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Targeted Movement Pattern Recognition for Infants with Perinatal Brachial Plexus Injury

  • Author(s): AbuZeid, Yasmeen
  • Advisor(s): Reinkensmeyer, David J
  • et al.
Abstract

This thesis presents work toward a novel rehabilitation tool for infants with limited arm movement such as those who sustain a perinatal brachial plexus injury (PBPI). PBPI is a traction injury to peripheral nerves that occurs during the birth process. An injury to the upper trunk of the plexus (C5-6 spinal nerves) partially or fully denervates the skin of the upper arm and muscles of the elbow (i.e., biceps, brachialis) and shoulder (i.e., Deltoid, Sternal Pectoralis Major, Rotator Cuff). Initially, PBPI is typically treated with Passive Range of Motion (PROM) and positioning led by a physical therapist or occupational therapist. If recovery is limited, nerve microsurgery is indicated by 6 months of age. Recovery in infants with PBPI varies from 38 to 80% of infants depending on the initial condition and severity, as well as the rate of reinnervation. Yet, through technology, there may be methods available to increase the rate of recovery, leading to greater use of the affected arm. Infants as young as 3 months of age have been found to increase arm and leg movements through a paradigm of contingent reinforcement (i.e. rewarding desired movement patterns with audiovisual stimulation such as an overhead mobile). Before a device can be fully constructed to provide contingent reinforcement for desired arm movements, those movements must be consistently detectable. Thus, for this thesis project, I studied automatic detection of the arm movements desired for young infants with PBPI using arm acceleration data.

Acceleration data was acquired from a wrist-worn sensor as an adult volunteer moved her arm in the desired motion. I implemented a template-matching algorithm based on taking the dot-product of a moving window of 3D acceleration vectors with template acceleration patterns, where the templates were movement samples deemed targeted and rehabilitative by an experienced physical therapist. I found that the algorithm detected rehabilitative movements with an accuracy of ~90%. The algorithm never identified a movement that was deemed as undesirable for this population of infants, by the physical therapist. These results reveal the potential for the template matching algorithm to be used in a contingent reinforcement paradigm capable of activating a toy to encourage infants with PBPI to make targeted rehabilitative arm movements.

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