The data processing to detect correlated movement of Cerebral Palsy patient in early phase

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Virginia Tech


The early diagnosis of CP (Cerebral Palsy) in infants is important for developing meaningful interventions. One of the major symptoms of the CP is lack of the coordinated movements of a baby. The bilateral coordinated movement (BCM) is that a baby shows in the early development stage. Each limb movement shows various ranges of speed and angle with fluency in a normal infant. When a baby has CP the movements are cramped and more synchronized.

A quantitative method is needed to diagnose the BCM. Data is collected from 3-axis accelerometers, which are connected, to each limb of the baby. Signal processing the collected data using short time Fourier transforms, along with the formation of time-dependent transfer functions and the coherence property is the key to the diagnostic approach. Combinations of each limb's movement and their relationship can represent the correlated movement. Data collected from a normal baby is used to develop the technique for identifying the fidgety movement. Time histories and the resulting diagnostic tool are presented to show the regions of the described movement. The evaluation of the transduction approach and the analysis is discussed in detail.

The application of the quantitative tool for the early diagnosis of CP offers clinicians the opportunity to provide interventions that may reduce the debilitating impact this condition has on children. Tools such as this can also be used to assess motor development in infants and lead to the identification and early intervention for other conditions.



Accelerometer, fidgety movement, bilateral coordinated movement, cerebral palsy diagnostic symptoms, coherence, short time Fourier transform, weighted average of window function