Rajiv Ranganathan, Ph.D. - US grants

DESCRIPTION (provided by applicant): The current proposal aims to facilitate hand function in chronic stroke patients. Deficits in hand function are extremely common after stroke and persist for a prolonged period of time. While conventional techniques have emphasized the repetitive practice of simple movements, the role of coordination in rehabilitation has not been explored extensively. In this proposal, the PIs examine the influence of training novel finger coordination patterns as a means of improving hand function and dexterity. They propose an innovative protocol to induce the reorganization of finger movements. Instead of providing explicit instructions, the PIs will elicit different coordination patterns in the context of a simpe task. Participants wear a data glove and the signals from the glove are mapped on to the position of a computer cursor. The goal of the participants is to move their fingers so that they learn to move the computer cursor to different targets on a screen. This protocol has the advantage of reducing the complex task of finger coordination into the simpler task of planning cursor movements. The first aim investigates how changing the relation between finger and cursor motion (i.e., changing the map) affects the reorganization of finger coordination. Specifically, the PIs examine the effectiveness of changing two features of the map (gain and variability) in driving the participants to reorganize their finger movements. The second aim examines the feasibility of using this protocol to improve hand function and dexterity in chronic stroke patients. Patients undergo training in the glove task with different maps designed to elicit varied finger movements. Clinical tests are then used to determine if training resulted in improved hand function. The results of these experiments have the potential to transform rehabilitation approaches by introducing the exploration of novel coordination patterns as an important component of training protocols. PUBLIC HEALTH RELEVANCE: Deficits in hand motor function are extremely common after stroke. The current proposal aims to improve hand function in chronic stroke patients by facilitating the practice of novel finger coordination patterns.

Children with severe movement impairments often depend on assistive devices such as wheelchairs, robotic arms, or communication aids for activities of their daily lives. However, learning to control these complex devices can be challenging for children. In this project, the investigators explore the development of a general purpose body-machine interface that allows children to control several devices using movements of the body. A key advantage of this type of interface is that it is non-invasive, easy to wear, and can "grow" with the child. The project will enhance basic understanding of how body movements can be exploited to control external devices, especially in children. The project will have an impact on the independence and quality of life for children with severe movement impairments. A key challenge of this research is to translate the body movements of the user into commands that can control the robotic arm for performing an intended task. The traditional approach to this translation problem has been based on principal components analysis (PCA); however, this is not well suited for complex tasks requiring the control of many degrees of freedom. In this project, the investigators will develop alternative, novel methods that can take full advantage of the movement repertoire of the user and can also yield intuitive control. In addition to the significant impact of this research on the quality of life of individuals with disabilities, the project includes outreach to K12 students and teachers to interest them in STEM and improve their understanding of disabilities and motor development.

The current work will be carried out through three aims. These are: 1) utilize a principal component analysis-based approach for control of high degree of freedom movements within the robot; 2) develop a virtual body model approach; and 3) determine learning characteristics of high-degree of freedom body machine interfaces in children. Each aspect of the research will be assessed through rigorous performance metrics. Specifically, the objectives of this project are to: capture a wide range of motion patterns using sensors on the head and upper body; and to map anatomically distinct motion patterns to commands for controlling the robot arm using a virtual model of the user's body. Based on the sensor data from the user, algorithms will be used to calculate how the virtual model bends, twists, and turns; and these deformations will then be translated into commands that control the robotic arm. In addition to developing these methods, the investigators will also evaluate the intuitiveness of these new methods by testing how quickly children can learn to control a robotic arm using these methods.

Humans often have to engage in the process of changing and refining existing movement patterns, when engaging in normal behaviors as well as in rehabilitation. The goal of this project is to examine this process of "motor re-learning" in complex motor tasks. This project is significant because it will advance theoretical understanding of the principles that drive motor re-learning, and illuminate how these principles can be used to develop new methods of training in healthy individuals. The project includes study of re-learning in violinists, generating outreach and broadening participation in STEM research, and building knowledge of motor learning in musical performance. The project will involve an educational component that provides training to graduate and undergraduate students in conducting research. The knowledge to be gained may have important implications for enhancing movement rehabilitation in individuals with physical disabilities, thereby advancing fundamental science supporting the national health and welfare.

Learning one motor skill can exert a powerful influence on subsequent motor learning. These effects can either promote or hinder learning, and can persist for months or years. Motor learning is complex, as even behaviors that seem quite simple can depend on coordination of multiple joints and multiple muscles. This project will alter this dependence, using a human-computer interface. Humans will learn to move a cursor on a screen using gestures. The experiment will change the function mapping the gestures into cursor movement, across or within training sessions. The expected findings will advance theories of motor learning, which largely ignore the existence and influence of previously learned coordination patterns.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.