Effects of a Soft Robotic Glove using a High Repetition Protocol in Chronic Stroke: A Pilot Study

Nuckols, Kristin; Hohimer, Cameron J.; Glover, Christina; Lucena, Diogo Schwerz de; Moyo, Will; Wagner, Diana; Cloutier, Alison; Lin, David J.; Walsh, Conor J.

doi:10.1109/biorob49111.2020.9224291

Cited by 8 publications

(12 citation statements)

References 39 publications

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“…While soft robotic gloves have been developed for convenient use [23][24][25][26][27], there is a safety concern regarding hyperextension during assistance [28]. The gloves are made of soft materials, such as fabric or silicone, and the actuators are remotely mounted on a desk or worn on another part of the body to reduce the external weight applied to the hand.…”

Section: Introductionmentioning

confidence: 99%

A Lightweight Dynamic Hand Orthosis With Sequential Joint Flexion Movement for Postoperative Rehabilitation of Flexor Tendon Repair Surgery

Park,

Hwang,

Gong

et al. 2024

IEEE Trans. Neural Syst. Rehabil. Eng.

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Section: Introductionmentioning

confidence: 99%

A Lightweight Dynamic Hand Orthosis With Sequential Joint Flexion Movement for Postoperative Rehabilitation of Flexor Tendon Repair Surgery

Park,

Hwang,

Gong

et al. 2024

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…Most existing hand orthoses include multiple actuators to assist dexterous finger movements for rehabilitation purposes. The hand orthoses comprise exoskeletons ( Ryu et al, 2008 ; Chiri et al, 2009 ; Ho et al, 2011 ; Ates et al, 2015 ), tendon-driven gloves ( Wege and Zimmermann, 2007 ; Ueki et al, 2012 ; Aiple and Schiele, 2013 ; Borboni et al, 2016 ; Xiloyannis et al, 2016 ; Kim and Park, 2018 ; Burns and Vinjamuri, 2020 ; Alicea et al, 2021 ), and inflatable robotic gloves ( Cappello et al, 2018 ; Nuckols et al, 2020 ). The exoskeletal orthoses can assist fingers with accurately controlled joint movements; however, they inherently suffer from poor portability due to their heavy weight.…”

Section: Introductionmentioning

confidence: 99%

Portable 3D-printed hand orthosis with spatial stiffness distribution personalized for assisting grasping in daily living

Park

2023

Front. Bioeng. Biotechnol.

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Stroke survivors having limited finger coordination require an active hand orthosis to assist them with grasping tasks for daily activities. The orthosis should be portable for constant use; however, portability imposes constraints on the number, size, and weight of the actuators, which increase the difficulty of the design process. Therefore, a tradeoff exists between portability and the assistive force. In this study, a personalized spatial stiffness distribution design is presented for a portable and strengthful hand orthosis. The spatial stiffness distribution of the orthosis was optimized based on measurements of individual hand parameters to satisfy the functional requirements of achieving sufficient grip aperture in the pre-grasping phase and minimal assistive force in the grasping phase. Ten stroke survivors were recruited to evaluate the system. Sufficient grip aperture and high grip strength-to-weight ratio were achieved by the orthosis via a single motor. Moreover, the orthosis significantly restored the range of motion and improved the performance of daily activities. The proposed spatial stiffness distribution can suggest a design solution to make strengthful hand orthoses with reduced weight.

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“…Unfortunately, neuromuscular diseases and traumatic events that impair manipulation skills have significant incidence rates, and can dramatically worsen the quality of life for affected people [3]. When the technology reached a sufficient level of maturity, wearable robotics entered the stage to help people with motor impairments in restoring or compensating for lost motor functions [4]: in particular, the introduction of soft materials in these actuated devices enhanced the human-machine interaction with promising results in the rehabilitation realm [5], [6], [7].…”

Section: Introductionmentioning

confidence: 99%

EMG-Driven Machine Learning Control of a Soft Glove for Grasping Assistance and Rehabilitation

Sierotowicz

Lotti

Nell

et al. 2022

IEEE Robot. Autom. Lett.

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In the field of rehabilitation robotics, transparent, precise and intuitive control of hand exoskeletons still represents a substantial challenge. In particular, the use of compliant systems often leads to a trade-off between lightness and material flexibility, and control precision. In this paper, we present a compliant, actuated glove with a control scheme to detect the user's motion intent, which is estimated by a machine learning algorithm based on muscle activity. Six healthy study participants used the glove in three assistance conditions during a force reaching task. The results suggest that active assistance from the glove can aid the user, reducing the muscular activity needed to attain a medium-high grasp force, and that closedloop control of a compliant assistive glove can successfully be implemented by means of a machine learning algorithm.

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Effects of a Soft Robotic Glove using a High Repetition Protocol in Chronic Stroke: A Pilot Study

Cited by 8 publications

References 39 publications

A Lightweight Dynamic Hand Orthosis With Sequential Joint Flexion Movement for Postoperative Rehabilitation of Flexor Tendon Repair Surgery

A Lightweight Dynamic Hand Orthosis With Sequential Joint Flexion Movement for Postoperative Rehabilitation of Flexor Tendon Repair Surgery

Portable 3D-printed hand orthosis with spatial stiffness distribution personalized for assisting grasping in daily living

EMG-Driven Machine Learning Control of a Soft Glove for Grasping Assistance and Rehabilitation

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