The relationship between a child's postural stability and manual dexterity

The neural systems responsible for postural control are separate from the neural substrates that underpin control of the hand. Nonetheless, postural control and eye-hand coordination are linked functionally. For example, a stable platform is required for precise manual control tasks (e.g. handwriting) and thus such skills often cannot develop until the child is able to sit or stand upright. This raises the question of the strength of the empirical relationship between measures of postural stability and manual motor control. We recorded objective computerised measures of postural stability in stance and manual control in sitting in a sample of school children (n = 278) aged 3-11 years in order to explore the extent to which measures of manual skill could be predicted by measures of postural stability. A strong correlation was found across the whole sample between separate measures of postural stability and manual control taken on different days. Following correction for age, a significant but modest correlation was found. Regression analysis with age correction revealed that postural stability accounted for between 1 and 10 % of the variance in manual performance, dependent on the specific manual task. These data reflect an interdependent functional relationship between manual control and postural stability development. Nevertheless, the relatively small proportion of the explained variance is consistent with the anatomically distinct neural architecture that exists for 'gross' and 'fine' motor control. These data justify the approach of motor batteries that provide separate assessments of postural stability and manual dexterity and have implications for therapeutic intervention in developmental disorders.</p

The relationship between a child's postural stability and manual dexterity

The neural systems responsible for postural control are separate from the neural substrates that underpin control of the hand. Nonetheless, postural control and eye-hand coordination are linked functionally. For example, a stable platform is required for precise manual control tasks (e.g. handwriting) and thus such skills often cannot develop until the child is able to sit or stand upright. This raises the question of the strength of the empirical relationship between measures of postural stability and manual motor control. We recorded objective computerised measures of postural stability in stance and manual control in sitting in a sample of school children (n = 278) aged 3–11 years in order to explore the extent to which measures of manual skill could be predicted by measures of postural stability. A strong correlation was found across the whole sample between separate measures of postural stability and manual control taken on different days. Following correction for age, a significant but modest correlation was found. Regression analysis with age correction revealed that postural stability accounted for between 1 and 10 % of the variance in manual performance, dependent on the specific manual task. These data reflect an interdependent functional relationship between manual control and postural stability development. Nevertheless, the relatively small proportion of the explained variance is consistent with the anatomically distinct neural architecture that exists for ‘gross’ and ‘fine’ motor control. These data justify the approach of motor batteries that provide separate assessments of postural stability and manual dexterity and have implications for therapeutic intervention in developmental disorders

Grasping the changes seen in older adults when reaching for objects of varied texture.

Old age is associated with reduced mobility of the hand. To investigate age related decline when reaching-to-lift an object we used sophisticated kinematic apparatus to record reaches carried out by healthy older and younger participants. Three objects of different widths were placed at three different distances, with objects having either a high or low friction surface (i.e. rough or slippery). Older participants showed quantitative differences to their younger counterparts - movements were slower and peak speed did not scale with object distance. There were also qualitative differences with older adults showing a greater propensity to stop the hand and adjust finger position before lifting objects. The older participants particularly struggled to lift wide slippery objects, apparently due to an inability to manipulate their grasp to provide the level of precision necessary to functionally enclose the object. These data shed light on the nature of age related changes in reaching-to-grasp movements and establish a powerful technique for exploring how different product designs will impact on prehensile behavior

Training compliance control yields improvements in drawing as a function of beery scores

Many children have difficulty producing movements well enough to improve in sensori-motor learning. Previously, we developed a training method that supports active movement generation to allow improvement at a 3D tracing task requiring good compliance control. Here, we tested 7–8 year old children from several 2nd grade classrooms to determine whether 3D tracing performance could be predicted using the Beery VMI. We also examined whether 3D tracing training lead to improvements in drawing. Baseline testing included Beery, a drawing task on a tablet computer, and 3D tracing. We found that baseline performance in 3D tracing and drawing co-varied with the visual perception (VP) component of the Beery. Differences in 3D tracing between children scoring low versus high on the Beery VP replicated differences previously found between children with and without motor impairments, as did post-training performance that eliminated these differences. Drawing improved as a result of training in the 3D tracing task. The training method improved drawing and reduced differences predicted by Beery scores

The relationship between manual coordination and mental health

Motor coordination impairments frequently co-occur with other developmental disorders and mental health problems in clinically referred populations. But does this reflect a broader dimensional relationship within the general population? A clearer understanding of this relationship might inform improvements in mental health service provision. However, ascertainment and referral bias means that there is limited value in conducting further research with clinically referred samples. We, therefore, conducted a cross-sectional population-based study investigating children’s manual coordination using an objective computerised test. These measures were related to teacher-completed responses on a behavioural screening questionnaire [the Strength and Difficulties Questionnaire (SDQ)]. We sampled 298 children (4–11 years old; 136 males) recruited from the general population. Hierarchical (logistic and linear) regression modelling indicated significant categorical and continuous relationships between manual coordination and overall SDQ score (a dimensional measure of psychopathology). Even after controlling for gender and age, manual coordination explained 15 % of the variance in total SDQ score. This dropped to 9 % after exclusion of participants whose SDQ responses indicated potential mental health problems. These results: (1) indicate that there is a clear relationship between children’s motor and mental health development in community-based samples; (2) demonstrate the relationship’s dimensional nature; and (3) have implications for service provision

Mean and standard deviation for <i>reciprocal root mean square error</i> (<i>RMSE</i>) whilst Tracking without and with a guide-line, with effect size estimates for between-task differences.

1<p>Effect size for the mean difference between reciprocal RMSE With and Without a Guide-line.</p

Children's head movements and postural stability as a function of task.

Manual dexterity and postural control develop throughout childhood, leading to changes in the synergistic relationships between head, hand and posture. But the postural developments that support complex manual task performance (i.e. beyond pointing and grasping) have not been examined in depth. We report two experiments in which we recorded head and posture data whilst participants simultaneously performed a visuomotor task. In Experiment 1, we explored the extent to which postural stability is affected by concurrently performing a visual and manual task whilst standing (a visual vs. manual-tracking task) in four age groups: 5-6 years (n = 8), 8-9 years (n = 10), 10-11 years (n = 7) and 19-21 years (n = 9). For visual tracking, the children's but not adult's postural movement increased relative to baseline with a larger effect for faster moving targets. In manual tracking, we found greater postural movement in children compared to adults. These data suggest predictive postural compensation mechanisms develop during childhood to improve stability whilst performing visuomotor tasks. Experiment 2 examined the extent to which posture is influenced by manual activity in three age groups of children [5-6 years (n = 14), 7-8 years (n = 25), and 9-10 years (n = 24)] when they were seated, given that many important tasks (e.g. handwriting) are learned and performed whilst seated. We found that postural stability varied in a principled manner as a function of task demands. Children exhibited increased stability when tracing a complex shape (which required less predictive postural adjustment) and decreased stability in an aiming task (which required movements that were more likely to perturb posture). These experiments shed light on the task-dependant relationships that exist between postural control mechanisms and the development of specific types of manual control

Bar-chart of reciprocal penalised path accuracy (<i>pPA</i>) by Age-Group and Sex.

<p>Reciprocal <i>pPA</i> is a unitless measure of spatial accuracy whilst tracing, adjusted to standardise for individual variation in speed. Statistically significant differences between Age-Groups and Sex were found on this outcome (both p<.001), with no significant interaction between them. Performance improved with increasing age and was consistently better (higher) in Females. Note: Error bars represent 95% confidence intervals.</p

Illustrations of the three manual control battery tasks: (a) Tracking, (b) Aiming and (c) Tracing.

<p>(a) Left is a schematic of first Tracking trial (i.e. without ‘Guideline’), annotated with a dotted line to indicate the trajectory of the moving dot. Right is a schematic of the second Tracking trial, which included the additional Guideline. (b) Schematic of the Aiming subtest, annotated with dotted arrows implying the movements participants would make with their stylus to move off the start position, between target locations and to reach the finish position. On the 4^th panel further annotations indicate the locations in which targets sequentially appeared, with numbers indicating the sequence in which they were cued. (c) Left is a schematic depicting tracing path A and right is a schematic depicting tracing path B. The black shaky lines are an example of the ‘ink trails’ a participant would produce with their stylus in the course of tracing.</p

Line-graph of reciprocal movement time (<i>MT</i>) by Age-Group, Sex and Experimental Condition.

<p>Reciprocal <i>MT</i> (sec⁻¹) is a measure of average time to move from one target to the next in a serial aiming task. In normal Baseline and Embedded-Baseline trials Female participants had a statistically significant advantage over males in the younger age-groups, with this crossing over in the older age-groups (i.e. no sex differences or a male advantage dependent on age-group and Condition). Meanwhile, no significant differences between sexes were observed, irrespective of age, for ‘Jump’ aiming movements that required additional online corrections. This was reflected in statistical analysis finding a significant 3-way interactions between Age-Group, Sex and Condition (p<.05). Note: Point estimates and associated 95% confidence Intervals for each sex group within an age-group have been artificially moved on the horizontal axis so that they display side-by-side, preventing overlaps obscuring interpretation.</p