JcvPCA and JsvCRP : a set of metrics to evaluate changes in joint coordination strategies (2505.09020v1)

Abstract: Characterizing changes in inter-joint coordination presents significant challenges, as it necessitates the examination of relationships between multiple degrees of freedom during movements and their temporal evolution. Existing metrics are inadequate in providing physiologically coherent results that document both the temporal and spatial aspects of inter-joint coordination. In this article, we introduce two novel metrics to enhance the analysis of inter-joint coordination. The first metric, Joint Contribution Variation based on Principal Component Analysis (JcvPCA), evaluates the variation in each joint's contribution during series of movements. The second metric, Joint Synchronization Variation based on Continuous Relative Phase (JsvCRP), measures the variation in temporal synchronization among joints between two movement datasets. We begin by presenting each metric and explaining their derivation. We then demonstrate the application of these metrics using simulated and experimental datasets involving identical movement tasks performed with distinct coordination strategies. The results show that these metrics can successfully differentiate between unique coordination strategies, providing meaningful insights into joint collaboration during movement. These metrics hold significant potential for fields such as ergonomics and clinical rehabilitation, where a precise understanding of the evolution of inter-joint coordination strategies is crucial. Potential applications include evaluating the effects of upper limb exoskeletons in industrial settings or monitoring the progress of patients undergoing neurological rehabilitation.

Evaluation of Changes in Joint Coordination Strategies Using JcvPCA and JsvCRP Metrics

This paper introduces two innovative metrics aiming to enhance the analysis of inter-joint coordination during movement tasks: Joint Contribution Variation based on Principal Component Analysis (JcvPCA) and Joint Synchronization Variation based on Continuous Relative Phase (JsvCRP). The need for these metrics arises from existing approaches' limitations in effectively quantifying the temporal and spatial aspects of joint coordination across multiple degrees of freedom.

Summary of JcvPCA and JsvCRP Metrics

JcvPCA Metric:

1. Objective: JcvPCA quantifies differences in joint contributions to a given movement task by utilizing PCA. It allows a comparison of joint participation across datasets, which include multiple joint trajectories.
2. Implementation: The metric requires selecting a reference dataset to define a PCA space and then projecting another dataset into this space. The absolute differences in PCA component weights between the datasets are calculated, offering insights into variations in joint utilization.

JsvCRP Metric:

1. Objective: JsvCRP provides a measure of joint synchronization by analyzing CRP between pairs of joints. It focuses on capturing temporal aspects of joint coordination strategies.
2. Implementation: CRP is computed by creating phase portraits that integrate position and velocity data. The variations between CRP curves are quantified by calculating the area between these curves across datasets, highlighting differences in synchronization.

Validation and Results

The metrics were validated using both simulated and experimental datasets. In simulated tests, variations in joint contribution and synchronization were effectively discerned using the proposed metrics, with clear interpretations offered for the numerical values obtained.

The experimental setup involved recording different coordination strategies using an upper limb exoskeleton. This practical application demonstrated the potential utility of JcvPCA and JsvCRP for characterizing physiological and non-physiological movement adaptations. Variability thresholds derived from physiological datasets informed the analysis, allowing the differentiation between natural variability and meaningful changes in coordination.

Implications and Future Perspectives

Theoretical Implications

The theoretical contribution of JcvPCA and JsvCRP lies in offering a structured approach to quantifying changes in coordination strategies. By providing mechanistic interpretations of joint utilization and synchronization, these metrics could advance our understanding of motor control and learning processes in both typical and atypical populations.

Practical Implications

Practically, these metrics show promise for applications across various domains such as rehabilitation, sports science, and ergonomics. For instance, they could aid in optimizing training protocols in sports by identifying effective joint use or detecting maladaptive patterns in individuals using assistive devices like exoskeletons.

Future Developments

Future work could focus on refining these metrics for higher dimensional datasets by defining optimal thresholds for PCA component selection and exploring alternative CRP comparison methods. Expanding the framework to incorporate more complex movement scenarios may also be beneficial, especially in capturing the nuances of inter-joint coordination in dynamic environments.

In conclusion, JcvPCA and JsvCRP provide valuable tools for advancing the quantification and understanding of joint coordination strategies, presenting opportunities for broad applications while encouraging new lines of inquiry in human movement analysis.