The potential of an automated system to identify the upper limb component of a controlled sitting posture.

Sánchez, MB, Loram, I, Darby, J, Holmes, P and Butler, PB (2017) The potential of an automated system to identify the upper limb component of a controlled sitting posture. Gait & posture, 58. pp. 223-228. ISSN 0966-6362

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Abstract

Full trunk control in sitting is demonstrated only when the head-trunk are aligned and upper limbs remain free of contact from mechanical support. These components represent a Controlled Kinetic Chain and can be evaluated in people with neuromotor disability using the Segmental Assessment of Trunk Control (SATCo) when a therapist provides manual trunk support at different segmental levels. However, the SATCo, as with other clinical assessments of control, is subjective. The SATCo was translated to objective rules relating the position of the hands and elbows to the head-trunk and then tested to determine the extent to which this automated objective method replicated the clinical judgement. Clinical evaluation used video to determine whether the upper limb was free of mechanical support while the objective evaluation used 3D motion capture of the trunk and upper limbs with a classification rule. The agreement between clinical and objective classification was calculated for three conditions of a distance-from-support-surface threshold parameter in five healthy adults and five children with cerebral palsy. The unfitted (zero-threshold values) method replicated the clinical judgement in part (68.26%±15.7, adults, 48.3%±33.9 children). The fitted (level-of-support determined) agreement showed that the process could be refined using trial specific parameters (88.32%±5.3 adults, 89.84%±10.2 children). The fixed-values agreement showed high values when using general group parameters (80.80%±3.1 adults, 74.31%±21.5 children). This objective classification of the upper limb component of trunk control largely captures the clinical evaluation. It provides the first stages in development of a clinically-friendly fully automated method.