Enhanced Rehabilitation Outcomes of Robotic-Assisted Gait Training with EksoNR Lower Extremity Exoskeleton in 19 Stroke Patients

Wiśniowska-Szurlej, Agnieszka; Wołoszyn, Natalia; Brożonowicz, Justyna; Ciąpała, Gabriela; Pietryka, Kamil; Grzegorczyk, Joanna; Leszczak, Justyna; Ćwirlej-Sozańska, Agnieszka; Sozański, Bernard; Korczowski, Bartosz

doi:10.12659/msm.940511

Cited by 3 publications

(2 citation statements)

References 45 publications

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“…The exoskeleton provided only information about the number of steps, walking time, and time of verticalization 24 , thus posing the need for an additional device such as smart insoles for assessing gait characteristics.…”

Section: Devicesmentioning

confidence: 99%

Integration of Smart Insoles for Gait Assessment in Exoskeleton-assisted Rehabilitation

D'Arco,

Wang,

Zheng

2024

Preprint

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A robotic exoskeleton enables individuals with limited or no mobility to engage in moderate exercises, promoting physical fitness and overall well-being. Exoskeletons, however, do not provide insights into gait patterns monitoring and analysis over time. This study proposes the integration of smart insoles as a cost-effective and non-invasive assistant for gait assessment in exoskeleton-assisted rehabilitation. The study, spanning 12 weeks, comprised three assessment sessions involving a total of 10 participants, including three healthy individuals, one stroke, one spinal cord injury, one traumatic brain injury, and four multiple sclerosis subjects. Gait phases were identified using a Finite State Machine with transitions guided by the predictions of a fuzzy c-means clustering algorithm. Kinematic and kinetic analyses highlighted disparities in stride time, cadence, stance time, and the trajectories of the centre of pressure. Despite these differences, individuals with multiple sclerosis showed no statistical differences from healthy subjects, underscoring the influence of the exoskeleton even in the absence of lower limb power. An analysis of acceptability demonstrated that participants found the smart insoles comfortable and expressed a willingness to employ them for future rehabilitation purposes. In conclusion, smart insoles can provide additional insights about users' gait compared to exoskeletons alone, allowing the progress of individuals involved in rehabilitation to be assessed over time, and helping clinicians to develop tailored rehabilitation plans.

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Section: Devicesmentioning

confidence: 99%

Integration of Smart Insoles for Gait Assessment in Exoskeleton-assisted Rehabilitation

D'Arco,

Wang,

Zheng

2024

Preprint

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“…Improvement of walking ability is one of the crucial rehabilitation goals for patients with hemiplegic stroke, and several studies have used improvement of walking ability as an outcome [1][2][3]. Robotic-assisted overground gait training and increasing the training time for treadmill-walking practice by wearable robot improved walking ability compared with a control [4,5]. Additionally, increasing daily physical therapy training time may contribute to improved walking ability in patients with severe motor paralysis of the lower extremities [6].…”

Section: Introductionmentioning

confidence: 99%

Gait training with a safety suspension device accelerates the achievement of supervision level walking in subacute stroke: a randomized controlled trial

Kawakami,

Miyasaka,

Hioki

et al. 2024

International Journal of Rehabilitation Research

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Practicing walking in a safety suspension device allows patients to move freely and without excessive reliance on a therapist, which requires correcting errors and may facilitate motor learning. This opens the possibility that patients with subacute stroke may improve their walking ability more rapidly. Therefore, we tested the hypothesis that overground gait training in a safety suspension device will result in achieving faster supervision-level walking than gait training without the suspension device. Twenty-seven patients with stroke admitted to the rehabilitation ward with functional ambulation categories (FAC) score of 2 at admission were randomly allocated to safety suspension-device group (SS group) or conventional assisted-gait training group (control group). In addition to regular physical therapy, each group underwent additional gait training for 60 min a day, 5 days a week for 4 weeks. We counted the days until reaching a FAC score of 3 and assessed the probability using Cox regression models. The median days required to reach a FAC score of 3 were 7 days for the SS group and 17.5 days for the control group, which was significantly different between the groups (P < 0.05). The SS group had a higher probability of reaching a FAC score of 3 after adjusting for age and admission motor impairment (hazard ratio = 3.61, 95% confidence interval = 1.40–9.33, P < 0.01). The gait training with a safety suspension device accelerates reaching the supervision-level walking during inpatient rehabilitation. We speculate that a safety suspension device facilitated learning by allowing errors to be experienced and correct in a safe environment.

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Assessment of wearable robotics performance in patients with neurological conditions

Gerez,

Micera,

Nuckols

et al. 2024

Current Opinion in Neurology

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Purpose of review While wearable robotics is expanding within clinical settings, particularly for neurological rehabilitation, there is still a lack of consensus on how to effectively assess the performance of these devices. This review focuses on the most common metrics, whose selection and design are crucial for optimizing treatment outcomes and potentially improve the standard care. Recent findings The literature reveals that while wearable robots are equipped with various embedded sensors, most studies still rely on traditional, nontechnological methods for assessment. Recent studies have shown that, although quantitative data from embedded sensors are available (e.g., kinematics), these are underutilized in favor of qualitative assessments. A trend toward integrating automatic assessments from the devices themselves is emerging, with a few notable studies pioneering this approach. Summary Our analysis suggests a critical need for developing standardized metrics that leverage the data from embedded sensors in wearable robots. This shift could enhance the accuracy of patient assessments and the effectiveness of rehabilitation strategies, ultimately leading to better patient outcomes in neurological rehabilitation.

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Enhanced Rehabilitation Outcomes of Robotic-Assisted Gait Training with EksoNR Lower Extremity Exoskeleton in 19 Stroke Patients

Cited by 3 publications

References 45 publications

Integration of Smart Insoles for Gait Assessment in Exoskeleton-assisted Rehabilitation

Integration of Smart Insoles for Gait Assessment in Exoskeleton-assisted Rehabilitation

Gait training with a safety suspension device accelerates the achievement of supervision level walking in subacute stroke: a randomized controlled trial

Assessment of wearable robotics performance in patients with neurological conditions

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