5 research outputs found

    Comparing walking with knee-ankle-foot orthoses and a knee-powered exoskeleton after spinal cord injury: a randomized, crossover clinical trial

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    Recovering the ability to stand and walk independently can have numerous health benefits for people with spinal cord injury (SCI). Wearable exoskeletons are being considered as a promising alternative to conventional knee-ankle-foot orthoses (KAFOs) for gait training and assisting functional mobility. However, comparisons between these two types of devices in terms of gait biomechanics and energetics have been limited. Through a randomized, crossover clinical trial, this study compared the use of a knee-powered lower limb exoskeleton (the ABLE Exoskeleton) against passive orthoses, which are the current standard of care for verticalization and gait ambulation outside the clinical setting in people with SCI. Ten patients with SCI completed a 10-session gait training program with each device followed by user satisfaction questionnaires. Walking with the ABLE Exoskeleton improved gait kinematics compared to the KAFOs, providing a more physiological gait pattern with less compensatory movements (38% reduction of circumduction, 25% increase of step length, 29% improvement in weight shifting). However, participants did not exhibit significantly better results in walking performance for the standard clinical tests (Timed Up and Go, 10-m Walk Test, and 6-min Walk Test), nor significant reductions in energy consumption. These results suggest that providing powered assistance only on the knee joints is not enough to significantly reduce the energy consumption required by people with SCI to walk compared to passive orthoses. Active assistance on the hip or ankle joints seems necessary to achieve this outcome.Peer ReviewedPostprint (published version

    Adapted assistance and resistance training with a knee exoskeleton after stroke

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    Studies on robotic interventions for gait rehabilitation after stroke require: (i) rigorous performance evidence; (ii) systematic procedures to tune the control parameters; and (iii) combination of control modes. In this study, we investigated how stroke individuals responded to training for two weeks with a knee exoskeleton (ABLE-KS) using both Assistance and Resistance training modes together with auditory feedback to train peak knee flexion angle. During the training, the torque provided by the ABLE-KS and the biofeedback were systematically adapted based on the subject’s performance and perceived exertion level. We carried out a comprehensive experimental analysis that evaluated a wide range of biomechanical metrics, together with usability and users’ perception metrics. We found significant improvements in peak knee flexion ( p=0.0016 ), minimum knee angle during stance ( p=0.0053 ), paretic single support time ( p=0.0087 ) and gait endurance ( p=0.022 ) when walking without the exoskeleton after the two weeks of training. Participants significantly ( p<0.00025 ) improved the knee angle during the stance and swing phases when walking with the exoskeleton powered in the high Assistance mode in comparison to the No Exo and the Unpowered conditions. No clinically relevant differences were found between Assistance and Resistance training sessions. Participants improved their performance with the exoskeleton (24-55 %) for the peak knee flexion angle throughout the training sessions. Moreover, participants showed a high level of acceptability of the ABLE-KS (QUEST 2.0 score: 4.5 ± 0.3 out of 5). Our preliminary findings suggest that the proposed training approach can produce similar or larger improvements in post-stroke individuals than other studies with knee exoskeletons that used higher training intensities.This work was supported in part by the Agency for Management of University and Research Grants (AGAUR) along with the Secretariat of Universities and Research of the Catalan Ministry of Research and Universities and the European Social Fund (ESF) under Grant 2020 FI_B 00331, in part by the Spanish Ministry of Science and Innovation (MCI)—Agencia Estatal de Investigación (AEI) under Grant PTQ2018-010227, in part by “La Caixa” Foundation under Grant LCF/TR/CC20/52480002, and in part by the Eurostars-3 Joint Program with co-financing from CDTI and the European Union’s Horizon Europe Research and Innovation Framework Program under Eureka Application Number 1789 under Grant CIIP-20221022Peer ReviewedPostprint (published version

    Inertial sensors for gait monitoring and design of adaptive controllers for exoskeletons after stroke: a feasibility study

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    Introduction: Tuning the control parameters is one of the main challenges in robotic gait therapy. Control strategies that vary the control parameters based on the user’s performance are still scarce and do not exploit the potential of using spatiotemporal metrics. The goal of this study was to validate the feasibility of using shank-worn Inertial Measurement Units (IMUs) for clinical gait analysis after stroke and evaluate their preliminary applicability in designing an automatic and adaptive controller for a knee exoskeleton (ABLE-KS). Methods: First, we estimated the temporal (i.e., stride time, stance, and swing duration) and spatial (i.e., stride length, maximum vertical displacement, foot clearance, and circumduction) metrics in six post-stroke participants while walking on a treadmill and overground and compared these estimates with data from an optical motion tracking system. Next, we analyzed the relationships between the IMU-estimated metrics and an exoskeleton control parameter related to the peak knee flexion torque. Finally, we trained two machine learning algorithms, i.e., linear regression and neural network, to model the relationship between the exoskeleton torque and maximum vertical displacement, which was the metric that showed the strongest correlations with the data from the optical system [r = 0.84; ICC(A,1) = 0.73; ICC(C,1) = 0.81] and peak knee flexion torque (r = 0.957). Results: Offline validation of both neural network and linear regression models showed good predictions (R2 = 0.70–0.80; MAE = 0.48–0.58 Nm) of the peak torque based on the maximum vertical displacement metric for the participants with better gait function, i.e., gait speed > 0.7 m/s. For the participants with worse gait function, both models failed to provide good predictions (R2 = 0.00–0.19; MAE = 1.15–1.29 Nm) of the peak torque despite having a moderate-to-strong correlation between the spatiotemporal metric and control parameter. Discussion: Our preliminary results indicate that the stride-by-stride estimations of shank-worn IMUs show potential to design automatic and adaptive exoskeleton control strategies for people with moderate impairments in gait function due to stroke.Peer ReviewedPostprint (published version

    Implantes que mejoran la calidad de vida de personas con amputaciones transfemorales

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    Nowadays, the use of prostheses for transfemoral amputees is painful, and users have poor control of leg movements. Still, the possibility to use an exoprostheses has a direct impact on the quality of life of amputees. This paper presents the project developed by TEQUIR to design a new concept of prosthesis that enables amputees to use a prosthetic leg, with a more natural and comfortable support. This innovation will have a direct impact on improving the quality of life of transfemoral amputees.En la actualidad, el uso de prótesis externas para amputados transfemorales es doloroso y los usuarios tienen un control deficiente de los movimientos de la pierna. Aun así, la posibilidad de emplear una exoprótesis tiene una repercusión directa en la calidad de vida de los amputados. En este artículo se presenta el proyecto desarrollado por TEQUIR para diseñar un nuevo concepto de prótesis que permita a los amputados emplear una pierna ortopédica con un apoyo más natural y confortable. Esta innovación tendrá un impacto directo en la mejora de la calidad de vida de los amputados transfemorales
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