Quantitative approaches to directly measure infant movement have not utilized miniature electronics technology, nor been used effectively in evaluating neurological dysfunctions' affect on movement. This thesis presents a new quantitative technique for measuring infant general movements (GMs) using micro-electromechanical accelerometers, while discussing future improvements for this technology and possible benefits to present methods of diagnosing cerebral palsy.

For decades, GMs have interested neurologists because characteristics can indicate neurological dysfunctions. Motions over the entire body that show fluency, variation, and complexity characterize normal GMs. Analyzing these movements can accurately predict neurological dysfunction - cerebral palsy, in particular.

This research describes a technique to make consistent, quantitative measurements of GMs using accelerometers on infant limbs. Signal processing techniques can find patterns, later determined characteristic of neurological dysfunctions. Such analyses complement the current technique of video footage review. Additionally, data could be reanalyzed using updated signal processing algorithms. An accurate collection of data allows physicians to quickly review an infant's entire history of motion studies.

Physical information can be inferred from the data. Correlation techniques have compared motions from different limbs to examine coordination. Evidence suggests this may help indicate dysfunction. High-speed data acquisition enables the study of high-frequency motions, possibly undetectable with the human eye.

This research has successfully recorded acceleration and video during GMs from four limbs on multiple infants. Signal processing techniques have been applied to create various graphical representations. The direct measurement of movement makes this work unique, enabling a graphical analysis tool for physicians based on physical performance.