Intra-limb joint coordination measures of upper limb and hand movements: A systematic review

People with central nervous system disorders typically have difficulties in coordination of the upper limb and hand movements, which significantly impairs their activities of daily living. Laboratory-based measures can provide quantitative and objective information about intra-limb coordination to aid the rehabilitation process of this population. However, there is currently no comprehensive review of laboratory-based measures.

The aim of this review was to identify and summarize laboratory-based intra-limb coordination measures for different upper limb and hand movements.

Searches were performed in the CINAHL, Embase, IEEE Xplore, MEDLINE, PubMed and Web of Science databases to identify studies published between 2013 and 2022. Two authors independently performed paper selection, data extraction and quality assessment.

21 papers were identified, and six types of coordination measures were classified. These included principal component analysis, continuous relative phase analysis, correlation analysis, regression analysis, uncontrolled manifold analysis, and uncorrelated surrogate data analysis, in descending order of occurrence. Regarding psychometric properties, all measures demonstrated good discriminative validity. However, only the principal component analysis approach and the continuous relative phase analysis approach were found to have good convergent validity and responsiveness, respectively. In terms of their practicality, these measures were primarily utilized for quantifying coordination in individuals with neurological disorders, with a greater emphasis on the coordination of upper limb movements rather than hand movements.

This review summarized and critiqued the characteristics of six types of joint coordination measures. Researchers and clinicians should therefore select appropriate measures based on individual needs. Future research should continue on analysing coordination in individuals with pathological conditions and exploring the application of these measures in quantifying hand movement coordination, to advance current knowledge and inform rehabilitation practices.