Bad research: you didn't tell us how close this got to 100% recovery while still in the hospital! That is the only goal in stroke and if you're not measuring that, you'll never get there!
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Therapeutic effects of powered exoskeletal robot-assisted gait training in inpatients in the early stage after stroke: a pilot case-controlled study
Journal of NeuroEngineering and Rehabilitation volume 21, Article number: 206 (2024)
Abstract
Background
Robot-assisted rehabilitation is considered beneficial for functional recovery in patients with stroke, but the therapeutic effect remains inconclusive. The present study investigated the therapeutic effects of gait training assisted by a user-initiated powered exoskeletal robot (UIPER) in patients in the early stage after stroke. We also characterized patients’ improvement by analyzing chronological changes in clinical measurements together with gait parameters obtained from internal sensors in the exoskeletal robot.
Methods
In this pilot case-controlled study, 17 and 81 patients with stroke onset durations of < 3 months were included in the robot-assisted combined with conventional treatment (RT + CT) group and conventional treatment only (CT) group, respectively. The UIPER, which provides knee flexion and extension support and has hip and knee sensors, was applied to guide gait performance in the RT + CT group. The patients in the RT + CT group received robot-assisted gait training for 40 min/ session, 1 session a day, and 2–3 sessions a week (6 sessions in total). The primary outcome was the proportion of patients reaching the minimum clinically important difference (MCID) in the 5-meter walking speed (5MWS) assessment, and the secondary outcomes were the MCID for the six-minute walking test, the Berg Balance Scale, the Barthel Index, the Fugl-Meyer assessment, and the timed up and go test before, during, and after the interventions. Gait parameters of the hip and knee were evaluated at baseline, midterm, and final sessions.
Results
Gait function improved in both groups after the intervention (both P < 0.05). The primary outcome showed that a greater proportion of patients reached the MCID for the 5MWS in the RT + CT group than in the CT group (70.6 vs. 43.2%, P = 0.040;
= 0.220). Gait analysis revealed improvements in gait in the RT + CT group, as indicated by increases in the perimeter and area of the hip–knee cyclogram, as well as the range of motion in the hip joint.
Conclusions
Gait training assisted by UIPER facilitates the recovery of walking speed and activities of daily living in patients with stroke, and these improvements may be related to improvements in gait parameters. Randomized controlled studies with larger sample sizes are needed to confirm these findings.
Trial registration
This trial was approved by the Institutional Review Board of Chang Gung Medical Foundation (No. 202200822B0).
Background
The majority of patients with stroke have a clinical presentation of hemiplegia, which can cause a loss of locomotor function [1, 2]. Restoration of walking ability is thus among the most important objectives of rehabilitation, particularly for those in the early stages after stroke. A common therapeutic approach is to correct the patient’s gait pattern, such as hip flexion, for daily activities in patients whose lower limb muscle power has partly recovered [3,4,5]. However, another challenge emerges during this recovery stage, as patients tend to develop unwanted compensatory movements manifested by exaggerated synergistic patterns [5, 6]. The resulting alternation of hip-knee coordination results in shorter step lengths on the affected side as well as a slower walking speed and unsymmetric gait [7,8,9]. The mechanical force exerted on the knee assists both extension and flexion of the knee, an approach that could potentially compensate for the inadequate torque in the affected side and thus enhance symmetry of weight-bearing during walking.
It is hypothesized that, as patients’ ambulatory ability gradually improve along the course of recovery, rehabilitation robots will progressively reduce the magnitude of assistance over time. Over recent decades, lower-limb exoskeletal robots have offered a novel approach for facilitating gait recovery in patients with stroke. Exoskeletal robots typically provide assistance for overground walking through advanced engineering using user-initiated, robot-initiated, and adaptive control with adjustable personalized parameters, thus offering precise robot actuation to augment the movement of the lower limbs during both the stance and swing phases of the gait cycle [10,11,12,13]. However, because motor capacity varies widely among patients with stroke, different motor recovery stages of post-stroke gait are supposed to benefit from specific type of rehabilitation robots, each of which was designed to address distinct phases of motor recovery [14,15,16]. Treadmill-based systems such as the Lokomat, a device with hip and knee actuations, ankle support, and body suspension, are suited for early-stage stroke patients who have minimal or no hip activation. Other hip-knee-ankle systems, such as the full-body, trunk-supported Ekso or the bioelectrically controlled Hybrid Assistive Limb (HAL), can facilitate weight-bearing, ground contact, and hip extension to trigger exoskeletal knee flexion. In later stages of motor recovery, a user-initiated control mechanism is essential for improving patient-driven gait, particularly for helping patients to perform knee flexion followed by hip activation. It is important to note that robots with this functionality is not yet widely applied clinically.
For this purpose, the Keeogo, a user-initiated powered exoskeletal robot (UIPER), is primarily designed to assist the patient with mobility impairments with a higher motor function stage for enhancing their locomotive abilities in communities and daily activities, such as walking, stair climbing, and transitioning [10]. Based on this design concept, the robot has knee motors but no hip motors and uses sensors in the hip and knee joints to detect and interpret the user’s intended movement, and then applies complementary torque through knee motors to assist performing stance and swing phases in gait. Although, the device has shown its potential to benefit motor control, postural stability, and movement kinetics in patients with stroke [17], its treatment effects and related gait parameters remain unclear.
Gait parameters during walking play a crucial role in determining the optimal settings for the application of UIPER on patients with stroke. Parameters such as walking speed [18] and gait symmetry [19, 20] are commonly used for assessing gait performance in the patients with stroke. The cyclogram, a measurement of inter-joint coordination during walking obtained from the data recorded by cameras or wearable sensers [21], provides a continuous, quantitively, and visual depiction of how two joints coordinate throughout a gait cycle [22]. For example, the cyclogram of normal gait obtained from a healthy participant shows smooth and consistent patterns, while that in patients with stroke would reflect deviations in joint coordination. In addition, range of motion, joint symmetry, gait similarity between both affected and unaffected sides, and the length of the gait trajectory can also be analyzed from the cyclogram. Therefore, analyzing kinematic parameters from sensors to objectively measure changes in gait performance can help understand how robot-assisted gait training facilitates post-stroke gait.
In this pilot study, we explored the therapeutic effects of the exoskeletal robot-assisted gait training (ERGT) in patients with stroke who demonstrated a relative higher levels of gait function at the early recovery stage, qualifying them for the UIPER category. A key innovation of our study was not only evaluating the therapeutic outcome, but also analyzing the alterations of gait parameters using data recorded by the internal sensors of the exoskeletal robot for characterizing how the robot enhance the gait. This process represents a state-of-the-art approach for objectively guiding and refining robot-assisted gait training throughout the rehabilitation in patients with stroke. Furthermore, this information offers critical insights for optimizing the selection of lower-limb robotic exoskeletons tailored to the specific needs of individual stroke patients for enhancing therapeutic outcomes and personalization of treatment.
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