77 research outputs found

    A review on design of upper limb exoskeletons

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    Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

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    This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level

    Modelling and EMG based Control of Upper Limb Exoskeletons for Hand Impairments

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    Functional losses associated with hand impairments have led to the growing development of hand exoskeletons. The main challenges are to develop the exoskeletons that work according to the user’s motion intention, which can be done by utilizing the electromyogram signals generated by forearm muscles contributed from the movement and/or grasping abilities of the hand. In this research, modelling and EMG based control of hand exoskeletons with the aim to assist stroke survivors in regaining their hand strength and functionality, and improve their quality of life is presented

    Soft Gloves: A Review on Recent Developments in Actuation, Sensing, Control and Applications

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    Interest in soft gloves, both robotic and haptic, has enormously grown over the past decade, due to their inherent compliance, which makes them particularly suitable for direct interaction with the human hand. Robotic soft gloves have been developed for hand rehabilitation, for ADLs assistance, or sometimes for both. Haptic soft gloves may be applied in virtual reality (VR) applications or to give sensory feedback in combination with prostheses or to control robots. This paper presents an updated review of the state of the art of soft gloves, with a particular focus on actuation, sensing, and control, combined with a detailed analysis of the devices according to their application field. The review is organized on two levels: a prospective review allows the highlighting of the main trends in soft gloves development and applications, and an analytical review performs an in-depth analysis of the technical solutions developed and implemented in the revised scientific research. Additional minor evaluations integrate the analysis, such as a synthetic investigation of the main results in the clinical studies and trials referred in literature which involve soft gloves

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

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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

    A virtual hand assessment system for efficient outcome measures of hand rehabilitation

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    Previously held under moratorium from 1st December 2016 until 1st December 2021.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control

    WiGlove : A Passive Dynamic Orthosis for Home-based Post-stroke Rehabilitation of Hand and Wrist

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    Stroke survivors often experience varying levels of motor function deficits in their hands affecting their ability to perform activities of daily life. Recovering their hand functions through neurorehabilitation is a significant step in their recovery towards independent living. Home-based rehabilitation using robotic devices allows stroke survivors to train at their convenience independent of factors such as the availability of therapists’ appointments and the need for frequent travel to outpatient clinics. While many robotic solutions have been proposed to address the above concerns, most focus on training only the wrist or the fingers, neglecting the synergy between the two. To address this, the WiGlove was co-designed to allow hemiparetic stroke survivors to train both the wrist and fingers in the comfort of their homes. The central hypothesis of this work is to investigate if a device designed using user-centred methods featuring aspects of usability such as easy donning and doffing and wireless operation, can act as a feasible tool for home-based rehabilitation of the hand and wrist following stroke. In order to aid this investigation, we tackled this task in three stages of usability and feasibility evaluations. Firstly, healthy participants tried the current state of the art, the SCRIPT Passive Orthosis, as well as the WiGlove, in a counterbalanced, within-subject experiment and attested to WiGlove’s improvement in several aspects of usability such as ease of don/doffing, suitability for ADL, unblocked natural degrees of freedom, safety and aesthetic appeal. Subsequently, a heuristic evaluation with six stroke therapists validated these improvements and helped identify issues they perceived to potentially affect the device’s acceptance. Integrating this feedback, the updated WiGlove was subjected to a six-week summative feasibility evaluation with two stroke survivors, with varying levels of impairment, in their homes without supervision from the therapists. Results from this study were overwhelmingly positive on the usability and acceptance of the WiGlove. Furthermore, in the case of the first participant who trained with it for a total of 39 hours, notable improvements were observed in the participant’s hand functions. It showed that even without a prescribed training protocol, both participants were willing to train regularly with the WiGlove and its games, sometimes several times a day. These results demonstrate that WiGlove can be a promising tool for home-based rehabilitation for stroke survivors and serve as evidence for a larger user study with more participants with varying levels of motor impairments due to stroke. The findings of this study also offer preliminary evidence supporting the effectiveness of training with the WiGlove, particularly in the case of the first participant, who exhibited a significant reduction of tone in the hand as a result of increased training intensity. Owing to the participant’s satisfaction with the device, it was requested by him to extend his involvement in the study by using the WiGlove for a longer duration which was facilitated

    Kinematics and Robot Design IV, KaRD2021

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    This volume collects the papers published on the special issue “Kinematics and Robot Design IV, KaRD2021” (https://www.mdpi.com/journal/robotics/special_issues/KaRD2021), which is the forth edition of the KaRD special-issue series, hosted by the open-access journal “MDPI Robotics”. KaRD series is an open environment where researchers can present their works and discuss all the topics focused on the many aspects that involve kinematics in the design of robotic/automatic systems. Kinematics is so intimately related to the design of robotic/automatic systems that the admitted topics of the KaRD series practically cover all the subjects normally present in well-established international conferences on “mechanisms and robotics”. KaRD2021, after the peer-review process, accepted 12 papers. The accepted papers cover some theoretical and many design/applicative aspects

    Virtual reality based upper extremity stroke rehabilitation system.

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    Some studies suggest that the use of Virtual Reality technologies as an assistive technology in combination with conventional therapies can achieve improved results in post stroke rehabilitation. Despite the wealth of ongoing research applied to trying to build a virtual reality based system for upper extremity rehabilitation, there still exists a strong need for a training platform that would provide whole arm rehabilitation. In order to be practical such a system should ideally be low cost (affordable or inexpensive for a common individual or household) and involve minimal therapist involvement. This research outlines some of the applications of virtual reality that have undergone clinical trials with patients suffering from upper extremity functional motor deficits. Furthermore, this thesis presents the design, development, implementation and feasibility testing of a Virtual Reality-based Upper Extremity Stroke Rehabilitation System. Motion sensing technology has been used to capture the real time movement data of the upper extremity and a virtual reality glove has been used to track the flexion/extension of the fingers. A virtual room has been designed with an avatar of the human arm to allow a variety of training tasks to be accomplished. An interface has been established to incorporate the real time data from the hardware to a virtual scene running on a PC. Three different training scenes depicting a real world scenario have been designed. These have been used to analyze the motion patterns of the users while executing the tasks in the virtual environment simulation. A usability study with the healthy volunteers performing the training tasks have been undertaken to study the ease of use, ease of learning and improved motivation in the virtual environment. Moreover this system costing approximately 2725 pounds would provide home based rehabilitation of the whole arm augmenting conventional therapy on a positive level. Statistical analysis of the data and the evaluation studies with the self report methodologies suggests the feasibility of the system for post stroke rehabilitation in home environment
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