Abstract
Kinematic synergies (kSYN) provide an approach to quantify the covariation of joint motions and to explain the mechanisms underlying human motor behavior. A low-dimensional control strategy by means of the activation of a moderate number of kSYN would simplify the performance of complex motor tasks. The purpose of this study was to examine similarities between the kSYN of varying locomotion tasks: straight-line walking, walking a 90° spin turn and walking upstairs. Task-specific kSYN were extracted from full body kinematic recordings of 13 participants by principal component analysis. The first five kSYN accounting for most of the variance within each task were selected for further analysis following previous studies. The similarities between the kSYN of the three different locomotion tasks were quantified by calculating cosine similarities (SIM), as a vector-based similarity measure ranging from 0 (no similarity) to 1 (high similarity), between absolute principal component loading vectors. A SIM between two kSYN > 0.8 was interpreted as highly similar. Two to three highly similar kSYN were identified when comparing two individual tasks with each other. One kSYN, primarily characterized by anteversion and retroversion of the arms and legs, were found to be similar in all three tasks. Additional kSYN that occurred between individual tasks reflected mainly an upwards/downwards movement of the body or a countercyclical knee flexion/extension. The results demonstrate that the three investigated locomotion tasks are characterized by kSYN and that certain kSYN repeatedly occur across the three locomotion tasks. PCA yields kSYN which are in descent order according to their amount of total variance accounted for. Referring to the placing of a kSYN within the order as priorization, we found a change in priorization of repeatedly occurring kSYN across the individual tasks. The findings support the idea that movements can be efficiently performed through a flexible combination of a lower number of control-relevant variables.
Highlights
The true complexity of the control processes involved in ordinary human movements is masked by the ease of their execution (Wolpert et al, 2013)
This leads to another fundamental question of motor control research: namely, how this versatility is implemented in the central nervous system (CNS)
In line with related studies on whole body gait patterns for straight-line walking (Daffertshofer et al, 2004; Majed et al, 2017), we found a small number of compositional elements that described the essential features of gait: a combination of five Kinematic synergies (kSYN) explained 83.9% of the variance in the kinematic data
Summary
The true complexity of the control processes involved in ordinary human movements is masked by the ease of their execution (Wolpert et al, 2013). The human central nervous system (CNS) consists of billions of interconnected neurons, and the musculoskeletal system is composed of approximately 700 muscles and over 300 mechanical degrees of freedom (Bruton and O’Dwyer, 2018). This highly redundant motor system enables us to achieve movement in countless ways. We learn an enormous number of skills, such as raising a hand or playing sports, in the course of our lives and even when the execution of such tasks seems to be easy, it requires a fine tuning of the CNS This leads to another fundamental question of motor control research: namely, how this versatility is implemented in the CNS. Finding answers to these two questions through analyzing the coordination of human movements, has—besides other challenges such as dealing with non-linearities within the motor system (Franklin and Wolpert, 2011)—become a central issue in motor control research (e.g., Bizzi et al, 1991; Wolpert and Kawato, 1998; Scholz and Schöner, 1999; Todorov and Jordan, 2002; d’Avella et al, 2003; Daffertshofer et al, 2004; Lacquaniti et al, 2012)
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