The goal of these studies is to understand how healthy subjects control contact forces between the hand and the environment. While many studies have focused on the analysis of motion, little is known about the ability to control contact forces when performing simple tasks, such as writing on a whiteboard or operating a screwdriver. The proposed studies will take advantage of an experimental and theoretical approach to motor control developed by the PI in previous cycles. The approach is based on describing the action of the arm control system as a field of forces generated by the neuromuscular system at the interface between the hand and the environment. This approach has been successful in describing multi-joint arm posture, movement and adaptation to changes in the external environment (force perturbations). The studies of this proposal are dual (in part) to this past work, as we will study multi-joint force control and adaptation to changes in the external environment (motion perturbations). The studies are organized into three specific aims:
(AIM 1) To describe and quantify the mechanics of force control. This study will test, on a population of healthy subjects, (a) the directional accuracy and repeatability of force generation;(b) subjects'achievable dynamic range of impedance in stochastic environments, from low levels during force control to high levels during posture control;and (c) the hypothesis that impedance during force and posture control tasks revert to similar levels when the environment is well characterized.
(AIM 2) To establish the adaptive properties of force control. As one learns to manipulate in a new environment, one forms representations of the environmental mechanics and geometry. These representations are the basis for the recovery of performance without the need for relearning motor skills. Adaptive mechanisms will be investigated for the recovery of force control after a change in the mechanical properties of the contacted environment.
(AIM 3) To assess and enhance the combination of force and motion control in manipulation tasks. Purposeful motor behavior requires the satisfaction of force and motion goals that are often present concurrently. Accordingly, the final goal of this study is to understand whether and how the training of force control may lead to improved performance in tasks that combine motion and force requirements, such as assembly. This study will take advantage of haptic and augmented reality technologies that are available in the PI's laboratory. This proposal is directed at understanding the intact mechanisms of force control. We expect that the observations from this study will lead to a comparative description of force control and manipulation deficits after stroke and other disorders, as well as to novel methods for the restoration of these functions.
This proposal is directed at understanding the intact mechanisms of force control. We expect that the observations from this study will provide a solid basis that will lead rapidly to a comparative description of force control and manipulation deficits after stroke and other disorders, as well as to novel methods for the restoration of these functions.
|Farshchiansadegh, Ali; Melendez-Calderon, Alejandro; Ranganathan, Rajiv et al. (2016) Sensory Agreement Guides Kinetic Energy Optimization of Arm Movements during Object Manipulation. PLoS Comput Biol 12:e1004861|
|Casadio, Maura; Pressman, Assaf; Mussa-Ivaldi, Ferdinando A (2015) Learning to push and learning to move: the adaptive control of contact forces. Front Comput Neurosci 9:118|
|Saha, Devjani J; Hu, Xiao; Perreault, Eric et al. (2015) The coordinate system for force control. Exp Brain Res 233:899-908|
|Berniker, Max; Franklin, David W; Flanagan, J Randall et al. (2014) Motor learning of novel dynamics is not represented in a single global coordinate system: evaluation of mixed coordinate representations and local learning. J Neurophysiol 111:1165-82|
|Patton, James L; Wei, Yejun John; Bajaj, Preeti et al. (2013) Visuomotor learning enhanced by augmenting instantaneous trajectory error feedback during reaching. PLoS One 8:e46466|
|Piovesan, D; Melendez-Calderon, A; Mussa-Ivaldi, F A (2013) Haptic recognition of dystonia and spasticity in simulated multi-joint hypertonia. IEEE Int Conf Rehabil Robot 2013:6650449|
|Melendez-Calderon, A; Piovesan, D; Mussa-Ivaldi, F A (2013) Therapist recognition of impaired muscle groups in simulated multi-joint hypertonia. IEEE Int Conf Rehabil Robot 2013:6650425|
|Piovesan, D; Melendez-Calderon, A; Mussa-Ivaldi, F A (2013) Haptic perception of multi-joint hypertonia during simulated patient-therapist physical tele-interaction. Conf Proc IEEE Eng Med Biol Soc 2013:4143-7|
|Piovesan, Davide; Morasso, Pietro; Giannoni, Psiche et al. (2013) Arm stiffness during assisted movement after stroke: the influence of visual feedback and training. IEEE Trans Neural Syst Rehabil Eng 21:454-65|
|Piovesan, Davide; Casadio, Maura; Mussa-Ivaldi, Ferdinando A et al. (2012) Comparing Two Computational Mechanisms for Explaining Functional Recovery in Robot-Therapy of Stroke Survivors. Proc IEEE RAS EMBS Int Conf Biomed Robot Biomechatron 2012:1488-1493|
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