Interaction Control for Human-Exoskeletons

Upper limb exoskeletons have drawn significant attention in neurorehabilitation because of the anthropomorphic mechanical structure analogous to human anatomy. Whereas, the training movements are typically unorganized because most exoskeletons ignore the natural movement characteristic of human upper limbs, particularly inter-joint postural synergy. This paper introduces a newly developed exoskeleton (Armule) for upper limb rehabilitation with a postural synergy design concept, which can reproduce activities of daily living (ADL) motion with the characteristics of human natural movements. The semitransparent active control strategy with the interactive force guidance and visual feedback ensured the active participation of users. Eight participants with hemiplegia due to a first-ever, unilateral stroke were recruited and included. They participated in exoskeleton therapy sessions for 4 weeks, with passive/active training under trajectories and postures with the characteristics of human natural movements. The primary outcome was the Fugl-Meyer Assessment for Upper Extremities (FMA-UE). The secondary outcomes were the Action Research Arm Test(ARAT), modified Barthel Index (mBI), and metric measured with the exoskeleton After the 4-weeks intervention, all subjects showed significant improvements in the following clinical measures: the FMA-UE (difference, 11.50 points, p = 0.002), the ARAT (difference, 7.75 points ), and the mBI (difference, 17.50 points, p = 0.003 ) score. Besides, all subjects showed significant improvements in kinematic and interaction force metrics measured with the exoskeleton. These preliminary results demonstrate that the Armule exoskeleton could improve individuals' motor control and ADL function after stroke, which might be associated with kinematic and interaction force optimization and postural synergy modification during functional tasks.

Repetitive task training (RTT) involves the active practice of task-specific motor activities and is a component of current therapy approaches in stroke rehabilitation.1 Primary objective is to determine whether RTT improves upper limb function/reach and lower limb function/balance in adults after stroke. Secondary objectives are (1) to determine the effect of RTT on secondary outcome measures, including activities of daily living, global motor function, quality of life/health status, and adverse events, (2) to determine the factors that could influence primary and secondary outcome measures, including the effect of dose of task practice, type of task (whole therapy, mixed, or single task), and timing of the intervention and type of intervention. We searched the Cochrane Stroke Group …

Powered exoskeletons can provide motion enhancement for both healthy and physically challenged people. Compared with lower limb exoskeletons, upper limb exoskeletons are required to have multiple degrees-of-freedom and can still produce sufficient augmentation force. Designs using serial mechanisms usually result in complicated and bulky exoskeletons that prevent themselves from being wearable. This paper presents a new exoskeleton aimed to achieve compactness and wearability. We consider a shoulder exoskeleton that consists of two spherical mechanisms with two slider crank mechanisms. The actuators can be made stationary and attached side-by-side, close to a human body. Thus better inertia properties can be obtained while maintaining lightweight. The dimensions of the exoskeleton are synthesized to achieve maximum output force. Through illustrations of a prototype, the exoskeleton is shown to be wearable and can provide adequate motion enhancement of a human's upper limb.

Introduction: Impaired balance is one of the primary causes of functional limitations. Related to sensory deficits specifically, balance disorder in stroke may be caused by decreased central integration of sensory cues, including somatosensory, visual and vestibular input. Case Presentation: This case describes a 23-year-old male with bilateral thalamic stroke following surgical resection of a recurring optic nerve meningioma. He had a complex medical history and is legally blind. He presented to outpatient neurorehabilitation 5 months following his stroke. He demonstrated absent light touch sensation and absent proprioception and kinesthetic awareness in his upper extremities, lower extremities, and trunk. Secondary to absent proprioception and vision and significant impairments related to shunt malfunction, he required total assistance for all mobility at initial examination. Discussion: After 8 months of intensive rehabilitation, he demonstrated substantial improvements in all functional mobility and recovery of sensation. Rehabilitation included interventions such as electrical stimulation, fluidotherapy, repetitive task training, and most significantly, external augmented feedback. This feedback included sensory cues, auditory and tactile cues, and maximizing the use of vestibular input. This case demonstrates that neurorehabilitation can benefit patients with impaired use of sensory cues and central integration.

As one of the research hotspots in the field of rehabilitation robotics, the upper limb exoskeleton robot has been widely used in the field of rehabilitation. However, the existing methods cannot comprehensively and accurately reflect the motion state of patients, which may lead to overtraining and secondary injury of patients in the process of rehabilitation training. In this paper, an upper limb exoskeleton control method based on mixed perception model of motion intention and intensity is proposed, which is based on the 6 degree-of-freedom upper limb rehabilitation exoskeleton in the laboratory. First, the kinematic information and heart rate information in the rehabilitation process of patients are collected, corresponding to patients’ motion intention and motion intensity, and fused to obtain the mixed perception vector. Second, the motion perception model based on long short-term memory neural network is established to realize the prediction of upper limb motion trajectory of patients and compared with back-propagation neural network to prove its effectiveness. Finally, the control system is built, and both offline and online test of the control method proposed are implemented. The experimental results show that the method can achieve comprehensive motion state perception of patients, realize real-time and accurate prediction trajectory according to human motion intention and intensity. The average prediction accuracy is 95.3%, and predicted joint angle error is less than 5 degrees. Therefore, the control method based on mixed perception model has good robustness and universality, which provides a new method for the active control of upper limb exoskeleton.

The upper limb exoskeleton has the advantages of high durability, low labor intensity, and repeatability, and has broad application prospects in stroke rehabilitation. Aiming at the incompatibility of the upper limb exoskeleton robotic with the human, an upper limb exoskeleton rehabilitation robot (ULERR) was designed. Firstly, according to the human anatomy, the joint configuration of human upper limbs is analyzed. The ULERR is designed for the rehabilitation training of patients with hemiplegia in the middle and late stages caused by stroke. Secondly, it is established the kinematics and dynamics model of the exoskeleton and completed the analysis of dynamic simulation. Finally, the rehabilitation robot prototype was tested by a 3D dynamic capture system to measure the range of motion (ROM) of the upper limb joints with the rehabilitation robot. Finally, the results of simulation and experimental concluded that joint motion of the robot is stable, the degrees of freedom (DoFs) of robot is conform to human motion, the designed robot is reasonable, and the robot is suitable for rehabilitation training requirements.

Dış iskeletler, çeşitli nedenlerle uzuvlarını kaybeden kişilerin kas rehabilitasyonu ve/veya sosyal hayata adaptasyonu için geliştirilmiş cihazlardır Bu çalışmada, Solidworks programı kullanılarak A Glass Fiber malzemeden yapılmış bir alt ekstremite dış iskeleti tasarlanmıştır. AnyBody programında tasarım modeli kas-iskelet sistemi üzerine bindirilerek iki yürüyüş döngüsü boyunca biyomekanik analizler yapılmıştır. Bu biyomekanik analizler sonucunda kas aktiviteleri, kas kuvveti, eklem momenti ve reaksiyon kuvveti verileri elde edilmiştir. Veriler, dış iskeletli ve dış iskeletsiz olmak üzere iki farklı yürüme yapan model üzerinde toplanmış ve analiz edilmiştir. Tasarımda kullanılan A Glass Fiber malzemenin dış iskeletin ağırlığını motor ağırlığı dahil yaklaşık 8-9 kg'a kadar düşürdüğü gözlemlenmiştir. Ayrıca dış iskelet tasarımının, literatürde tasarlanan benzer dış iskeletlere göre kaslar ve eklemler üzerindeki kuvveti daha fazla azalttığı görülmüştür. Ayrıca simülasyon sonuçları, dış iskeletin femur ve tibianın S şeklindeki yapısının insan anatomik daha uygun olduğunu göstermiştir. Ayrıca yürüyüşte gövdeden bacaklara kuvvet aktarımının daha dengeli olduğu gözlemlenmiştir. Son olarak dış iskelet ile yürümenin psoas major kasını daha fazla çalıştırarak kalçanın ön-arka kuvvetini arttırdığı sonucuna varılmıştır.

Aiming at a pneumatic artificial muscle (PAM) lower extremity exoskeleton, a control mechanism based on hybrid phase sliding mode control (SMC) is proposed. First of all, the human gait cycle is mainly divided into the swing phase and stance phase, and the lower extremity exoskeleton phase models are established by the Euler–Lagrange method, respectively. Secondly, the lower limb exoskeleton is inevitably affected in the diverse working environment, and the exoskeleton model has nonlinear and strong coupling characteristics, which both increase the control difficulty. In this situations, a robust sliding mode control method is designed based on an Extended State Observer (ESO). Thirdly, the pneumatic muscle takes time to contract and relax, and then the joint input torque cannot jump when the gait phase changes, hence, the smoothing switching of the assistive control scheme is introduced to solve it. The smoothing switching time is detected by a phase detector, and the phase detector is designed by the plantar pressure information. Finally the comparative simulation shows that this control strategy has the advantages of fast time, high control precision and no jump during control torque switching. Pneumatic artificial muscle contraction rate curve shows that the pneumatic muscles’ motion range meets the control requirement of the exoskeleton.

The number of older people is growing rapidly around the world. Ageing process results in reduced or restricted mobility which is essential to perform activities of daily living. Currently, there are numerous powered assistive exoskeletons commercially available as well as are being developed to support and rehabilitate lower limbs. Significant attention is also been given to develop upper limb rehabilitation devices, however the question of what kind of assistive devices can be used by elderly group of people for their upper limbs and what technical characteristics they should incorporate is not properly researched. This paper presents the state of the art of currently available assistive exoskeletons which can be exploited to support the motions of upper limbs of elderly to perform activities of daily living. Mechanism type, degrees of freedom, type actuators and materials selected for the fabrication of these porotypes are presented in detail. Also, the type of control systems utilized for these upper limb exoskeletons are discussed in detail with the insight on the feedback signal methods. A detailed discussion on the challenges in the fields of mechanism development, actuation and control for these upper limb powered exoskeletons is presented with the opportunities for future technological developments.

Exoskeleton robotics has ushered in a new era of modern neuromuscular rehabilitation engineering and assistive technology research. The technology promises to improve the upper-limb functionalities required for performing activities of daily living. The exoskeleton technology is evolving quickly but still needs interdisciplinary research to solve technical challenges, e.g., kinematic compatibility and development of effective human–robot interaction. In this paper, the recent development in upper-limb exoskeletons is reviewed. The key challenges involved in the development of assistive exoskeletons are highlighted by comparing available solutions. This paper provides a general classification, comparisons, and overview of the mechatronic designs of upper-limb exoskeletons. In addition, a brief overview of the control modalities for upper-limb exoskeletons is also presented in this paper. A discussion on the future directions of research is included.

Resistance training is a popular form of exercise recommended by national health organizations, such as the American College of Sports Medicine (ACSM) and the American Heart Association (AHA). This form of training is available for most populations. A compact design of upper limb exoskeleton mechanism for homebased resistance training using a spring-loaded upper limb exoskeleton with a three degree-of-freedom shoulder joint and a one degree-of-freedom elbow joint allows a patient or a healthy individual to move the upper limb with multiple joints in different planes. It can continuously increase the resistance by adjusting the spring length to train additional muscle groups and reduce the number of potential injuries to upper limb joints caused by the mass moment of inertia of the training equipment. The aim of this research is to perform a preliminary evaluation of the designed function by adopting an appropriate motion analysis system and experimental design to verify our prototype of the exoskeleton and determine the optimal configuration of the spring-loaded upper limb exoskeleton.

This article introduces a human–robot interaction controller toward the lower extremity exoskeleton whose aim is to improve the tracking performance and drive the exoskeleton to shadow the wearer with less interaction force. To acquire the motion intention of the wearer, two subsystems are designed: the first is to infer the wearer is in which phase based on floor reaction force detected by a multi-sensor system installed in the sole, and the second is to infer the motion velocity based on the multi-axis force sensor and admittance model. An improved single-input fuzzy sliding mode controller is designed, and the adaptive switching controller is combined to promote the tracking performance considering system uncertainties. Adaptation laws are designed based on the Lyapunov stability theorem. Therefore, the stability of the single-input adaptive fuzzy sliding mode control can be guaranteed. Finally, the proposed methods are applied to the lower extremity exoskeleton, especially in the swing phase. Its effectiveness is validated by comparative experiments.

Most exoskeletons for upper limbs used in stroke rehabilitation rely solely on muscle activity signals, which are often weak and unstable. This study aimed to develop and improve the control method for these exoskeletons. Two Myo Armband sensors and six force sensors were evaluated to collect electromyography (EMG) signals and reaction forces from the forearm and upper arm regions of ten healthy participants. The data was used to control an external exoskeleton for upper limb rehabilitation, including basic hand and elbow movements. Three methodological techniques were adopted for classifying and analyzing electromyography (EMG) data: K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA). Offline analysis revealed that SVM exhibited the highest accuracy, achieving an average of 95.209% for hand motions utilizing only Myo Armband data and 99.406% for elbow movements among the ten participants. A new method that uses an SVM classifier to combine EMG and force data got 99.1% accuracy. This study demonstrates the superiority of the SVM algorithm in classifying movements and enhancing control of upper limb exoskeletons.

The movement of lifting heavy objects with upper limb exoskeleton is a dynamic process of multi-muscle coordination. Muscle fatigue occurs after repetitive lifting heavy objects with exoskeleton robot for a long time. Due to the dynamic characteristics of the moving process, the traditional linear analysis methods can not fully characterize the muscle fatigue problem of upper limb. In this paper, a novel approach base on ross recurrence plot (CRP)and recurrence quantification analysis (RQA)is proposed to analyze the progression of muscle fatigue of upper limb. Firstly, distance threshold and date length of the recurrence plot is chosen according to the RP dynamical structures of the electromyography (EMG)signals. Then the phase space reconstruction techniques and recurrence plot theory are utilized to analyze the nonstationarity characteristics of the multichannel and single-channel surface EMG signals during the fatigue process. Finally, the RQA indices of the overall and local muscles are calculated. The experiments show that the CRP can qualitatively reflect the change of muscle fatigue state. Meanwhile, the RQA indices of multi-channel and single-channel EMG signals can quantitatively reveal the changes of muscle fatigue from the overall and local perspectives. This method provides a theoretical basis for evaluating muscle fatigue during repeated moving in the way of nonlinear dynamics.

Monitoring of muscle activities of human limbs is essential for designing controllers of wearable robotic devices such as prosthetics, orthotics and exoskeletons. Human-robot interaction (HRI) is generally studied to control these devices and ascertain comfort levels of the wearer. Cognitive-HRI (cHRI) and physical-HRI (pHRI) are the two main types of HRI methods identified in literature. Surface electromyography (sEMG) signals of skeletal muscles are commonly used in cHRI methods to identify the motion intentions. However, sEMG signals are sensitive to the environmental conditions such as electric and magnetic disturbances. Alternatively, changes to muscle stiffness and volume are measured in pHRI methods. Accordingly, this paper presents a novel sensory system to detect motions of upper or lower limbs by monitoring surface-muscle pressure (SMP). It is comprised of specially designed ’pressurized-air-pouches’ made of silicone. Experiments were carried out with the developed SMP monitoring system to detect muscles activities during biceps curls. The results were compared against sEMG signals to evaluate the validity of the proposed method. The analysis indicated a strong correlation between the signals measured and verifies the potential of using SMP as an effective muscle activity sensing method.