Design of a spring-assisted exoskeleton module for wrist and hand rehabilitation

Perry, Joel C.; Trimble, Shawn T.; Machado, Luiz Gustavo Castilho; Schroeder, Jeremiah S.; Belloso, Aitor; Rodríguez-de-Pablo, Cristina; Keller, Thierry

doi:10.1109/embc.2016.7590772

Cited by 11 publications

(9 citation statements)

References 7 publications

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“…Perry et al [84] reported on the development of exoskeleton, which enables training of the fingers and thumb in grasp and release tasks. The design has been made as an add-on module for use with the ArmAssist arm rehabilitation system.…”

Section: Spring-assisted Exoskeleton Module For Wrist and Hand Rehabimentioning

confidence: 99%

“…On the other hand, several studies [41,84,150] have proposed spherical mechanisms to replicate the 3-DOF shoulder and wrist movements, but most of them have considered the shoulder and wrist joints as a ball socket joint. This consideration is not able to provide optimal solution against designing a mechanism which could accommodate the effect of instantaneous center of rotation for shoulder and wrist joints.…”

Section: Kinematic Compatibilitymentioning

confidence: 99%

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A Review on Design of Upper Limb Exoskeletons

2020

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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.

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Section: Spring-assisted Exoskeleton Module For Wrist and Hand Rehabimentioning

confidence: 99%

Section: Kinematic Compatibilitymentioning

confidence: 99%

A Review on Design of Upper Limb Exoskeletons

2020

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“…Also, at the University of Idaho, add-on modules for wrist prono-supination and hand grasping training have been presented. Over the years, the device has been iteratively redesigned based on the updated requirements gained from clinical interviews, expert focus groups, and pilot tests with patients and therapists (Perry et al, 2012;Jung et al, 2013;Perry et al, 2016;Butler et al, 2017;Tomić et al, 2017). (Yurkewich et al, 2019), and (D) X-Glove (Triandafilou, 2014).…”

Section: Compact and Lightweight Hand Exoskeletonmentioning

confidence: 99%

Robotic Home-Based Rehabilitation Systems Design: From a Literature Review to a Conceptual Framework for Community-Based Remote Therapy During COVID-19 Pandemic

2021

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During the COVID-19 pandemic, the higher susceptibility of post-stroke patients to infection calls for extra safety precautions. Despite the imposed restrictions, early neurorehabilitation cannot be postponed due to its paramount importance for improving motor and functional recovery chances. Utilizing accessible state-of-the-art technologies, home-based rehabilitation devices are proposed as a sustainable solution in the current crisis. In this paper, a comprehensive review on developed home-based rehabilitation technologies of the last 10 years (2011–2020), categorizing them into upper and lower limb devices and considering both commercialized and state-of-the-art realms. Mechatronic, control, and software aspects of the system are discussed to provide a classified roadmap for home-based systems development. Subsequently, a conceptual framework on the development of smart and intelligent community-based home rehabilitation systems based on novel mechatronic technologies is proposed. In this framework, each rehabilitation device acts as an agent in the network, using the internet of things (IoT) technologies, which facilitates learning from the recorded data of the other agents, as well as the tele-supervision of the treatment by an expert. The presented design paradigm based on the above-mentioned leading technologies could lead to the development of promising home rehabilitation systems, which encourage stroke survivors to engage in under-supervised or unsupervised therapeutic activities.

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“…According to the Public Health Agency of Canada and the Heart and Stroke Foundation, approximately 741,800 adults (365,000 men and 376,800 women) aged over 20 years old live with the effects of a stroke (2012/13). Stroke damages the brain, and 80% of people who suffered a stroke have hemiparesis, which is an impaired motor control on the affected side (2). Most survivors of hemispheric stroke present limited movement of the contralesional upper extremity.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Analysis of a Novel Real-time Adaptive Assist-as-needed Controller for Robot-assisted Rehabilitation for Stroke Patients

Arantes

Bressan

McGibbon

2021

Preprint

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Background: Rehabilitation therapy plays an essential role in assisting stroke patients in regaining function. For this reason, many studies have been conducted to optimize rehabilitation interventions to improve effectiveness and efficiency. In this context, robotic devices for rehabilitation and assistance can be effective. Several studies have demonstrated that using a robot as a therapy tool can significantly reduce motor impairment. However, the slacking behavior, in which the patient lets the robot guide their movements even when they are capable of doing so by themselves, has been identified as a major barrier to reaching the full potential of robot-assist rehabilitation. This paper developed a novel electromyographical-based adaptive assist-as-needed (aAAN) controller aiming to avoid this slacking behavior. Methods: Five stroke patients were recruited to test the controller. Motor impairment status was documented with the Fugl-Meyer (FMA) assessment. In this experiment, horizontal arms tasks were conducted with the robot off and on to assess the subject’s performance in both scenarios. Velocity, time, and position were quantified as performance parameters during the training. Arm and shoulder EMG and electroencephalography (EEG) were used to assess the performance of the controller. Results: The cross-sectional results showed strong second-order relationships between Fugl-Meyer score and outcome measures, where performance metrics (path length and accuracy) were sensitive to change in participants with lower functional status. In comparison, speed and electrophysiological metrics (EMG and EEG) were more sensitive to change in participants with higher functional status. EEG signal amplitude increased when the robot suggested that the robot was inducing a challenge during the training tasks. Conclusion: The preliminary results were very promising; slacking was avoided for all participants during training with the aAAN controller.

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Design of a spring-assisted exoskeleton module for wrist and hand rehabilitation

Cited by 11 publications

References 7 publications

A Review on Design of Upper Limb Exoskeletons

A Review on Design of Upper Limb Exoskeletons

Robotic Home-Based Rehabilitation Systems Design: From a Literature Review to a Conceptual Framework for Community-Based Remote Therapy During COVID-19 Pandemic

A Comprehensive Analysis of a Novel Real-time Adaptive Assist-as-needed Controller for Robot-assisted Rehabilitation for Stroke Patients

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