The H2 robotic exoskeleton for gait rehabilitation after stroke: early findings from a clinical study

Magdo Bortole, Anusha Venkatakrishnan, Fangshi Zhu, Juan C Moreno, Gerard E Francisco, Jose L Pons, Jose L Contreras-Vidal, Magdo Bortole, Anusha Venkatakrishnan, Fangshi Zhu, Juan C Moreno, Gerard E Francisco, Jose L Pons, Jose L Contreras-Vidal

Abstract

Background: Stroke significantly affects thousands of individuals annually, leading to considerable physical impairment and functional disability. Gait is one of the most important activities of daily living affected in stroke survivors. Recent technological developments in powered robotics exoskeletons can create powerful adjunctive tools for rehabilitation and potentially accelerate functional recovery. Here, we present the development and evaluation of a novel lower limb robotic exoskeleton, namely H2 (Technaid S.L., Spain), for gait rehabilitation in stroke survivors.

Methods: H2 has six actuated joints and is designed to allow intensive overground gait training. An assistive gait control algorithm was developed to create a force field along a desired trajectory, only applying torque when patients deviate from the prescribed movement pattern. The device was evaluated in 3 hemiparetic stroke patients across 4 weeks of training per individual (approximately 12 sessions). The study was approved by the Institutional Review Board at the University of Houston. The main objective of this initial pre-clinical study was to evaluate the safety and usability of the exoskeleton. A Likert scale was used to measure patient's perception about the easy of use of the device.

Results: Three stroke patients completed the study. The training was well tolerated and no adverse events occurred. Early findings demonstrate that H2 appears to be safe and easy to use in the participants of this study. The overground training environment employed as a means to enhance active patient engagement proved to be challenging and exciting for patients. These results are promising and encourage future rehabilitation training with a larger cohort of patients.

Conclusions: The developed exoskeleton enables longitudinal overground training of walking in hemiparetic patients after stroke. The system is robust and safe when applied to assist a stroke patient performing an overground walking task. Such device opens the opportunity to study means to optimize a rehabilitation treatment that can be customized for individuals.

Trial registration: This study was registered at ClinicalTrials.gov ( https://ichgcp.net/clinical-trials-registry/NCT02114450 ).

Figures

Fig. 1
Fig. 1
H2 robotic exoskeleton. The six joints are powered by brushless DC motors coupled to Harmonic Drive gearboxes. All sensory information comes from sensors placed on the exoskeleton: 6 potentiometers, 18 Hall Effect sensors, 24 strain gauges and 4 foot switches. A rechargeable battery pack of lithium polymer powers the exoskeleton
Fig. 2
Fig. 2
H2 overall control architecture. All sensors in both legs are connected to the H2-Joint1 ∼6 boards that communicate to H2-ARM board through a deterministic real-time network. A Wi-Fi connection is used to capture the kinematic and kinetic data generated in the exoskeleton. A Bluetooth link connects the exoskeleton to a user interface in a smartphone
Fig. 3
Fig. 3
Control scheme for gait assistance. First, the algorithm generates an adaptative reference trajectory. Based on this reference, a force field controller guides the patient limbs, applying the necessary torque to complete gait in each joint independently
Fig. 4
Fig. 4
Stroke patient using H2 exoskeleton at the beginning of one training session
Fig. 5
Fig. 5
Hip, knee and ankle trajectories performed by all subjects. Blue line is the reference trajectory that patients are guided through by means of a force field. Red line represents the average of all steps performed by subject in the first training session. Black line is the average of all steps performed at last session. Trajectories are represented based on stride length percentage, from heel strike to next heel strike
Fig. 6
Fig. 6
Number of steps performed in all training sessions by all subjects. Although the number of steps and walk speed depends on patient’s conditions and mood on the training day, the overall results clearly show an increase over time

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