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Ketkar VD, Wolbrecht ET, Perry JC, Farrens A. Design and Development of a Spherical 5-Bar Thumb Exoskeleton Mechanism for Poststroke Rehabilitation. J Med Device 2023; 17:021002. [PMID: 37152413 PMCID: PMC10158975 DOI: 10.1115/1.4056864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 01/23/2023] [Indexed: 02/10/2023] Open
Abstract
This paper presents the kinematic design and development of a two degree-of-freedom (2DOF) spherical 5-bar thumb exoskeleton to augment the finger individuating grasp exercise robot (FINGER) rehabilitation robot, which assists the index and middle fingers individually in naturalistic grasping. The thumb module expands the capabilities of FINGER, allowing for broader proprioceptive training and assessment of hand function. The design process started by digitizing thumb-grasping motions to the index and the middle fingers separately, recorded from multiple healthy subjects utilizing a motion capture system. Fitting spheres to trajectory data of each subject allowed normalization of all subjects' data to a common center and radius. A two-revolute joint serial-chain mechanism was synthesized (intermediate optimization step) to reach the normalized trajectories. Next, the two resulting grasping trajectories were spatially sampled as targets for the 2DOF spherical 5-bar synthesis. Optimization of the spherical 5-bar included symmetry constraints and cost-function penalties for poor manipulability. The resulting exoskeleton assists both flexion/extension and abduction/adduction of the thumb enabling a wide range of motions. Consistent with FINGER, the parallel structure of the spherical 5-bar places the actuators at the base of the module, allowing for desirable characteristics, including high backdrivability, high controllable bandwidth, and low mechanical impedance. The mechanical design was developed from the kinematic solution, including an adjustable thumb cuff to accommodate different hand sizes. Fit and function of the device were tested on multiple subjects, including survivors of stroke. A proportional-derivative force controller with gravity and friction compensation was implemented to reduce resistance to motion during subject testing.
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Affiliation(s)
- Vishwanath D. Ketkar
- Department of Electrical Engineering, University of Idaho, Moscow, ID 83844-0902
| | - Eric T. Wolbrecht
- Department of Mechanical Engineering, University of Idaho, Moscow, ID 83844-0902
| | - Joel C. Perry
- Department of Mechanical Engineering, University of Idaho, Moscow, ID 83844-0902
| | - Andria Farrens
- Department of Biomedical Engineering, University of California, Irvine, CA 92697
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Pignolo L, Servidio R, Basta G, Carozzo S, Tonin P, Calabrò RS, Cerasa A. The Route of Motor Recovery in Stroke Patients Driven by Exoskeleton-Robot-Assisted Therapy: A Path-Analysis. Med Sci (Basel) 2021; 9:64. [PMID: 34842770 PMCID: PMC8628926 DOI: 10.3390/medsci9040064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 10/18/2021] [Accepted: 10/24/2021] [Indexed: 11/24/2022] Open
Abstract
Background: Exoskeleton-robot-assisted therapy is known to positively affect the recovery of arm functions in stroke patients. However, there is a lack of evidence regarding which variables might favor a better outcome and how this can be modulated by other factors. Methods: In this within-subject study, we evaluated the efficacy of a robot-assisted rehabilitation system in the recovery of upper limb functions. We performed a path analysis using a structural equation modeling approach in a large sample of 102 stroke patients (age 63.6 ± 13.1 years; 61% men) in the post-acute phase. They underwent 7 weeks of bilateral arm training assisted by an exoskeleton robot combined with a conventional treatment (consisting of simple physical activity together with occupational therapy). The upper extremity section of the Fugl-Meyer (FM-UE) scale at admission was used as a predictor of outcome, whereas age, gender, side of the lesion, days from the event, pain scale, duration of treatment, and number of sessions as mediators. Results: FM-UE at admission was a direct predictor of outcome, as measured by the motricity index of the contralateral upper limb and trunk control test, without any other mediating factors. Age, gender, days from the event, side of lesion, and pain scales were independently associated with outcomes. Conclusions: To the best of our knowledge, this is the first study assessing the relationship between clinical variables and outcomes induced by robot-assisted rehabilitation with a path-analysis model. We define a new route for motor recovery of stroke patients driven by exoskeleton-robot-assisted therapy, highlighting the role of FM-UE at admission as a useful predictor of outcome, although other variables need to be considered in the time-course of disease.
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Affiliation(s)
- Loris Pignolo
- S’Anna Institute, 88900 Crotone, Italy; (G.B.); (S.C.); (P.T.); (A.C.)
| | - Rocco Servidio
- Department of Cultures, Education and Society, University of Calabria, 87036 Rende, Italy;
| | - Giuseppina Basta
- S’Anna Institute, 88900 Crotone, Italy; (G.B.); (S.C.); (P.T.); (A.C.)
| | - Simone Carozzo
- S’Anna Institute, 88900 Crotone, Italy; (G.B.); (S.C.); (P.T.); (A.C.)
| | - Paolo Tonin
- S’Anna Institute, 88900 Crotone, Italy; (G.B.); (S.C.); (P.T.); (A.C.)
| | | | - Antonio Cerasa
- S’Anna Institute, 88900 Crotone, Italy; (G.B.); (S.C.); (P.T.); (A.C.)
- Institute for Biomedical Research and Innovation (IRIB), National Research Council of Italy (CNR), 98164 Messina, Italy
- Pharmacotechnology Documentation and Transfer Unit, Preclinical and Translational Pharmacology, Department of Pharmacy, Health Science and Nutrition, University of Calabria, 87036 Rende, Italy
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Alicea R, Xiloyannis M, Chiaradia D, Barsotti M, Frisoli A, Masia L. A soft, synergy-based robotic glove for grasping assistance. WEARABLE TECHNOLOGIES 2021; 2:e4. [PMID: 38486631 PMCID: PMC10936321 DOI: 10.1017/wtc.2021.3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 01/18/2021] [Accepted: 02/18/2021] [Indexed: 03/17/2024]
Abstract
This paper presents a soft, tendon-driven, robotic glove designed to augment grasp capability and provide rehabilitation assistance for postspinal cord injury patients. The basis of the design is an underactuation approach utilizing postural synergies of the hand to support a large variety of grasps with a single actuator. The glove is lightweight, easy to don, and generates sufficient hand closing force to assist with activities of daily living. Device efficiency was examined through a characterization of the power transmission elements, and output force production was observed to be linear in both cylindrical and pinch grasp configurations. We further show that, as a result of the synergy-inspired actuation strategy, the glove only slightly alters the distribution of forces across the fingers, compared to a natural, unassisted grasping pattern. Finally, a preliminary case study was conducted using a participant suffering from an incomplete spinal cord injury (C7). It was found that through the use of the glove, the participant was able to achieve a 50% performance improvement (from four to six blocks) in a standard Box and Block test.
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Affiliation(s)
- Ryan Alicea
- Assistive Robotics and Interactive ExoSuits (ARIES) Lab, Institute for Computer Engineering (ZITI), Heidelberg University, Heidelberg, Germany
| | - Michele Xiloyannis
- Sensory-Motor Systems (SMS) Lab, Institute of Robotics and Intelligent Systems (IRIS), ETH Zurich, Zurich, Switzerland
- The Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Zurich, Switzerland
| | - Domenico Chiaradia
- Perceptual Robotics (PERCRO) Laboratory, TeCIP Institute, Scuola Superiore Sant’Anna, Pisa, Italy
| | - Michele Barsotti
- Perceptual Robotics (PERCRO) Laboratory, TeCIP Institute, Scuola Superiore Sant’Anna, Pisa, Italy
| | - Antonio Frisoli
- Perceptual Robotics (PERCRO) Laboratory, TeCIP Institute, Scuola Superiore Sant’Anna, Pisa, Italy
| | - Lorenzo Masia
- Assistive Robotics and Interactive ExoSuits (ARIES) Lab, Institute for Computer Engineering (ZITI), Heidelberg University, Heidelberg, Germany
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Pignolo L, Serra S, Basta G, Carozzo S, Arcuri F, Pignataro LM, Ciancarelli I, Tonin P, Cerasa A. Data on a new neurorehabilitation approach targeting functional recovery in stroke patients. Data Brief 2019; 27:104685. [PMID: 31737755 PMCID: PMC6849111 DOI: 10.1016/j.dib.2019.104685] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 09/23/2019] [Accepted: 10/11/2019] [Indexed: 11/28/2022] Open
Abstract
Robotic-assisted devices are known to positively affect the recovery of one specific motor effector after stroke. However, it has widely been reported that the functional status of patients is only partially ameliorated after application of this kind of advanced treatment. Here, data about the effect of a new rehabilitation approach has been described in a large population of stroke patients. We sought to validate an integrated rehabilitation system for stroke (IRSS) patients, which is composed of a set of robotic-assisted tools aimed at recovering the entire body. We evaluated the motor recovery in 84 stroke patients equally divided into experimental and control groups to assess the difference between IRSS approach and conventional rehabilitation treatment. We found that IRSS induced a significant improvement as measured by functional neurological scales, such as the barthel index and functional independence measure. The data provided in this article will assist therapists and physicians working for developing new rehabilitation protocols more focused on a holistic functional recovery approach. The data are available at Mendeley Data, https://doi.org/10.17632/wptmgm7zk2.1.
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Affiliation(s)
- Loris Pignolo
- S. Anna Institute, Research in Advanced Neurorehabilitation (RAN), 88900, Crotone, Italy
| | - Sebastiano Serra
- S. Anna Institute, Research in Advanced Neurorehabilitation (RAN), 88900, Crotone, Italy
| | - Giuseppina Basta
- S. Anna Institute, Research in Advanced Neurorehabilitation (RAN), 88900, Crotone, Italy
| | - Simone Carozzo
- S. Anna Institute, Research in Advanced Neurorehabilitation (RAN), 88900, Crotone, Italy
| | - Francesco Arcuri
- S. Anna Institute, Research in Advanced Neurorehabilitation (RAN), 88900, Crotone, Italy
| | | | - Irene Ciancarelli
- Department of Life, Health and Environmental Sciences, University of L'Aquila, Nova Salus S.r.l., L'Aquila, Italy
| | - Paolo Tonin
- Department of Life, Health and Environmental Sciences, University of L'Aquila, Nova Salus S.r.l., L'Aquila, Italy
| | - Antonio Cerasa
- S. Anna Institute, Research in Advanced Neurorehabilitation (RAN), 88900, Crotone, Italy
- IBFM, National Research Council, 88100, Catanzaro, Italy
- Corresponding author. Neuroimaging Unit, IBFM-CNR, 88100, Catanzaro, Italy.
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Abstract
The development of robotic devices for rehabilitation is a fast-growing field. Nowadays, thanks to novel technologies that have improved robots’ capabilities and offered more cost-effective solutions, robotic devices are increasingly being employed during clinical practice, with the goal of boosting patients’ recovery. Robotic rehabilitation is also widely used in the context of neurological disorders, where it is often provided in a variety of different fashions, depending on the specific function to be restored. Indeed, the effect of robot-aided neurorehabilitation can be maximized when used in combination with a proper training regimen (based on motor control paradigms) or with non-invasive brain machine interfaces. Therapy-induced changes in neural activity and behavioral performance, which may suggest underlying changes in neural plasticity, can be quantified by multimodal assessments of both sensorimotor performance and brain/muscular activity pre/post or during intervention. Here, we provide an overview of the most common robotic devices for upper and lower limb rehabilitation and we describe the aforementioned neurorehabilitation scenarios. We also review assessment techniques for the evaluation of robotic therapy. Additional exploitation of these research areas will highlight the crucial contribution of rehabilitation robotics for promoting recovery and answering questions about reorganization of brain functions in response to disease.
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MajidiRad A, Yihun Y, Desai J, Hakansson NA. Simulation of Exoskeleton Alignment and its Effect on the Knee Extensor and Flexor Muscles. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019; 2019:4093-4096. [PMID: 31946771 DOI: 10.1109/embc.2019.8856640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
This study presents the analysis of different knee joint impairments and their effects on the knee extensor and flexor muscles. Joint impairments can result from stroke, musculoskeletal diseases, or misalignment of an attached exoskeleton joint. Understanding the correlation between parameters involved in joint movement mechanisms as well as force interactions could provide insight to establish an appropriate design for exoskeletons. Joints can be powered or even be rectified in terms of alignment by exoskeletons to help a patient recover quickly. For the study, OpenSIM 4.0 was used to generate models and simulations of the human musculoskeletal structure with and without introduced knee joint impairments along the sagittal and transverse directions. A scenario to simulate the constraints of an exoskeleton designed with a single hinge joint to mimic the knee joint was also considered. Alterations to the knee joint axis within the range of +5.00 to -6.40 mm would result in a meaningful yet not a significant change in muscle stresses; the simulation outputs indicate that constraining the knee joint motion to the sagittal plane will only increase the force generated by the vastus lateralis muscle up to 4.3%.
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Xiao F. Proportional myoelectric and compensating control of a cable-conduit mechanism-driven upper limb exoskeleton. ISA TRANSACTIONS 2019; 89:245-255. [PMID: 30711342 DOI: 10.1016/j.isatra.2018.12.028] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 11/25/2018] [Accepted: 12/18/2018] [Indexed: 06/09/2023]
Abstract
Recent studies have indicated that human motion recognition based on surface electromyography (sEMG) is a reliable and natural method for achieving motion intention. However, achieving accurate estimates of intended motion using a low computational cost is the main challenge in this scenario. In this study, a proportional myoelectric and compensating control method for estimating and assisting human motion intention with a cable-conduit mechanism-driven upper limb exoskeleton was proposed. The integral signal of sEMG and its time-delayed signals were applied as a new feature vector to represent the role of sEMG, which ensured the accuracy and real-time performance of motion estimation. An integrated circuit was used to reduce time of feature extraction. A feed-forward compensator was designed to compensate for the effect of the hysteresis problem in the exoskeleton, which is inevitable when the cable-conduit mechanism was applied to reduce the exoskeleton weight. The model-free control method based on PID method and least squares support vector machine were applied to avoid calculating the complex biomechanical model of human upper limb and the dynamic model of exoskeleton. Experimental results validated the proposed method. The average values of the root-mean-square difference (RMSD) for motion estimation were 0.0579 ± 0.0085 [motion with constant pace (CP)] and 0.0845 ± 0.0137 [motion with variable pace (VP)]. The Bland-Altman analysis results showed that the estimated angle of the proposed method was consistent with the actual angle. The performance of the control method was good, and the accuracies were 98.5608% ± 0.4485% (motion with CP) and 96.6119% ± 0.6628% (motion with VP).
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Affiliation(s)
- Feiyun Xiao
- Hefei University of Technology (HFUT), Hefei, PR China.
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Tsai YL, Huang JJ, Pu SW, Chen HP, Hsu SC, Chang JY, Pei YC. Usability Assessment of a Cable-Driven Exoskeletal Robot for Hand Rehabilitation. Front Neurorobot 2019; 13:3. [PMID: 30814945 PMCID: PMC6381032 DOI: 10.3389/fnbot.2019.00003] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 01/23/2019] [Indexed: 11/21/2022] Open
Abstract
Study design: Case series. Background: Robot-assisted rehabilitation mediated by exoskeletal devices is a popular topic of research. The biggest difficulty in the development of rehabilitation robots is the consideration of the clinical needs. This study investigated the usability of a novel cable-driven exoskeletal robot specifically designed for hand rehabilitation. Methods: The study consists of three steps, including prototype development, spasticity observation, and usability evaluation. First, we developed the prototype robot DexoHand to manipulate the patient's fingers based on the clinical needs and the cable-driven concept established in our previous work. Second, we applied DexoHand to patients with different levels of spasticity. Finally, we obtained the system usability scale (SUS) and assessed its usability. Results: Two healthy subjects were recruited in the pre-test, and 18 patients with stroke and four healthy subjects were recruited in the formal test for usability. The total SUS score obtained from the patients and healthy subjects was 94.77 ± 2.98 (n = 22), indicating an excellent level of usability. The satisfaction score was 4.74 ± 0.29 (n = 22), revealing high satisfaction with DexoHand. The tension profile measured by the cables showed the instantaneous force used to manipulate fingers among different muscle tone groups. Conclusions:DexoHand meets the clinical needs with excellent usability, satisfaction, and reliable tension force monitoring, yielding a feasible platform for robot-assisted hand rehabilitation.
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Affiliation(s)
- Yu-Lin Tsai
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Jian-Jia Huang
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.,School of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Shu-Wei Pu
- Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan
| | - Hsiang-Peng Chen
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Shao-Chih Hsu
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Jen-Yuan Chang
- Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu, Taiwan
| | - Yu-Cheng Pei
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.,School of Medicine, Chang Gung University, Taoyuan, Taiwan.,Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan.,Center for Vascularized Composite Allotransplantation, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
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Movement Velocity and Fluidity Improve after Armeo®Spring Rehabilitation in Children Affected by Acquired and Congenital Brain Diseases: An Observational Study. BIOMED RESEARCH INTERNATIONAL 2018; 2018:1537170. [PMID: 30581845 PMCID: PMC6276530 DOI: 10.1155/2018/1537170] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Revised: 10/29/2018] [Accepted: 11/06/2018] [Indexed: 11/17/2022]
Abstract
Background Children with cerebral palsy (CP) and acquired brain injury (ABI) often exhibit upper limb impairment, with repercussions in their daily activities. Robotic rehabilitation may promote their functional recovery, but evidence of its effectiveness is often based on qualitative functional scales. The primary aim of the present work was to assess movement precision, velocity, and smoothness using numerical indices from the endpoint trajectory of Armeo®Spring. Secondly, an investigation of the effectiveness of robotic rehabilitation in CP and ABI children was performed. Methods Upper limb functional changes were evaluated in children with CP (N=21) or ABI (N=22) treated with Armeo®Spring (20 45-minute sessions over 4 weeks) using clinical scales and numerical indices computed from the exoskeleton trajectory. Results Functional scales (i.e., QUEST and Melbourne) were sensitive to changes produced by the treatment for the whole study group and for the two etiology-based subgroups (improvements above Minimal Clinically Importance Difference). Significant improvement was also observed in terms of velocity, fluidity, and precision of the movement through the numerical indices of kinematic performance. Differences in the temporal evolution of the motor outcome were highlighted between the ABI and CP subgroups, pointing toward adopting different rehabilitative protocols in these two populations. Conclusions Robot-assisted upper limb rehabilitation seems to be a promising tool to promote and assess rehabilitation in children affected by acquired and congenital brain diseases.
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Wu Q, Wu H. Development, Dynamic Modeling, and Multi-Modal Control of a Therapeutic Exoskeleton for Upper Limb Rehabilitation Training. SENSORS 2018; 18:s18113611. [PMID: 30356005 PMCID: PMC6263634 DOI: 10.3390/s18113611] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 10/12/2018] [Accepted: 10/17/2018] [Indexed: 11/16/2022]
Abstract
Robot-assisted training is a promising technology in clinical rehabilitation providing effective treatment to the patients with motor disability. In this paper, a multi-modal control strategy for a therapeutic upper limb exoskeleton is proposed to assist the disabled persons perform patient-passive training and patient-cooperative training. A comprehensive overview of the exoskeleton with seven actuated degrees of freedom is introduced. The dynamic modeling and parameters identification strategies of the human-robot interaction system are analyzed. Moreover, an adaptive sliding mode controller with disturbance observer (ASMCDO) is developed to ensure the position control accuracy in patient-passive training. A cascade-proportional-integral-derivative (CPID)-based impedance controller with graphical game-like interface is designed to improve interaction compliance and motivate the active participation of patients in patient-cooperative training. Three typical experiments are conducted to verify the feasibility of the proposed control strategy, including the trajectory tracking experiments, the trajectory tracking experiments with impedance adjustment, and the intention-based training experiments. The experimental results suggest that the tracking error of ASMCDO controller is smaller than that of terminal sliding mode controller. By optimally changing the impedance parameters of CPID-based impedance controller, the training intensity can be adjusted to meet the requirement of different patients.
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Affiliation(s)
- Qingcong Wu
- College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
| | - Hongtao Wu
- College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
- State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin 150001, China.
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