By Dr Patricia van de Walle and Dr Pieter Meyns.

Toddlers learn to walk with their arms in an elevated position. As gait matures, a reciprocal arm swing with the hands at the height of the hips and both arms alongside the trunk quickly appears. Arm swing is an integral part of typical walking, most likely with the goal of minimizing energy expenditure and optimizing stability. However, arm swing is not always well coordinated in patient populations, where often the position of the arms remains elevated. This altered arm swing can be the result of compensation strategies, altered gross motor function or a combination of both, and compromises the role of arm swing during typical walking. There are several movement disorders in children that affect not only lower but also upper limb movements during walking. As such, age-related reference data of arm movements during walking are imperative to allow clinicians to assess whether deviations are related to immaturity or whether they are caused by an underlying pathology or need for compensation.

Gait data of 102 participants between 3 to 35 years old was collected using a full-body marker set (Vicon, Plug-In-Gait; Figure 1A). This gait data was analysed for five age-groups: young children (3-6y), children (6-10y), pubertal children (10-14y), adolescents (14-19y) and adults (19-35y). Age-related changes in arm movements were compared using continuous joint angular waveforms, and as mean joint angle position and range of motion of shoulder, elbow and wrist in different anatomical planes. The overall shape of the arm movement patterns was comparable across all age groups (Figure 1B) with lower variability in the older age groups. At the shoulder, a larger mean extension angle was seen in the two youngest groups compared to the older children and adults. The range of shoulder axial rotation was significantly larger in adults compared to all other age groups. In the two youngest groups, a higher mean elbow flexion and wrist extension angle was found.

Natural arm swing patterns were present at the age of three but showed maturation (i.e. change to adult-like values) and/or fine-tuning (i.e. decrease of variability) in all joints and planes. Some remnants of the elevated arm position were observed until the age of ten years (e.g. increased shoulder abduction and decreased elbow flexion range of motion) where others already disappeared at the age of six years (e.g. increased mean shoulder extension and elbow flexion position). In conclusion, age-specific reference data should be used when clinically assessing arm swing during walking in pediatric pathologies.  

Figure 1: Marker setup and normative joint angle data.  A) Plugin gait total body marker placement. B) Group average of the joint angles over the gait cycle in sagittal (shoulder, elbow, wrist; + = flexion), transversal (shoulder; + = internal rotation) and coronal plane (shoulder and wrist; + = abduction). Black line (adults); blue line (adolescents); red line (pubertal children), green line (children); yellow line (young children). Significant differences between the joint angular profiles between age groups (SPM-d1; ANOVA) are presented by a grey rectangle: * p<0.05, ** p<0.01, *** p<0.001

Publication
Van de Walle, P., Meyns, P., Desloovere, K., De Rijck, J., Kenis, J., Verbecque, E., … & Hallemans, A. (2018). Age-related changes in arm motion during typical gait. Gait & posture, 66, 51-57. https://doi.org/10.1016/j.gaitpost.2018.07.176

This article resulted from combined expertise of motion analysts/researchers at the Clinical Motion Analysis Laboratory, Cerebral Palsy Reference centre UZ Leuven, and three Belgian Universities i.e. UAntwerp, UHasselt and KU Leuven.

About the Author

When you grow, it is clear that your abilities and movement coordination improve. Consequently, you are able to perform motor tasks that you could not do earlier. Ideally, this is because you acquire the ability to use more complex motor strategies as you mature. The question is, can we measure and analyse this movement complexity? And, if yes, do we expect to see an increase in motor complexity with age, independently from the motor task analysed?

To answer these questions, we studied motor complexity during walking in children, adolescents and young adults. We assessed movement complexity from trunk acceleration data using multiscale entropy. Multiscale entropy expresses the probability that two data traces remain close to each other over time. We examined motor complexity during two different locomotor tasks: i) natural gait, which is a paradigmatic task, expected to become more automatic with age maturation, and ii) tandem gait, which is a non-paradigmatic task that challenges motor control performance, constraining the base of support both in the medio-lateral and  antero-posterior directions. We expected motor complexity to decrease during normal walking and an increase during tandem gait with age. Our hypothesis was confirmed, and results showed a significant increase of motor complexity with age in tandem walking and a decrease on the sagittal plane in normal walking. Interestingly, the ratio of motor complexity (R-Sen in Figure below) measured during both tasks started around 100% at six years of age (similar level of complexity), and showed a progressive decrease to 50% in adulthood (with higher complexity in the tandem gait condition).

These results indicated that multiscale entropy is capable to detect changes in movement complexity with motor control maturation. This technique offers new opportunities for improving our understanding on motor control and its development. Our results further reveal a concurrent development of automaticity and complexity. With age maturation, motor complexity decreased during normal walking but increased during tandem walking. This may results from experience obtained during daily life, which leads adults to reach an optimized solution for normal walking, thereby manifesting a decreased movement complexity, while during a novel tandem walking task, they are able to employ more complex motor strategies to successfully perform the task. Finally, our results highlight directionality of changes with age in system complexity, which may depend on the direction of the adaptations or tolerance to stressors.

Figure. An overview of the two walking conditions (left) with normal walking (top) and tandem walking (bottom), and the effect of age on the ratio of complexity during these tasks (right) in antero-posterior and vertical directions.

Publication

M. C. Bisi & R. Stagni (2018): Changes of human movement complexity during maturation: quantitative assessment using multiscale entropy, Computer Methods in Biomechanics and Biomedical Engineering, DOI: 10.1080/10255842.2018.1448392

About the Author

Adequate balance control is a prerequisite for normal motor development. In children showing motor or developmental problems, identifying balance control problems is often the first step towards monitoring and rehabilitation. However, a universal definition of balance control is lacking in literature despite ample interest in the concept of balance over the past 30 years. Defining a complex and multifaceted skill like balance control is indeed not an easy task. In clinical practice, numerous tests are available to measure balance in children but not all are able to assess all aspects of this complex skill. The lack of a clear definition of balance control and the wealth of balance tests used in clinical practice highlight the need for an adequate assessment tool.

To provide an overview of balance measurement tools and functional balance tests used in children, we performed a literature search in PubMED and Web of Science. We described the psychometric properties of the available tests and, to highlight the different aspects of balance control, we defined a conceptual framework combining different views on balance control. This conceptual framework is not a definition of what balance control is, but rather provides a framework to classify available tests according to the ‘balance control components’ and ‘task constraints’ that the test assesses (see table 1).  A total of 14 functional balance tests were identified. By categorizing these tests in our conceptual framework, it became clear that no single balance measure could independently comprehend the total concept of balance control. Our results further suggest that static and dynamic balance control are part of the same construct, but the extent to which both aspects of balance control contribute to the performance on a given task appears to depend on the task constraints.

Our overview has clear clinical implications. In clinical practice, a combination of tests is recommended, paying attention to postural control in both static and dynamic situations and under different task constraints. Our literature search reveals that a test for children that is able to evaluate reactive mechanisms to balance perturbations is lacking. Furthermore, our literature study suggests that it is necessary to establish a criterion standard to measure balance in children. Such a criterion would allow to further investigate structural validity and responsiveness of the existing tests.

Publication

Psychometric properties of functional balance tests in children: a literature review. Verbecque E, Lobo Da Costa PH, Vereeck L, Hallemans A. Dev Med Child Neurol. 2015 Jun;57(6):521-9. doi: 10.1111/dmcn.12657

About the Author