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Proietti T, Nuckols K, Grupper J, Schwerz de Lucena D, Inirio B, Porazinski K, Wagner D, Cole T, Glover C, Mendelowitz S, Herman M, Breen J, Lin D, Walsh C. Combining soft robotics and telerehabilitation for improving motor function after stroke. WEARABLE TECHNOLOGIES 2024; 5:e1. [PMID: 38510985 PMCID: PMC10952055 DOI: 10.1017/wtc.2023.26] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 11/07/2023] [Accepted: 12/02/2023] [Indexed: 03/22/2024]
Abstract
Telerehabilitation and robotics, either traditional rigid or soft, have been extensively studied and used to improve hand functionality after a stroke. However, a limited number of devices combined these two technologies to such a level of maturity that was possible to use them at the patients' home, unsupervised. Here we present a novel investigation that demonstrates the feasibility of a system that integrates a soft inflatable robotic glove, a cloud-connected software interface, and a telerehabilitation therapy. Ten chronic moderate-to-severe stroke survivors independently used the system at their home for 4 weeks, following a software-led therapy and being in touch with occupational therapists. Data from the therapy, including automatic assessments by the robot, were available to the occupational therapists in real-time, thanks to the cloud-connected capability of the system. The participants used the system intensively (about five times more movements per session than the standard care) for a total of more than 8 hr of therapy on average. We were able to observe improvements in standard clinical metrics (FMA +3.9 ± 4.0, p < .05, COPM-P + 2.5 ± 1.3, p < .05, COPM-S + 2.6 ± 1.9, p < .05, MAL-AOU +6.6 ± 6.5, p < .05) and range of motion (+88%) at the end of the intervention. Despite being small, these improvements sustained at follow-up, 2 weeks after the end of the therapy. These promising results pave the way toward further investigation for the deployment of combined soft robotic/telerehabilitive systems at-home for autonomous usage for stroke rehabilitation.
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Affiliation(s)
- Tommaso Proietti
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Kristin Nuckols
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Jesse Grupper
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Diogo Schwerz de Lucena
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Bianca Inirio
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | | | - Diana Wagner
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Tazzy Cole
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Christina Glover
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Sarah Mendelowitz
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Maxwell Herman
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Joan Breen
- Whittier Rehabilitation Hospital, Bradford, MA, USA
| | - David Lin
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Department of VA Medical Center, Providence, RI, USA
| | - Conor Walsh
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
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Hernández Echarren A, Sánchez Cabeza Á. [Hand robotic devices in neurorehabilitation: A systematic review on the feasibility and effectiveness of stroke rehabilitation]. Rehabilitacion (Madr) 2023; 57:100758. [PMID: 36319483 DOI: 10.1016/j.rh.2022.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 07/18/2022] [Accepted: 08/01/2022] [Indexed: 11/22/2022]
Abstract
Robot-assisted therapy is a relatively new intervention, increasingly used in the rehabilitation treatment of stroke patients. It allows to increase the number of repetitions in the performance of specific tasks movements. For this review, a search was carried out between August and October 2021 in the PubMed, Web of Science, Scopus, Cochrane, PEDro and OTseeker databases, selecting a total of six randomized controlled trials where robot-assisted hand therapy was used in stroke rehabilitation. Studies agree that robot-assisted hand therapy has benefits in all phases of stroke rehabilitation that translate into motor and functional improvements of the upper limb and improvements in hemispatial neglect.
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Affiliation(s)
- A Hernández Echarren
- Departamento de Fisioterapia, Terapia Ocupacional, Rehabilitación y Medicina Física, Facultad de Ciencias de la Salud, Universidad Rey Juan Carlos, Madrid, España.
| | - Á Sánchez Cabeza
- Departamento de Fisioterapia, Terapia Ocupacional, Rehabilitación y Medicina Física, Facultad de Ciencias de la Salud, Universidad Rey Juan Carlos, Madrid, España
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López D, Casado-Fernández L, Fernández F, Fuentes B, Larraga-García B, Rodríguez-Pardo J, Hernández D, Alonso E, Díez-Tejedor E, Gutiérrez Á, Alonso de Leciñana M. Neurodata Tracker: Software for computational assessment of hand motor skills based on optical motion capture in a virtual environment. Digit Health 2023; 9:20552076231174786. [PMID: 37197411 PMCID: PMC10184203 DOI: 10.1177/20552076231174786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 04/21/2023] [Indexed: 05/19/2023] Open
Abstract
Objectives Deficits affecting hand motor skills negatively impact the quality of life of patients. The NeuroData Tracker platform has been developed for the objective and precise evaluation of hand motor deficits. We describe the design and development of the platform and analyse the technological feasibility and usability in a relevant clinical setting. Methods A software application was developed in Unity (C#) to obtain kinematic data from hand movement tracking by a portable device with two cameras and three infrared sensors (leap motion®). Four exercises were implemented: (a) wrist flexion-extension (b) finger-grip opening-closing (c) finger spread (d) fist opening-closing. The most representative kinematic parameters were selected for each exercise. A script in Python was integrated in the platform to transform real-time kinematic data into relevant information for the clinician. The application was tested in a pilot study comparing the data provided by the tool from ten healthy subjects without any motor impairment and ten patients diagnosed with a stroke with mild to moderate hand motor deficit. Results The NeuroData Tracker allowed the parameterization of kinematics of hand movement and the issuance of a report with the results. The comparison of the data obtained suggests the feasibility of the tool for detecting differences between patients and healthy subjects. Conclusions This new platform based on optical motion capturing provides objective measurement of hand movement allowing quantification of motor deficits. These findings require further validation of the tool in larger trials to verify its usefulness in the clinical setting.
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Affiliation(s)
- David López
- Department of Neurology and Stroke Centre, Hospital La Paz Institute for Health Research – IdiPAZ (La Paz University Hospital, Universidad Autónoma de Madrid), Madrid, Spain
| | - Laura Casado-Fernández
- Department of Neurology and Stroke Centre, Hospital La Paz Institute for Health Research – IdiPAZ (La Paz University Hospital, Universidad Autónoma de Madrid), Madrid, Spain
| | | | - Blanca Fuentes
- Department of Neurology and Stroke Centre, Hospital La Paz Institute for Health Research – IdiPAZ (La Paz University Hospital, Universidad Autónoma de Madrid), Madrid, Spain
| | | | - Jorge Rodríguez-Pardo
- Department of Neurology and Stroke Centre, Hospital La Paz Institute for Health Research – IdiPAZ (La Paz University Hospital, Universidad Autónoma de Madrid), Madrid, Spain
| | - David Hernández
- Department of Rehabilitation, Hospital La Paz Institute for Health Research – IdiPAZ (La Paz University Hospital, Universidad Autónoma de Madrid), Madrid, Spain
| | - Elisa Alonso
- Department of Neurology and Stroke Centre, Hospital La Paz Institute for Health Research – IdiPAZ (La Paz University Hospital, Universidad Autónoma de Madrid), Madrid, Spain
| | - Exuperio Díez-Tejedor
- Department of Neurology and Stroke Centre, Hospital La Paz Institute for Health Research – IdiPAZ (La Paz University Hospital, Universidad Autónoma de Madrid), Madrid, Spain
| | - Álvaro Gutiérrez
- ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
| | - María Alonso de Leciñana
- Department of Neurology and Stroke Centre, Hospital La Paz Institute for Health Research – IdiPAZ (La Paz University Hospital, Universidad Autónoma de Madrid), Madrid, Spain
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Secciani N, Brogi C, Pagliai M, Buonamici F, Gerli F, Vannetti F, Bianchini M, Volpe Y, Ridolfi A. Wearable Robots: An Original Mechatronic Design of a Hand Exoskeleton for Assistive and Rehabilitative Purposes. Front Neurorobot 2021; 15:750385. [PMID: 34744679 PMCID: PMC8568131 DOI: 10.3389/fnbot.2021.750385] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 09/15/2021] [Indexed: 11/13/2022] Open
Abstract
Robotic devices are being employed in more and more sectors to enhance, streamline, and augment the outcomes of a wide variety of human activities. Wearable robots arise indeed as of-vital-importance tools for telerehabilitation or home assistance targeting people affected by motor disabilities. In particular, the field of “Robotics for Medicine and Healthcare” is attracting growing interest. The development of such devices is a primarily addressed topic since the increasing number of people in need of rehabilitation or assistive therapies (due to population aging) growingly weighs on the healthcare systems of the nation. Besides, the necessity to move to clinics represents an additional logistic burden for patients and their families. Among the various body parts, the hand is specially investigated since it most ensures the independence of an individual, and thus, the restoration of its dexterity is considered a high priority. In this study, the authors present the development of a fully wearable, portable, and tailor-made hand exoskeleton designed for both home assistance and telerehabilitation. Its purpose is either to assist patients during activities of daily living by running a real-time intention detection algorithm or to be used for remotely supervised or unsupervised rehabilitation sessions by performing exercises preset by therapists. Throughout the mechatronic design process, special attention has been paid to the complete wearability and comfort of the system to produce a user-friendly device capable of assisting people in their daily life or enabling recorded home rehabilitation sessions allowing the therapist to monitor the state evolution of the patient. Such a hand exoskeleton system has been designed, manufactured, and preliminarily tested on a subject affected by spinal muscular atrophy, and some results are reported at the end of the article.
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Affiliation(s)
- Nicola Secciani
- Department of Industrial Engineering, University of Florence, Firenze, Italy
| | - Chiara Brogi
- Department of Industrial Engineering, University of Florence, Firenze, Italy
| | - Marco Pagliai
- Department of Industrial Engineering, University of Florence, Firenze, Italy
| | - Francesco Buonamici
- Department of Industrial Engineering, University of Florence, Firenze, Italy
| | - Filippo Gerli
- IRCCS Don Gnocchi, Don Carlo Gnocchi Foundation, Firenze, Italy
| | | | - Massimo Bianchini
- Institute for Complex Systems, National Research Council, Sesto Fiorentino, Italy
| | - Yary Volpe
- Department of Industrial Engineering, University of Florence, Firenze, Italy
| | - Alessandro Ridolfi
- Department of Industrial Engineering, University of Florence, Firenze, Italy
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Effects of a Soft Robotic Hand for Hand Rehabilitation in Chronic Stroke Survivors. J Stroke Cerebrovasc Dis 2021; 30:105812. [PMID: 33895427 DOI: 10.1016/j.jstrokecerebrovasdis.2021.105812] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 03/11/2021] [Accepted: 04/02/2021] [Indexed: 11/21/2022] Open
Abstract
OBJECTIVES Soft robotic hands are proposed for stroke rehabilitation in terms of their high compliance and low inherent stiffness. We investigated the clinical efficacy of a soft robotic hand that could actively flex and extend the fingers in chronic stroke subjects with different levels of spasticity. METHODS Sixteen chronic stroke subjects were recruited into this single-group study. Subjects underwent 20 sessions of 1-hour EMG-driven soft robotic hand training. Training effect was evaluated by the pre-training and post-training assessments with the clinical scores: Action Research Arm Test(ARAT), Fugl-Meyer Assessment for Upper Extremity(FMA-UE), Box-and-Block test(BBT), Modified Ashworth Scale(MAS), and maximum voluntary grip strength. RESULTS For all the recruited subjects (n = 16), significant improvement of upper limb function was generally observed in ARAT (increased mean=2.44, P = 0.032), FMA-UE (increased mean=3.31, P = 0.003), BBT (increased mean=1.81, P = 0.024), and maximum voluntary grip strength (increased mean=2.14 kg, P < 0.001). No significant change was observed in terms of spasticity with the MAS (decreased mean=0.11, P = 0.423). Further analysis showed subjects with mild or no finger flexor spasticity (MAS<2, n = 9) at pre-training had significant improvement of upper limb function after 20 sessions of training. However, for subjects with moderate and severe finger flexor spasticity (MAS=2,3, n = 7) at pre-training, no significant change in clinical scores was shown and only maximum voluntary grip strength had significant increase. CONCLUSION EMG-driven rehabilitation training using the soft robotic hand with flexion and extension could be effective for the functional recovery of upper limb in chronic stroke subjects with mild or no spasticity.
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Proulx CE, Beaulac M, David M, Deguire C, Haché C, Klug F, Kupnik M, Higgins J, Gagnon DH. Review of the effects of soft robotic gloves for activity-based rehabilitation in individuals with reduced hand function and manual dexterity following a neurological event. J Rehabil Assist Technol Eng 2020; 7:2055668320918130. [PMID: 32435506 PMCID: PMC7223210 DOI: 10.1177/2055668320918130] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 03/17/2020] [Indexed: 12/20/2022] Open
Abstract
Despite limited scientific evidence, there is an increasing interest in soft robotic gloves to optimize hand- and finger-related functional abilities following a neurological event. This review maps evidence on the effects and effectiveness of soft robotic gloves for hand rehabilitation and, whenever possible, patients' satisfaction. A systematized search of the literature was conducted using keywords structured around three areas: technology attributes, anatomy, and rehabilitation. A total of 272 titles, abstracts, and keywords were initially retrieved, and data were extracted out of 13 articles. Six articles investigated the effects of wearing a soft robotic glove and eight studied the effect or effectiveness of an intervention with it. Some statistically significant and meaningful beneficial effects were confirmed with the 29 outcome measures used. Finally, 11 articles also confirmed users' satisfaction with regard to the soft robotic glove, while some articles also noticed an increased engagement in the rehabilitation program with this technology. Despite the heterogeneity across studies, soft robotic gloves stand out as a safe and promising technology to improve hand- and finger-related dexterity and functional performance. However, strengthened evidence of the effects or effectiveness of such devices is needed before their transition from laboratory to clinical practice.
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Affiliation(s)
- Camille E Proulx
- School of Rehabilitation, Université de Montréal, Montréal, Canada.,Center for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR), Institut universitaire sur la réadaptation en déficience physique de Montréal, CIUSSS Centre-Sud-de-l'Île-de-Montréal, Montreal, QC, Canada
| | - Myrka Beaulac
- School of Rehabilitation, Université de Montréal, Montréal, Canada
| | - Mélissa David
- School of Rehabilitation, Université de Montréal, Montréal, Canada
| | - Catryne Deguire
- School of Rehabilitation, Université de Montréal, Montréal, Canada
| | - Catherine Haché
- School of Rehabilitation, Université de Montréal, Montréal, Canada
| | - Florian Klug
- Technischen Universität Darmstadt, Darmstaadt, Germany
| | - Mario Kupnik
- Technischen Universität Darmstadt, Darmstaadt, Germany
| | - Johanne Higgins
- School of Rehabilitation, Université de Montréal, Montréal, Canada.,Center for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR), Institut universitaire sur la réadaptation en déficience physique de Montréal, CIUSSS Centre-Sud-de-l'Île-de-Montréal, Montreal, QC, Canada
| | - Dany H Gagnon
- School of Rehabilitation, Université de Montréal, Montréal, Canada.,Center for Interdisciplinary Research in Rehabilitation of Greater Montreal (CRIR), Institut universitaire sur la réadaptation en déficience physique de Montréal, CIUSSS Centre-Sud-de-l'Île-de-Montréal, Montreal, QC, Canada
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