Background: The SCI-GDI is an accurate and effective metric to summarize gait kinematics in adults with SCI. It is usually computed with the information registered with a photogrammetry system because it requires accurate information of pelvic and hip movement in the three anatomic planes, which is hard to record with simpler systems. Additionally, due to being developed from the GDI, the SCI-GDI is built upon nine joint movements selected for a pediatric population with cerebral palsy, for which the GDI was originally developed, but those nine movements are not necessarily as meaningful for adults with SCI.
View Article and Find Full Text PDFBackground: To overcome the application limitations of functional electrical stimulation (FES), such as fatigue or nonlinear muscle response, the combination of neuroprosthetic systems with robotic devices has been evaluated, resulting in hybrid systems that have promising potential. However, current technology shows a lack of flexibility to adapt to the needs of any application, context or individual. The main objective of this study is the development of a new modular neuroprosthetic system suitable for hybrid FES-robot applications to meet these needs.
View Article and Find Full Text PDFFront Bioeng Biotechnol
August 2024
When assessing gait analysis outcomes for clinical use, it is indispensable to use an accurate system ensuring a minimal measurement error. Inertial Measurement Units (IMUs) are a versatile motion capture system to evaluate gait kinematics during out-of-lab activities and technology-assisted rehabilitation therapies. However, IMUs are susceptible to distortions, offset and drifting.
View Article and Find Full Text PDFBackground: Despite technical advances in the field of wearable robotic devices (WRD), there is still limited user acceptance of these technologies. While usability often comes as a key factor influencing acceptance, there is a scattered landscape of definitions and scopes for the term. To advance usability evaluation, and to integrate usability features as design requirements during technology development, there is a need for benchmarks and shared terminology.
View Article and Find Full Text PDFBackground: The Gait Deviation Index for Spinal Cord Injury (SCI-GDI) was recently proposed as a dimensionless multivariate kinematic measure based on 21 gait features derived from 3-dimensional kinematic data which quantifies gait impairment of adult population with incomplete spinal cord injury (iSCI) relative to the normative gait of a healthy group. Nevertheless, no validity studies of the SCI-GDI have been published to date.
Objective: To assess the construct validity of the SCI-GDI in adult population following iSCI.
Objective: We aim to determine a comprehensive set of requirements, perceptions, and expectations that people with spinal cord injury (SCI) and the clinicians in charge of their rehabilitation have regarding the use of wearable robots (WR) for gait rehabilitation.
Background: There are concerns due to the limited user acceptance of WR for gait rehabilitation. Developers need to emphasize understanding the needs and constraints of all stakeholders involved, including the real-life dynamics of rehabilitation centers.
The Gait Deviation Index (GDI) is a dimensionless multivariate measure of overall gait pathology represented as a single score that indicates the gait deviation from a normal gait average. It is calculated using kinematic data recorded during a three-dimensional gait analysis and an orthonormal vectorial basis with 15 gait features that was originally obtained using singular value decomposition and feature analysis on a dataset of children with cerebral palsy. Ever since, it has been used as an outcome measure to study gait in several conditions, including spinal cord injury (SCI).
View Article and Find Full Text PDFFront Hum Neurosci
April 2022
The Gait Deviation Index (GDI) is a multivariate measure of overall gait pathology based on 15 gait features derived from three-dimensional (3D) kinematic data. GDI aims at providing a comprehensive, easy to interpret, and clinically meaningful metric of overall gait function. It has been used as an outcome measure to study gait in several conditions: cerebral palsy (CP), post-stroke hemiparetic gait, Duchenne muscular dystrophy, and Parkinson's disease, among others.
View Article and Find Full Text PDFBackground: Add-on robot-mediated therapy has proven to be more effective than conventional therapy alone in post-stroke gait rehabilitation. Such robot-mediated interventions routinely use also visual biofeedback tools. A better understanding of biofeedback content effects when used for robotic locomotor training may improve the rehabilitation process and outcomes.
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