demonstrate our conclusions.

A predictor–corrector scheme is developed for the numerical solution of the sine‐Gordon equation using the method of lines approach. The solution of the approximating differential system satisfies a recurrence relation, which involves the cosine function. Pade' approximants are used to replace the cosine function in the recurrence relation. The resulting schemes are analyzed for order, stability, and convergence. Numerical results demonstrate the efficiency and accuracy of the predictor–corrector scheme over some well‐known existing methods. © 2000 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 16: 133–146, 2000

A predictor–corrector scheme is developed for the numerical solution of the sine-Gordon equation using the method of lines approach. The solution of the approximating differential system satisfies a recurrence relation, which involves the cosine function. Pade' approximants are used to replace the cosine function in the recurrence relation. The resulting schemes are analyzed for order, stability, and convergence. Numerical results demonstrate the efficiency and accuracy of the predictor–corrector scheme over some well-known existing methods. © 2000 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 16: 133–146, 2000

A predictor–corrector scheme is developed for the numerical solution of the sine-Gordon equation using the method of lines approach. The solution of the approximating differential system satisfies a recurrence relation, which involves the cosine function. Pade' approximants are used to replace the cosine function in the recurrence relation. The resulting schemes are analyzed for order, stability, and convergence. Numerical results demonstrate the efficiency and accuracy of the predictor–corrector scheme over some well-known existing methods. © 2000 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 16: 133–146, 2000

A predictor–corrector scheme is developed for the numerical solution of the sine-Gordon equation using the method of lines approach. The solution of the approximating differential system satisfies a recurrence relation, which involves the cosine function. Pade' approximants are used to replace the cosine function in the recurrence relation. The resulting schemes are analyzed for order, stability, and convergence. Numerical results demonstrate the efficiency and accuracy of the predictor–corrector scheme over some well-known existing methods. © 2000 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 16: 133–146, 2000

Quenching phenomena play important roles in both steady and unsteady combustion processes. This article studies a compound finite difference method for solving a nonlinear degenerate combustion model problem. The approach combines procedures of semidiscretization, adaptive ODE solver, and highly stable rational approximation for handling the spatial degeneracy and quenching singularity involved. A second‐order adaptive scheme is constructed, which provides monotone convergence of the numerical solution and direct computations of critical quenching values. It has a simple, yet accurate and reliable, structure and is easy to use. We further demonstrate advantages of the scheme by comparing it to existing algorithms. Numerical examples are presented to further strengthen our results. © 1999 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 15: 29–47, 1999

Short carbon fibre-reinforced polyimide composites were prepared by wet impregnating chopped short carbon fibres with PMR-type polyimide matrix resin solution followed by evaporating the solvent with strong stirring. The processing properties of the prepolymer moulding powders were investigated. The mechanical properties and thermo-oxidative stability of the fabricated composite were also studied. Experimental results demonstrate that the short fibre filled moulding powders exhibit good melt resin flowing characteristics and can be processed by a hot press moulding technique to produce small-size, complicated composite structures which are difficult to produce using continuous fibre-reinforced composite prepregs by an autoclave technique. The composites exhibit outstanding mechanical properties and excellent thermal and thermo-oxidative stabilities at temperatures as high as 320 °C.

Quenching phenomena play important roles in both steady and unsteady combustion processes. This article studies a compound finite difference method for solving a nonlinear degenerate combustion model problem. The approach combines procedures of semidiscretization, adaptive ODE solver, and highly stable rational approximation for handling the spatial degeneracy and quenching singularity involved. A second-order adaptive scheme is constructed, which provides monotone convergence of the numerical solution and direct computations of critical quenching values. It has a simple, yet accurate and reliable, structure and is easy to use. We further demonstrate advantages of the scheme by comparing it to existing algorithms. Numerical examples are presented to further strengthen our results. © 1999 John Wiley & Sons, Inc. Numer Methods Partial Differential Eq 15: 29–47, 1999

Assuming the smoothness and a generalized Lipschitz condition we establish the existence and uniqueness of the periodic solutions of higher order nonlinear hyperbolic partial differential equations.Copyright 1994, 1999 Academic Press, Inc.

Tumor suppressors of the retinoblastoma susceptibility gene family regulate cell growth and differentiation. Polyomavirus large T antigens (large T) bind Rb family members and block their function. Mutations of large T sequences conserved with the DnaJ family affect large T binding to a cellular DnaK, heat shock protein 70. The same mutations abolish large T activation of E2F-containing promoters and Rb binding-dependent large T activation of cell cycle progression. Cotransfection of a cellular DnaJ domain blocks wild-type large T action, showing that the connection between the chaperone system and tumor suppressors is direct. Although they are inactive in assays dependent on Rb family binding, mutants in the J region retain the ability to associate with pRb, p107, and p130. This suggests that binding of Rb family members by large T is not sufficient for their inactivation and that a functional J domain is required as well. This work connects the DnaJ and DnaK molecular chaperones to regulation of tumor suppressors by polyomavirus large T.

We propose a new two-electron band theory approach to treat correlated f-electron systems. This involves: first, an exact two-body treatment of the local correlations for a 'solid-state atom', i.e. non-spherical local environment of a cerium (or other pertinent) nucleus; then, turning on the interactions giving extended two-electron states (bands). This approach treats the hybridization and exchange Coulomb interaction effects within this two-body treatment on an equal footing. Without invoking the concept of Kondo resonance, it provides a non-magnetic singlet state competing, side by side with other, magnetic states. It explains the wide diversity in f magnetism and the heavy fermion phenomenology, including the specific heat and susceptibility, and most significant, provides an absolute prediction of the Wilson ratio, reproducing the experimental scale and trend in change of the Wilson (low-temperature susceptibility to specific heat) ratio on going from non-magnetic to magnetic heavy fermion materials.

The oxidation of poly(4-methylstyrene) with cerium(IV) and cobalt(III) complexes in glacial acetic acid introduces functional groups selectively into the 4-methyl position. The polymer backbone methine groups are almost completely protected from oxidation due to stereo-electronic effects. The reaction proceeds by double electron transfer to give intermediate polymeric benzyl cations. These combine with nucleophiles present in the reaction mixture, such as acetic acid, trichloroacetic acid, or nitrate, to give polymeric benzyl acetates, benzyl trichloroacetates, and benzyl nitrates. These substituents can be exchanged for each other, leading to poly(4-methylstyrenes) containing between 10 and 45% of a single reactive leaving group. The effects of reaction conditions on oxidation yields and selectivity are described.

Ce3+‐doped oxide glass with high Gd2O3(30 mol%) concentration was prepared as a scintillating glass under CO reducing atmosphere. A dominant emission band of the Ce3+5d → 4f transition peaking around 400 nm was observed in the photo‐ and radioluminescence (PL, RL) spectra. PL decay was governed by a few tens of nanoseconds decay time. The integral scintillation efficiency of about 30% of the Bi4Ge3O12scintillator was observed as well. It exhibits a light yield of about 910 photons/MeV with an energy resolution of 18.3% (FWHM) in the pulse height spectrum of 662 keV γ‐rays from a 137Cs source.

This paper proposes a pneumatic upper limb rehabilitation robot (PULRR) which is designed for bilateral upper limb active rehabilitation of the patients after stroke. The PULRR provides an active resistance rehabilitation method based on the pneumatic control system. The air kinetics of the pneumatic cylinder model and the dynamics of the pneumatic system with load are established. An antisaturation proportional-integral-differential (PID) controller is presented for the constant resistance force control through directly adjusting the position of the throttle valve spool according to the patient's active moving speed and the feedback of the air pressure in both chambers. In addition, simulation and experimental results indicate that the controller is effective in constant resistance force control. The resistance mode proposed in this paper shows great potential in active resistance rehabilitation for the patients who suffer from the dyskinesia and insufficient muscle strength of the upper limb with enhanced safety and compliance.