Quantifying States and Transitions of Emerging Postural Control for Children Not Yet Able to Sit Independently.

Objective, quantitative postural data is limited for individuals who are non-ambulatory, especially for those who have not yet developed trunk control for sitting. There are no gold standard measurements to monitor the emergence of upright trunk control. Quantification of intermediate levels of postural control is critically needed to improve research and intervention for these individuals. Accelerometers and video were used to record postural alignment and stability for eight children with severe cerebral palsy aged 2 to 13 years, under two conditions, seated on a bench with only pelvic support and with additional thoracic support. This study developed an algorithm to classify vertical alignment and states of upright control; Stable, Wobble, Collapse, Rise and Fall from accelerometer data. Next, a Markov chain model was created to calculate a normative score for postural state and transition for each participant with each level of support. This tool allowed quantification of behaviors previously not captured in adult-based postural sway measures. Histogram and video recordings were used to confirm the output of the algorithm. Together, this tool revealed that providing external support allowed all participants: (1) to increase their time spent in the Stable state, and (2) to reduce the frequency of transitions between states. Furthermore, all participants except one showed improved state and transition scores when given external support.

Stance width changes how sensory feedback is used for multisegmental balance control.

A multilink sensorimotor integration model of frontal plane balance control was developed to determine how stance width influences the use of sensory feedback in healthy adults. Data used to estimate model parameters came from seven human participants who stood on a continuously rotating surface with three different stimulus amplitudes, with eyes open and closed, and at four different stance widths. Dependent variables included lower body (LB) and upper body (UB) sway quantified by frequency-response functions. Results showed that stance width had a major influence on how parameters varied across stimulus amplitude and between visual conditions. Active mechanisms dominated LB control. At narrower stances, with increasing stimulus amplitude, subjects used sensory reweighting to shift reliance from proprioceptive cues to vestibular and/or visual cues that oriented the LB more toward upright. When vision was available, subjects reduced reliance on proprioception and increased reliance on vision. At wider stances, LB control did not exhibit sensory reweighting. In the UB system, both active and passive mechanisms contributed and were dependent on stance width. UB control changed across stimulus amplitude most in wide stance (opposite of the pattern found in LB control). The strong influence of stance width on sensory integration and neural feedback control implies that rehabilitative therapies for balance disorders can target different aspects of balance control by using different stance widths. Rehabilitative strategies designed to assess or modify sensory reweighting will be most effective with the use of narrower stances, whereas wider stances present greater challenges to UB control.