Adapted Assistance and Resistance Training With a Knee Exoskeleton After Stroke

de Miguel Fernández, Jesús; Rey-Prieto, Marta; Rio, Miguel Salazar-Del; López-Matas, Helena; Guirao-Cano, Lluis; Font-Llagunes, Josep M.; Lobo-Prat, Joan

doi:10.1109/tnsre.2023.3303777

Cited by 7 publications

(3 citation statements)

References 47 publications

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“…The ABLE-KS is a wearable, unilateral, powered knee exoskeleton that provides knee stability assistance during stance, and flexion and extension assistance during swing. Further details about the knee exoskeleton can be found in de Miguel-Fernández et al ( 2023b ). The synchronization with the user is based on the detection of the foot–ground contacts of both legs following a threshold-based algorithm that uses shank angle and velocity.…”

Section: Methodsmentioning

confidence: 99%

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

De Miguel-Fernández,

Salazar-Del Rio,

Rey-Prieto

et al. 2023

Front. Bioeng. Biotechnol.

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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.

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Section: Methodsmentioning

confidence: 99%

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

De Miguel-Fernández,

Salazar-Del Rio,

Rey-Prieto

et al. 2023

Front. Bioeng. Biotechnol.

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“…The effectiveness of RE in stroke patients primarily pertains to the correction of abnormal gait patterns and the enhancement of walking ability. Additional reported benefits include improved cardiopulmonary function, alleviation of lower limb spasticity, enhancement of patients' balance capabilities, promotion of proprioceptive recovery, and increased neural plasticity (Molteni et al, 2020;Herrin et al, 2023;Lee et al, 2023;Rey-Prieto et al, 2023). Currently, most RE on the market offer dual functionalities, as lower limb rehabilitation in clinical settings is predominantly based on gait.…”

Section: The Efficacy Of Re-assisted Walking Therapy For Stroke Patientsmentioning

confidence: 99%

Robotic exoskeleton-assisted walking rehabilitation for stroke patients: a bibliometric and visual analysis

Wen,

Huang,

Liu

et al. 2024

Front. Bioeng. Biotechnol.

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Objective:This study aimed to conduct a bibliometric analysis of the literature on exoskeleton robot assisted walking rehabilitation for stroke patients in the Web of Science Core Collection over the past decade.Method:Retrieved literature on exoskeleton robot assisted gait training for stroke hemiplegic patients from the Web of Science Core Collection from 1 January 2014 to 31 January 2024. The search method was topic search, and the types of documents were “article, meeting abstract, review article, early access.” CiteSpace was used to analyze the search results from countries, institutions, keywords, cited references and cited authors.Result:A total of 1,349 articles were retrieved, and 1,034 were ultimately included for visualization analysis. The annual publication volume showed an upward trend, with countries, institutions, and authors from Europe and America in a leading position. The core literature was also published by authors from European and American countries. The keywords were divided into 8 clusters: # 0 soft robotic exit, # 1 robot assisted gain training, # 2 multiple scales, # 3 magnetic rheological brake, # 4 test retest reliability, # 5 electromechanical assisted training, # 6 cerebra salary, and # 7 slow gain. The early research direction focused on the development of exoskeleton robots, verifying their reliability and feasibility. Later, the focus was on the combination of exoskeleton robot with machine learning and other technologies, rehabilitation costs, and patient quality of life.Conclusion:This study provides a visual display of the research status, development trends, and research hotspots, which helps researchers in this field to grasp the research hotspots and choose future research directions.

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“…In the stance phase, notably, knee hyperextension is observed in about 40-68% of stroke patients, significantly affecting gait speed and symmetry, and increasing the metabolic cost of walking [1,16,17]. Addressing these abnormal gaits requires innovative solutions like the knee-actuated exoskeletal gait orthosis (KAEGO), which assists knee joint flexion and extension based on the patient's gait intentions [16,[18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Motion-Based Control Strategy of Knee Actuated Exoskeletal Gait Orthosis for Hemiplegic Patients: A Feasibility Study

Heo,

Choi,

Lee

et al. 2023

Applied Sciences

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In this study, we developed a unilateral knee actuated exoskeletal gait orthosis (KAEGO) for hemiplegic patients to conduct gait training in real-world environments without spatial limitations. For this purpose, it is crucial that the controller interacts with the patient’s gait intentions. This study newly proposes a simple gait control strategy that detects the gait state and recognizes the patient’s gait intentions using only the motion information of the lower limbs obtained from an embedded inertial measurement units (IMU) sensor and a knee angle sensor without employing ground reaction force (GRF) sensors. In addition, a torque generation method based on negative damping was newly applied as a method to determine the appropriate amount of assistive torque to support flexion or extension movements of the knee joint. To validate the performance of the developed KAEGO and the effectiveness of our proposed gait control strategy, we conducted walking tests with a hemiplegic patient. These tests included verifying the accuracy of gait recognition and comparing the metabolic cost of transport (COT). The experimental results confirmed that our gait control approach effectively recognizes the patient’s gait intentions without GRF sensors and reduces the metabolic cost by approximately 8% compared to not wearing the device.

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Adapted Assistance and Resistance Training With a Knee Exoskeleton After Stroke

Cited by 7 publications

References 47 publications

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

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

Robotic exoskeleton-assisted walking rehabilitation for stroke patients: a bibliometric and visual analysis

Motion-Based Control Strategy of Knee Actuated Exoskeletal Gait Orthosis for Hemiplegic Patients: A Feasibility Study

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