Assessment of ambulation functions through kinematic analysis in individuals with stroke: a systematic review.

Jiaqi Li, Patrick W Kwong, Wang Lin, Kenneth N Fong, Wenping Wu, Ananda Sidarta
Author Information
  1. Jiaqi Li: Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
  2. Patrick W Kwong: Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China - wai-hang.kwong@polyu.edu.hk.
  3. Wang Lin: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
  4. Kenneth N Fong: Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
  5. Wenping Wu: Department of Rehabilitation Medicine, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
  6. Ananda Sidarta: Rehabilitation Research Institute of Singapore, Nanyang Technological University, Singapore, Singapore.

Abstract

INTRODUCTION: Although kinematic assessments for stroke-induced lower limb impairments offer a promising alternative to conventional scale evaluations, interpreting high-dimensional kinematic data remains challenging due to numerous metrics reported in past studies. This study aimed to provide an exhaustive overview of existing studies using kinematics data to assess the gait impairments in individuals with stroke, along with examining their clinimetric properties for future clinical applications.
EVIDENCE ACQUISITION: A systematic search was conducted across PubMed (08/2024), Scopus (08/2024), Web of Science (08/2024), CINAHL (08/2024), EMBASE (08/2024), and IEEE (08/2024). We included articles that recruited individuals over 18 years old with stroke and utilized motion capture technologies to evaluate lower limb kinematics. Similar metrics were consolidated in the analysis, and the COSMIN Risk of Bias Checklist was used to evaluate the methodological quality of studies investigating the clinimetric properties of kinematic metrics. Convergent validity of metrics was evaluated by examining their association with the Fugl-Meyer scale of lower limbs and walking speed. Moreover, the GRADE approach was used to rate the quality of evidence.
EVIDENCE SYNTHESIS: A total of 383 studies were classified into 10 categories. Seven studies on metric reliability were rated high for methodological quality. Metrics with satisfactory reliability included spatiotemporal, spatial metrics, and a data-driven score. Six studies with high methodological quality assessed convergent validity. The dynamic gait index, angular component of the coefficient of correspondence (ACC), change in cadence, stride length, and hip range of motion showed satisfactory validity. Among the 13 studies, 12 studies were rated as moderate quality of evidence using the GRADE approach.
CONCLUSIONS: There are significant variations in measurements across studies, and high-quality studies evaluating clinimetric properties are scarce. For a more standardized evidence-based approach to kinematic lower limb assessment, further high-quality research validating these assessments' clinimetric properties is essential.

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MeSH Term

Humans
Biomechanical Phenomena
Stroke
Stroke Rehabilitation
Gait Disorders, Neurologic
Lower Extremity
Reproducibility of Results

Word Cloud

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