Assessment Methods of Post-stroke Gait: A Scoping Review of Technology-Driven Approaches to Gait Characterization and Analysis

Abstract

Background: Gait dysfunction or impairment is considered one of the most common and devastating physiological consequences of stroke, and achieving optimal gait is a key goal for stroke victims with gait disability along with their clinical teams. Many researchers have explored post stroke gait, including assessment tools and techniques, key gait parameters and significance on functional recovery, as well as data mining, modeling and analyses methods.Research Question: This study aimed to review and summarize research efforts applicable to quantification and analyses of post-stroke gait with focus on recent technology-driven gait characterization and analysis approaches, including the integration of smart low cost wearables and Artificial Intelligence (AI), as well as feasibility and potential value in clinical settings.Methods: A comprehensive literature search was conducted within Google Scholar, PubMed, and ScienceDirect using a set of keywords, including lower extremity, walking, post-stroke, and kinematics. Original articles that met the selection criteria were included.Results and Significance: This scoping review aimed to shed light on tools and technologies employed in post stroke gait assessment toward bridging the existing gap between the research and clinical communities. Conventional qualitative gait analysis, typically used in clinics is mainly based on observational gait and is hence subjective and largely impacted by the observer's experience. Quantitative gait analysis, however, provides measured parameters, with good accuracy and repeatability for the diagnosis and comparative assessment throughout rehabilitation. Rapidly emerging smart wearable technology and AI, including Machine Learning, Support Vector Machine, and Neural Network approaches, are increasingly commanding greater attention in gait research. Although their use in clinical settings are not yet well leveraged, these tools promise a paradigm shift in stroke gait quantification, as they provide means for acquiring, storing and analyzing multifactorial complex gait data, while capturing its non-linear dynamic variability and offering the invaluable benefits of predictive analytics.

Reliability of IMU-Based Gait Assessment in Clinical Stroke Rehabilitation

“…In recent years, several studies have demonstrated that portable devices, such as electromygraphy, insole foot pressure sensors, motion capture systems, and inertial measurement units (IMUS), can objectively measure gait and be used to compute gait features [ 18 , 19 , 20 , 21 , 22 , 23 ]. Of all of these devices, IMUs might be the most feasible for clinical use because measuring with IMUs requires no expensive equipment, and they are easy to operate.…”

“…This indicates that IMUs can be used to monitor gait recovery; hence, they function as a clinical evaluation tool. Despite the advantages of using IMUs to assess gait, regular IMU-based measurements have yet to be adopted by clinicians [ 21 , 29 ]. This is because IMU data needs to be collected, processed, and converted to clinically relevant information, requiring time, processing tools, and expertise.…”

Assessment of Agreement Between a New Application to Compute the Wisconsin Gait Score and 3-Dimensional Gait Analysis, and Reliability of the Application in Stroke Patients

“…However, 3DGA is rather costly, and the related measurements provide a large body of data to be interpreted, which may be inconvenient in the clinical setting. Due to these drawbacks, many researchers worldwide are looking for new solutions specifically enabling gait analysis in patients after stroke (Ferrarello et al, 2013;Begg et al, 2014;Solanki and Lahiri, 2018;Li et al, 2019;Tian et al, 2019;Seo et al, 2020;Iosa et al, 2021;Mohan et al, 2021;Wang et al, 2021). As an example, Seo et al proposed an assessment method referred to as clinometric gait analysis and applying a smart insoles technology.…”

Methodological Considerations in Assessing Interlimb Coordination on Poststroke Gait: A Scoping Review of Biomechanical Approaches and Outcomes

“…However, to the best of our knowledge, there is no consensus regarding the method and its suitability for assessing gait interlimb coordination in poststroke patients [31].…”