Posts Tagged elbow

[ARTICLE] Physiological and kinematic effects of a soft exosuit on arm movements – Full Text

Abstract

Background

Soft wearable robots (exosuits), being lightweight, ergonomic and low power-demanding, are attractive for a variety of applications, ranging from strength augmentation in industrial scenarios, to medical assistance for people with motor impairments. Understanding how these devices affect the physiology and mechanics of human movements is fundamental for quantifying their benefits and drawbacks, assessing their suitability for different applications and guiding a continuous design refinement.

Methods

We present a novel wearable exosuit for assistance/augmentation of the elbow and introduce a controller that compensates for gravitational forces acting on the limb while allowing the suit to cooperatively move with its wearer. Eight healthy subjects wore the exosuit and performed elbow movements in two conditions: with assistance from the device (powered) and without assistance (unpowered). The test included a dynamic task, to evaluate the impact of the assistance on the kinematics and dynamics of human movement, and an isometric task, to assess its influence on the onset of muscular fatigue.

Results

Powered movements showed a low but significant degradation in accuracy and smoothness when compared to the unpowered ones. The degradation in kinematics was accompanied by an average reduction of 59.20±5.58% (mean ± standard error) of the biological torque and 64.8±7.66% drop in muscular effort when the exosuit assisted its wearer. Furthermore, an analysis of the electromyographic signals of the biceps brachii during the isometric task revealed that the exosuit delays the onset of muscular fatigue.

Conclusions

The study examined the effects of an exosuit on the characteristics of human movements. The suit supports most of the power needed to move and reduces the effort that the subject needs to exert to counteract gravity in a static posture, delaying the onset of muscular fatigue. We interpret the decline in kinematic performance as a technical limitation of the current device. This work suggests that a powered exosuit can be a good candidate for industrial and clinical applications, where task efficiency and hardware transparency are paramount.

Background

In the never-ending quest to push the boundaries of their motor performance, humans have designed a wealth of wearable robotic devices. In one of the earliest recorded attempts to do so, in 1967, Mosher aspired to create a symbiotic unit that would have the “…alacrity of man’s information and control system coupled with the machine’s power and ruggedness” [1]. His design of the Hardiman, although visionary, ran into fundamental technological limitations.

Advances in materials science, electronics and energy storage have since enabled an exponential growth of the field, with state-of-the-art exoskeletons arguably accomplishing Mosher’s vision [2]. Wearable robotic technology has been successful in augmenting human strength during locomotion [3], reducing the metabolic cost of human walking [45], restoring ambulatory capabilities to paraplegic patients [6], assisting in rehabilitating stroke patients [789], harvesting energy from human movements [10] and helping to study fundamental principles underlying human motor control [1112].

These feats were achieved with machines made of rigid links of metal and capable of accurately and precisely delivering high forces to their wearer. While this is undeniably an advantage, it comes at a cost: 1) a significant inertia, which affects both the kinematics of human movement and the power requirements of the device; 2) the need for the joints of the robot to be aligned with the biological joints [13], resulting in increased mechanical complexity and size [14]; 3) a strong cosmetic impact, shown to be linked with psychological health and well-being [15].

The recent introduction of soft materials to transmit forces and torques to the human body [16] has allowed to design wearable robotic devices on the other side of the spectrum: lightweight, low-profile and compliant machines that sacrifice accuracy and magnitude of assistance for the sake of portability and svelteness.

Soft exoskeletons, or exosuits, are clothing-like devices made of fabric or elastomers that wrap around a person’s limb and work in parallel with his/her muscles [1718]. Characteristic of exosuits is that they rely on the structural integrity of the human body to transfer reaction forces between body segments, rather than having their own frame, thus acting more like external muscles than an external skeleton. Their intrinsic compliance removes the need for alignment with the joints and their low-profile allows to wear them underneath everyday clothing.

Exosuits actively transmit power to the human body either using cables, moved by electric motors, or soft pneumatic actuators, embedded in the garment. The latter paradigm was probably among the first to be proposed [19] and has been explored to assist stroke patients during walking [20], to increase shoulder mobility in subjects with neuromuscular conditions [21], to help elbow movements [22] and for rehabilitation purposes to train and aid grasping [232425].

Cable-driven exosuits, instead, include a DC motor that transmits power to the suit using Bowden cables. This flexible transmission allows to locate the actuation stage where its additional weight has the least metabolic impact on its wearer. Using this paradigm to provide assistance to the lower limbs has resulted in unprecedented levels of walking economy in healthy subjects [26] and improved symmetry and efficiency of mobility in stroke patients [27]. Similar principles were used to provide active support to hip and knee extension, reducing activation of the gluteus maximus in sit-to-stand and stand-to-sit transitions [28].

Cable-driven exosuits seem to work particularly well for lower-limbs movements, where small bursts of well-timed assistance can have a big impact on the dynamics and metabolic cost of locomotion [29]. Yet, Park et al. have shown that they have the potential for assisting the upper-limbs in quasi-static movements too: using a tendon-driving mechanism, a textile interface and an elastic component they found a significant reduction in the activity of the deltoid muscle when supporting the weight of the arm [30].

Similar results were reported by Chiaradia et al., where a soft exosuit for the elbow was shown to reduce the activation of the biceps brachii muscle in dynamic movements [31], and by Khanh et al., where the same device was used to improve the range of motion of a patient suffering from bilateral brachial plexus injury [32].

While there is extensive work on the analysis of the effects of wearing a soft exosuit on the kinematics, energetics and muscular activation during walking [33], the authors are unaware of comparable studies on movements of the upper limbs, whose variety of volitional motions is fundamentally different from the rhythmic nature of walking.

Understanding how these devices affect the physiology and mechanics of human movements is fundamental for quantifying their benefits and drawbacks, assessing their suitability for different applications and guiding a continuous data-driven design refinement.

In this study we investigate the kinematic and physiological effects of wearing a cable-driven exosuit to support elbow movements. We hypothesize that the low inertia and soft nature of the exosuit will allow it to work in parallel with the user’s muscles, delaying the onset of fatigue while having little to no impact on movement kinematics.

We propose a variation of the design and controller presented in [3234] and introduce a controller that both detects the wearer’s intention, allowing the suit to quickly shadow the user’s movements, and compensates for gravitational forces acting on the limb, thus reducing the muscular effort required for holding a static posture. We collect kinematic, dynamic and myoelectric signals from subjects wearing the device, finding that the exosuit affects motion smoothness, significantly reduces muscular effort and delays the onset of fatigue. The analysis offers interesting insights on the viability of using this technology for human augmentation/assistance and medical purposes.

Methods

Exosuit design

An exosuit is a device consisting of a frame made of soft material that wraps around the human body and transmits forces to its wearer’s skeletal structure. In a cable-driven exosuit, artificial tendons are routed along a targeted joint and attached to anchor points on both of its sides. When the tendons are tensioned they deliver an assistive moment to the joint.

[…]

Continue —>  Physiological and kinematic effects of a soft exosuit on arm movements | Journal of NeuroEngineering and Rehabilitation | Full Text

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[Abstract] Development of Digital Control System for Wearable Mechatronic Devices: Applications in Musculoskeletal Rehabilitation of the Upper Limb – Thesis

Abstract

The potential for wearable mechatronic systems to assist with musculoskeletal rehabilitation of the upper limb has grown with the technology. One limiting factor to realizing the benefits of these devices as motion therapy tools is within the development of digital control solutions. Despite many device prototypes and research efforts in the surrounding fields, there are a lack of requirements, details, assessments, and comparisons of control system characteristics, components, and architectures in the literature. Pairing this with the complexity of humans, the devices, and their interactions makes it a difficult task for control system developers to determine the best solution for their desired applications.

The objective of this thesis is to develop, evaluate, and compare control system solutions that are capable of tracking motion through the control of wearable mechatronic devices. Due to the immaturity of these devices, the design, implementation, and testing processes for the control systems is not well established. In order to improve the efficiency and effectiveness of these processes, control system development and evaluation tools have been proposed.

The Wearable Mechatronics-Enabled Control Software framework was developed to enable the implementation and comparison of different control software solutions presented in the literature. This framework reduces the amount of restructuring and modification required to complete these development tasks. An integration testing protocol was developed to isolate different aspects of the control systems during testing. A metric suite is proposed that expands on the existing literature and allows for the measurement of more control characteristics. Together, these tools were used ii ABSTRACT iii to developed, evaluate, and compare control system solutions.

Using the developed control systems, a series of experiments were performed that involved tracking elbow motion using wearable mechatronic elbow devices. The accuracy and repeatability of the motion tracking performances, the adaptability of the control models, and the resource utilization of the digital systems were measured during these experiments. Statistical analysis was performed on these metrics to compare between experimental factors. The results of the tracking performances show some of the highest accuracies for elbow motion tracking with these devices. The statistical analysis revealed many factors that significantly impact the tracking performance, such as visual feedback, motion training, constrained motion, motion models, motion inputs, actuation components, and control outputs.

Furthermore, the completion of the experiments resulted in three first-time studies, such as the comparison of muscle activation models and the quantification of control system task timing and data storage needs. The successes of these experiments highlight that accurate motion tracking, using biological signals of the user, is possible, but that many more efforts are needed to obtain control solutions that are robust to variations in the motion and characteristics of the user.

To guide the future development of these control systems, a national survey was conducted of therapists regarding their patient data collection and analysis methods. From the results of this survey, a series of requirements for software systems, that allow therapists to interact with the control systems of these devices, were collected. Increasing the participation of therapists in the development processes of wearable assistive devices will help to produce better requirements for developers.

This will allow the customization of control systems for specific therapies and patient characteristics, which will increase the benefit and adoption rate of these devices within musculoskeletal rehabilitation programs.

via “Development of Digital Control System for Wearable Mechatronic Devices” by Tyler Desplenter

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[Abstract] Motor Impairment–Related Alterations in Biceps and Triceps Brachii Fascicle Lengths in Chronic Hemiparetic Stroke

Poststroke deficits in upper extremity function occur during activities of daily living due to motor impairments of the paretic arm, including weakness and abnormal synergies, both of which result in altered use of the paretic arm. Over time, chronic disuse and a resultant flexed elbow posture may result in secondary changes in the musculoskeletal system that may limit use of the arm and impact functional mobility.

This study utilized extended field-of-view ultrasound to measure fascicle lengths of the biceps (long head) and triceps (distal portion of the lateral head) brachii in order to investigate secondary alterations in muscles of the paretic elbow.

Data were collected from both arms in 11 individuals with chronic hemiparetic stroke, with moderate to severe impairment as classified by the Fugl-Meyer assessment score. Across all participants, significantly shorter fascicles were observed in both biceps and triceps brachii (P < .0005) in the paretic limb under passive conditions. The shortening in paretic fascicle length relative to the nonparetic arm measured under passive conditions remained observable during active muscle contraction for the biceps but not for the triceps brachii.

Finally, average fascicle length differences between arms were significantly correlated to impairment level, with more severely impaired participants showing greater shortening of paretic biceps fascicle length relative to changes seen in the triceps across all elbow positions (r= −0.82, P = .002). Characterization of this secondary adaptation is necessary to facilitate development of interventions designed to reduce or prevent the shortening from occurring in the acute stages of recovery poststroke.

 

via Motor Impairment–Related Alterations in Biceps and Triceps Brachii Fascicle Lengths in Chronic Hemiparetic Stroke – Christa M. Nelson, Wendy M. Murray, Julius P. A. Dewald, 2018

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[Abstract + References] A Tendon-driven Upper-limb Rehabilitation Robot – IEEE Conference Publication

Abstract

Rehabilitation robots are playing an increasingly important role in daily rehabilitation of patients. In recent years, exoskeleton rehabilitation robots have become a research hotspot. However, the existing exoskeleton rehabilitation robots are mainly rigid exoskeletons. During rehabilitation training using such exoskeletons, the patient’s joint rotation center is fixed, which cannot adapt to the actual joint movements, resulting in secondary damage to the patients. Therefore, in this paper, a tendon-driven flexible upper-limb rehabilitation robot is proposed; the structure and connectors of the rehabilitation robot are designed considering the physiological structure of human upper limbs; we also built the prototype and performed experiments to validate the designed robot. The experimental results show that the proposed upper-limb rehabilitation robot can assist the human subject to conduct upper-limb rehabilitation training.

I. Introduction

Central nervous system diseases, such as stroke, spinal cord injury and traumatic brain injury, tend to cause movement disorder [1]. Clinical studies have shown that intensive rehabilitation training after cerebral injury help patients recover motoric functions because of the brain plasticity [1], [2]. Traditional movement therapy is highly dependent on physiotherapists and the efficacy is limited by professional knowledge and skill levels of physiotherapists [3]. Upper-limbs recover more slowly than lower limbs because of the complex function of neurons. Meanwhile, the rehabilitation therapies are unaffordable for most patients. Robotic rehabilitation opened another way of rehabilitation training and its efficacy has been validated in clinical trials [3], [4]. Many upper-limb robot devices have been developed for rehabilitation or assistance in various forms. One of the famous devices was MIT-MANUS developed by MIT. This kind of devices are stationary external system where the patient inserts their hand or arm and is robotically assisted or resisted in completing predetermined tasks [3], [5]. Other examples of this type of devices include Lum et al.^{\prime}s MIME [6], Kahn et al.’s ARM Guide [7] and a 2-DOF upper-limb rehabilitation robot developed by Tsinghua

 

References

1. M. Hallett, “Plasticity of the human motor cortex and recovery from stroke”, Brain Research Reviews, vol. 36, pp. 169-174, 2001.

2. J. D. Schaechter, “Motor rehabilitation and brain plasticity after hemiparetic stroke”, Progress in Neurobiology, vol. 73, pp. 61-72, 2004.

3. Q. Yang, D. Cao, J. Zhao, “Analysis on State of the Art of upper-limb Rehabilitation Robots”, Jiqiren/robot, vol. 35, pp. 630, 2013.

4. P. Maciejasz, J. Eschweiler, K. Gerlach-Hahn, A. Jansen-Troy, S. Leonhardt, “A survey on robotic devices for upper-limb rehabilitation”, Journal of Neuroengineering & Rehabilitation, vol. 11, pp. 3, 2014.

5. C. J. Nycz, M. A. Delph, G. S. Fischer, “Modeling and design of a tendon actuated flexible robotic exoskeleton for hemiparetic upper-limb rehabilitation”, International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3889-3892, 2015.

6. P. S. Lum, C. G. Burgar, P. C. Shor, “Use of the MIME robotic system to retrain multijoint reaching in post-stroke hemiparesis: why some movement patterns work better than others”, Engineering in Medicine and Biology Society 2003. Proceedings of the International Conference of the IEEE, vol. 2, pp. 1475-1478, 2003.

7. D. J. Reinkensmeyer, L. E. Kahn, M. Averbuch, A. Mckenna-Cole, B. D. Schmit, W. Z. Rymer, “Understanding and treating arm movement impairment after chronic brain injury: progress with the ARM guide”, Journal of Rehabilitation Research & Development, vol. 37, pp. 653-662.

8. Y. Zhang, Z. Wang, L. Ji, S. Bi, “The clinical application of the upper extremity compound movements rehabilitation training robot”, International Conference on Rehabilitation Robotics, pp. 91-94, 2005.

9. H. Fukushima, “Health and wellbeing in the 21st century (No. 4): Early rehabilitation and conditions for which it is appropriate [J]” in Social-human environmentology, pp. 6, 2004.

10. T. G. Sugar, J. He, E. J. Koeneman, J. B. Koeneman, R. Herman, H. Huang et al., “Design and control of RUPERT: a device for robotic upper extremity repetitive therapy”, IEEE Transactions on Neural Systems & Rehabilitation Engineering a Publication of the IEEE Engineering in Medicine & Biology Society, vol. 15, no. 3, pp. 336-46, 2007.

11. J. C Perry, J. Rosen, S. Burns, “Upper-Limb Powered Exoskeleton Design”, Mechatronics IEEE/ASME Transactions on, vol. 12, pp. 408-417, 2007.

12. A. U. Pehlivan, O. Celik, M. K. O’Malley, “Mechanical design of a distal arm exoskeleton for stroke and spinal cord injury rehabilitation”, IEEE International Conference on Rehabilitation Robotics IEEE Int Conf Rehabil Robot, pp. 5975428, 2011.

13. S Koo, T. P. Andriacchi, “The Knee Joint Center of Rotation is Predominantly on the Lateral Side during Normal Walking[J]”, Journal of Biomechanics, vol. 41, no. 6, pp. 1269, 2008.

14. Y. Mao, S. K. Agrawal, “Transition from mechanical arm to human arm with CAREX: A cable driven ARm EXoskeleton (CAREX) for neural rehabilitation”, Proc. IEEE Int. Conf. Robot. Autom., pp. 2457-2462, 2012.

15. Y. Mao, X. Jin, G. G. Dutta, J. P. Scholz, S. K. Agrawal, “Human movement training with a cable driven ARm EXoskeleton (CAREX)”, IEEE Trans. Neural Syst. Rehabil. Eng., vol. 23, no. 1, pp. 84-92, Jan. 2015.

16. DJ Reinkensmeyer, JL Emken, SC. Cramer, “Robotics motor learning and neurologic recovery”, Annual Review of Biomedical Engineering, vol. 6, no. 1, pp. 497-525, 2004.

17. QZ Yang, CF Cao, JH. Zhao, “Analysis of the status of the research of the upper-limb rehabilitative robot”, Robot, vol. 35, no. 5, pp. 630-640, 2013.

18. XZ Jiang, XH Huang, CH Xiong et al., “Position Control of a Rehabilitation Robotic Joint Based on Neuron Proportion-Integral and Feedforward Control”, Journal of Computational & Nonlinear Dynamics, vol. 7, no. 2, pp. 024502, 2012.

19. ZC Chen, Z. Huang, “Motor relearning in the application of the rehabilitation therapy for stroke”, Chinese Journal of Rehabilitation Medicine, vol. 22, no. 11, pp. 1053-1056, 2007.

20. JC Perry, J Rosen, S. Burns, “Upper-Limb Powered Exoskeleton Design[J]”, IEEE/ASME Transactions on Mechatronics, vol. 12, no. 4, pp. 408-417, 2007.

21. C LV, Research on rehabilitation robot for upper-limb hemiplegia, Shanghai China:, 2011.

22. Y K Woo, G H Cho, E Y. Yoo, Effect of PNF Applied to the Unaffected Side on Muscle Tone of Affected Side in Patients with Hemiplegia[J], vol. 9, no. 2, 2002.

23. JH Liang, JP Tong, X. Li, “Observation of the curative effect of continuous passive movement of joints in the treatment of lower limb spasticity”, Theory and practice of rehabilitation in China, vol. 14, no. 11, pp. 1067-1067, 2008.

 

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[Abstract] Design and Development of a Robot Guided Rehabilitation Scheme for Upper Extremity Rehabilitation

Abstract

To rehabilitate individuals with impaired upper-limb function, we have designed and developed a robot guided rehabilitation scheme. A humanoid robot, NAO was used for this purpose. NAO has 25 degrees of freedom. With its sensors and actuators, it can walk forward and backward, can sit down and stand up, can wave his hand, can speak to the audience, can feel the touch sensation, and can recognize the person he is meeting. All these qualities have made NAO a perfect coach to guide the subjects to perform rehabilitation exercises. To demonstrate rehabilitation exercises with NAO, a library of recommended rehabilitation exercises involving shoulder (i.e., abduction/adduction, vertical flexion/extension, and internal/external rotation), and elbow (i.e., flexion/extension) joint movements was formed in Choregraphe (graphical programming interface). In experiments, NAO was maneuvered to instruct and demonstrate the exercises from the NRL. A complex ‘touch and play’ game was also developed where NAO plays with the subject that represents a multi-joint movement’s exercise. To develop the proposed tele-rehabilitation scheme, kinematic model of human upper-extremity was developed based modified Denavit-Hartenberg notations. A complete geometric solution was developed to find a unique inverse kinematic solution of human upper-extremity from the Kinect data. In tele-rehabilitation scheme, a therapist can remotely tele-operate the NAO in real-time to instruct and demonstrate subjects different arm movement exercises. Kinect sensor was used in this scheme to get tele-operator’s kinematics data. Experiments results reveals that NAO can be tele-operated successfully to instruct and demonstrate subjects to perform different arm movement exercises. A control algorithm was developed in MATLAB for the proposed robot guided supervised rehabilitation scheme. Experimental results show that the NAO and Kinect sensor can effectively be used to supervise and guide the subjects in performing active rehabilitation exercises for shoulder and elbow joint movements.

Recommended Citation
Assad-Uz-Zaman, Md, “Design and Development of a Robot Guided Rehabilitation Scheme for Upper Extremity Rehabilitation” (2017). Theses and Dissertations. 1578.
https://dc.uwm.edu/etd/1578

via “Design and Development of a Robot Guided Rehabilitation Scheme for Upp” by Md Assad-Uz-Zaman

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[Abstract] Design and development of an upper limb rehabilitation robotic system – IEEE Conference Publication

Abstract

This paper presents ongoing research activities for the designing and development of an upper limb rehabilitation robotic system needed by the Prokinetic Rehabilitation Clinic. Prokinetic therapists identified the need of a passive rehabilitation robotic system (RRS) with 3 degrees of freedom for upper limb. The medical and technical requirements analysis for an upper limb rehabilitation robotic system, the video motion analysis were carried out, and the mechanical, actuation, control systems and human-machine interface of the RRS were designed and developed. The results of designing and developing an upper limb rehabilitation robotic system are presented here.
Date of Conference: 28-31 May 2018

 

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[Abstract] Kinematic analysis and control for upper limb robotic rehabilitation system – IEEE Conference Publication

Abstract

Present physical rehabilitation practice implies one-to-one therapist — patient interactions. This leads to shortage of therapists and high costs for patient or healthcare insurance systems. Along with Prokinetic Rehabilitation Clinic, we proposed a new intelligent, adaptive robotic system (RAPMES), which can provide the rehabilitation protocols, defined by a therapist, for the wrist and elbow of upper limb, considering the patient reactions and based on real-time feedback. RAPMES is a passive rehabilitation robotic system (RRS) with 3 degrees of freedom, and assists the rehabilitation process for elbow, forearm and wrist movements. Computation of the kinematic model for the RAPMES robotic device is required in order to determine the parameters associated with the mechanical joints, so that the experimental model executes certain trajectories in space. In this paper, we will present both forward and inverse kinematics determined for the experimental model. The kinematic model was implemented in Matlab environment, and we present a series of simulations, conducted in order to validate the proposed kinematic model. Then, we impose the functional movements (determined using the real-time video motion analysis system, as polynomial movement functions) as input to the kinematic model, and we present a series of simulations and results. The RAPMES control algorithm includes the kinematic model, and uses the polynomial movement functions as control input.
Date of Conference: 28-31 May 2018

 

I. Introduction

Statistics shows that, at European Union level, the upper limb is second common body part injured, as a result of unintentional physical injury [1]. Also, one can note the shortage of therapists and high costs for patient or healthcare insurance systems. Current development in robotics may offer a solution for this problem [2], allowing the creation of robotic devices to support the rehabilitation process, in a supervised or unsupervised way, in physiotherapy clinics or at home. In this context, we proposed RAPMES, a new intelligent, adaptive robotic system, which can provide the rehabilitation protocols, defined by a therapist, for the wrist and elbow of upper limb, considering the patient reactions and based on real-time feedback. RAPMES robotic system is designed on an ongoing research project, which implies several stages of development. In a first stage, we conducted a study involving therapists, the personnel and devices existent in a physiotherapy clinic. The role of this study was to determine the requirements for the robotic device, and to reveal the specific therapeutic needs of patients with rehabilitation indications at wrist and elbow level. On a second stage, we used a real-time video motion analysis system, to determine and understand specific functional movements frequently made with the dominant upper limb, by healthy persons. One of our research objectives is to include these movements as a part of RAPMES control algorithm, as they may offer a better rehabilitation of the upper limb, for specific moves. Next, we designed the robotic device, based on findings described above, and realized an experimental model of the robotic device.

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[Conference paper] Kinematic Design of a Parallel Robot for Elbow and Wrist Rehabilitation|Abstract+References

Abstract

This paper presents the kinematics of modular a parallel robot for post-stroke rehabilitation of elbow and wrist. The targeted motions for rehabilitation are: elbow flexion, pronation/supination, flexion/extension and adduction/abduction (radial/ulnar deviation) of the wrist. The kinematic structure of the robotic system is presented starting from general considerations concerning the rehabilitation protocol of the upper limb. Its kinematics is developed and simulation results are presented for a proposed training exercise.

References

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    Allington J, Spencer SJ, Klein J, Buell M, Reinkensmeyer DJ, Bobrow J (2011) Supinator extender (SUE): a pneumatically actuated robot for forearm/wrist rehabilitation after stroke. In: Proceedings of the Conference on IEEE Engineering in Medicine and Biology Society, pp 1579–1582Google Scholar
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    Carbone G et al (2017) A study of feasibility for a limb exercising device. Advances in Italian mechanism science. In: Proceedings of the first international conference of the IFToMM Italy, pp 11–21Google Scholar
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    Colizzi L, Lidonnici A, Pignolo P (2012) Upper limb rehabilitation after stroke: ARAMIS a “robomechatronic” innovative approach and prototype. In: Proceedings of the 4th IEEE RAS & EMBS international conference on biomedical robotics and biomechatronics (BioRob), pp 1410–1414Google Scholar
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    Major KA, Major ZZ, Carbone G, Pîslă A, Vaida C, Gherman B, Pîslă D (2016) Ranges of motion as basis for robot-assisted post-stroke rehabilitation. Int J Bioflux Soc Hum Vet Med 8(4):192–196Google Scholar
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[Abstract] A wearable monitoring system for at-home stroke rehabilitation exercises: A preliminary study

Abstract:

When stroke survivors perform rehabilitation exercises in clinical settings, experienced therapists can evaluate the associated quality of movements by observing only the initial part of the movement execution so that they can discourage therapeutically undesirable movements effectively and reinforce desirable ones as much as possible in the limited therapy time. This paper introduces a novel monitoring platform based on wearable technologies that can replicate the capability of skilled therapists. Specifically, we propose to deploy five wearable sensors on the trunk, and upper and forearm of the two upper limbs, analyze partial to complete observation data of reaching exercise movements, and employ supervised machine learning to estimate therapists’ evaluation of movement quality. Estimation performance was evaluated using F-Measure, Receiver Operating Characteristic Area, and Root Mean Square Error, showing that the proposed system can be trained to evaluate the movement quality of the entire exercise movement using as little as the initial 5s of the exercise performance. The proposed platform may help ensure high quality exercise performance and provide virtual feedback of experienced therapists during at-home rehabilitation.

I. Introduction

Stroke is a leading cause of death and disabilities in adults, and the majority of its survivors suffer from upper extremity paresis [1]. There is scientific evidence that repetitive rehabilitation exercises and training could improve motor abilities as a result of motor learning processes [2]. Among many, a reaching movement is a fundamental component of daily movement that requires the coordination of multiple upper extremity segments [3]. It is shown that repetitive reaching exercises improve the smoothness, precision, and speed of arm movements [4]. To continue to improve and to sustain motor function, it is clinically important that patients continue to engage in rehabilitation exercises even outside the clinical settings [5], which emphasizes the importance of the home-based therapy.

 

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[Abstract] Biomechatronics design of a robotic arm for rehabilitation – IEEE Conference Publication

Abstract

Rehabilitation is an important process to restore muscle strength and joint’s range of motion. This paper proposes a biomechatronic design of a robotic arm that is able to mimic the natural movement of the human shoulder, elbow and wrist joint. In a preliminary experiment, a subject was asked to perform four different arm movements using the developed robotic arm for a period of two weeks. The experimental results were recorded and can be plotted into graphical results using Matlab. Based on the results, the robotic arm shows encouraging effect by increasing the performance of rehabilitation process. This is proven when the result in degree value are accurate when being compared with the flexion of both shoulder and elbow joints. This project can give advantages on research if the input parameter needed in the flexion of elbow and wrist.

I. Introduction

According to the United Nations (UN), by 2030 the number of people over 60 years will increase by 56 per cent, from 901 million to more than 1.4 billion worldwide [1]. As the number of older persons is expected to grow, it is imperative that government and private health care providers prepare adequate and modern facilities that can provide quality services for the needs of older persons especially in rehabilitation centers. Implementation of robotic technology in rehabilitation process is a modern method and definitely can contribute in this policy and capable in promoting early recovery and motor learning [2]. Furthermore, systematic application of robotic technology can produce significant clinical results in motor recovery of post-traumatic central nervous system injury by assisting in physical exercise based on voluntary movement in rehabilitation [3].

via Biomechatronics design of a robotic arm for rehabilitation – IEEE Conference Publication

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