10 North Greene Street Baltimore, MD 21201
(410) 605-7000 ext. 6142
University of Texas (Austin, TX) BSME 1974 Mechanical Engineering
Rensselaer Polytechnic Institute (Troy NY) MSME 1977 Mechanical Engineering
Massachusetts Institute of Technology (Cambridge, MA) MBA 1984 Business Administration
University of California (Berkeley, CA) PhD 2005 Mechanical Engineering
I am a Mechanical Engineer with special training in Automatic Control, Applied Mathematics, and Vision Science; and have successfully applied this expertise in a number of studies of sensorimotor control. For my doctoral thesis I developed a quantitative model of the human visual system’s performance detecting and tracking the looming cue (changes in the size of an approaching/receding object’s retinal image) in the collision detection and avoidance task. My successful application of engineering methods to the study of human vision led me to Northwestern University/Rehabilitation Institute of Chicago to study upper limb control as part of a DARPA-funded effort to develop next-generation upper limb prostheses. There I developed a shoulder-activated controller for a 2-degree of freedom powered shoulder joint, and a computer based implementation of Fitts Law (a widely accepted method for evaluating human reaching movements) to assess and compare the performance of several candidate controller designs. I next accepted a position at Temple University to study the control of human balance and posture. There I led the development and implementation of an NIH R01 funded study which investigated the manner in which consistent and inconsistent visual and physical motion inputs affect postural response in healthy elderly compared to age-matched stroke subjects. In another study I collaborated in the creation of a robotic arm to simulate and study the structure and implementation of internal models in the human nervous system. There I again employed Fitts Law, this time to validate its performance against that of human subjects. My current studies are focused on Internal Model (IM) theory, which posits the existence of highly adaptable neural structures within the central nervous system that control movement through kinematic and dynamic “models” of the body and its parts, and relevant objects and features of the external environment. IM’s provide an ideal framework within which findings and concepts from numerous fields can be combined to develop neuro-physiologically accurate computational models to assess and compare healthy and impaired movement, and provide insight into the neural and physiological bases for observed movement deficits. They form the theoretical basis for my VA Career Development Award (CDA), which synthesizes and extends my prior research to the more general problem of balance and movement. The goal of this five year study is to develop a quantitative diagnostic instrument based on the IM paradigm to assess the deficits associated with age-induced high fall risk (HFR) and stroke in the performance of a balanced reaching task in three-dimensional space. My Pepper Development Project extends these concepts further, where I study the two major types of balance disturbance—expected and unexpected balance disturbances, and assess the effects of different training regimens on the ability of elderly high fall risk individuals to respond to them. These findings will allow me to advance the “technology” of Internal Models by incorporating functional models of the actual neural structures involved, thus elaborating on existing IM control algorithms and making them more closely representative of the actual underlying processes.
Balance, Balance Disorders, Automatic Control, Internal Model, Biomechanics
J. E. Barton, and J. D. Sorkin, “Design and Evaluation of Prosthetic Shoulder Controller,” Journal of Rehabilitation Research and Development, vol. 51, no. 5, pp. 711-726, 2014.
J. E. Barton, A. Roy, J. D. Sorkin, M. W. Rogers, and R. Macko, “An Engineering Model of Human Balance Control Part 1: Biomechanical Model,” ASME Journal of Biomechanical Engineering, vol. 138, no. 1, pp. 014502 (1-11), 2015.
J. E. Barton, V. Graci, C. Hafer-Macko, J. D. Sorkin, and R. F. Macko, “Dynamic Balanced Reach: A Temporal and Spectral Analysis across Increasing Performance Demands,” ASME Journal of Biomechanical Engineering, vol. 138, no. 12, pp. 121009 (1-13), 2016.