Analysis of movement quality in full-body physical activities

Full-body human movement is characterized by fine-grain expressive qualities that humans are easily capable of exhibiting and recognizing in others' movement. In sports (e.g., martial arts) and performing arts (e.g., dance), the same sequence of movements can be performed in a wide range of ways characterized by different qualities, often in terms of subtle (spatial and temporal) perturbations of the movement. Even a non-expert observer can distinguish between a top-level and average performance by a dancer or martial artist. The difference is not in the performed movements-the same in both cases-but in the \u201cquality\u201d of their performance. In this article, we present a computational framework aimed at an automated approximate measure of movement quality in full-body physical activities. Starting from motion capture data, the framework computes low-level (e.g., a limb velocity) and high-level (e.g., synchronization between different limbs) movement features. Then, this vector of features is integrated to compute a value aimed at providing a quantitative assessment of movement quality approximating the evaluation that an external expert observer would give of the same sequence of movements. Next, a system representing a concrete implementation of the framework is proposed. Karate is adopted as a testbed. We selected two different katas (i.e., detailed choreographies of movements in karate) characterized by different overall attitudes and expressions (aggressiveness, meditation), and we asked seven athletes, having various levels of experience and age, to perform them. Motion capture data were collected from the performances and were analyzed with the system. The results of the automated analysis were compared with the scores given by 14 karate experts who rated the same performances. Results show that the movement-quality scores computed by the system and the ratings given by the human observers are highly correlated (Pearson's correlations r = 0.84, p = 0.001 and r = 0.75, p = 0.005)

Evaluating Movement Quality Through Intrapersonal Synchronization

We present a method to measure intrapersonal synchronization of movement from motion capture data, and we show that our method is effective in classifying the level of skills of athletes performing karate kata. Our method is based on detecting relevant peaks of acceleration of limbs (arms and legs) and measuring their synchronization. We run a multiscale analysis, based on topological persistence, to rank the importance of peaks of acceleration. The resulting impulse signals are processed next with a multievent class synchronization algorithm, in order to define an overall synchronization index that scores the level of intrapersonal synchronization with a single scalar value. We build a basic multiclass classifier, which uses just the means of indexes computed on the different classes in the training set. We make a statistical analysis and a cross validation of the classifier on real data. Performances by athletes from three levels of skill have been recorded, classified by experts, and used to test our method. Cross validation of the classifier is performed by leave-one-out and bootstrap resampling. Results show that our method can classify correctly with very high probability (beyond $ext99 ext$), while it succeeds on $ext100 ext$ of the data used in cross validation

Interpersonal entrainment in music performance: Theory, method and model

Interpersonal musical entrainment—temporal synchronization and coordination between individuals in musical contexts—is a ubiquitous phenomenon related to music’s social functions of promoting group bonding and cohesion. Mechanisms other than sensorimotor synchronization are rarely discussed, while little is known about cultural variability or about how and why entrainment has social effects. In order to close these gaps, we propose a new model that distinguishes between different components of interpersonal entrainment: sensorimotor synchronization—a largely automatic process manifested especially with rhythms based on periodicities in the 100–2000 ms timescale—and coordination, extending over longer timescales and more accessible to conscious control. We review the state of the art in measuring these processes, mostly from the perspective of action production, and in so doing present the first cross-cultural comparisons between interpersonal entrainment in natural musical performances, with an exploratory analysis that identifies factors that may influence interpersonal synchronization in music. Building on this analysis we advance hypotheses regarding the relationship of these features to neurophysiological, social, and cultural processes. We propose a model encompassing both synchronization and coordination processes and the relationship between them, the role of culturally shared knowledge, and of connections between entrainment and social processes