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Human Motor Control. This research addresses the role of the peripheral neuromuscular system in the control of posture and movement. System identification methods are used to address three main questions: (1) What are the mechanical properties of human joints and how do they vary under normal physiological conditions? (2) What mechanisms are responsible for generating the mechanical behavior; what are the relative roles of intrinsic muscle properties and reflex mechanisms? (3) What role do these mechanical properties play in the control of posture and movement?

Biomedical System Identification and Signal Analysis. This research focuses on the development of tools and techniques for the analysis of biomedical signals and system and their application to clinically relevant problems. The emphasis is on practical methods for the identification of linear-time-varying and nonlinear systems within a continuous-time, nonparametric context. Current application areas are: (1) human motor control; (2) respiratory monitoring for apnea detection/prediction in the pediatric recovery room; and (3) automated decision support for electronic fetal monitoring.