Organizational Unit:

Institute for Robotics and Intelligent Machines (IRIM)

Permanent Link

https://hdl.handle.net/1853/70657

Includes Organization(s)

Organizational Unit

Biorobotics and Human Modeling Lab

Organizational Unit

Humanoid Robotics Laboratory

Full item page

Publication Search Results

Now showing 1 - 10 of 153

Pilot Study For Examining Human-Robot Trust In Healthcare Interventions Involving Sensitive Personal Information

(Georgia Institute of Technology, 2017-07) Xu, Jin ; Howard, Ayanna M.

Socially interactive humanoid robots have been widely used in physical therapy and rehabilitation for children with motor disabilities. Previous studies have shown that embedding human-like behavior on a robotic playmate improves the efficacy of the physical therapy through corrective feedback. Understanding of trust in such scenarios is especially important since the behavior of the robot impacts the outcomes of the interaction through changes of trust, thus affecting rehabilitation performance. The objective of this pilot study was to examine aspects of trust between humans and socially interactive humanoid robots when robots provide incorrect personal information about them. A between-subject experiment was conducted with eight participants. Each participant was randomly assigned to one of the following conditions: 1) Reliable robot or 2) Faulty robot. Survey responses about trust were collected after interacting with the robot. Results indicate a trend showing that humans will trust a socially interactive robot with their personal information, even if the robot makes a mistake. These results can provide insights into the development of a robotic therapy coach but also motivates future studies to examine elements of human-robot trust in different healthcare scenarios.
Validation of Accuracy of the Super Pop VR™ Kinematic Assessment Methodology Using Markerless Versus Marker-Based Motion Capture Systems

(Georgia Institute of Technology, 2016) García-Vergara, Sergio ; Robinette, Paul ; Chen, Yu-Ping ; Howard, Ayanna M.

Therapists and clinicians have been combining virtual reality (VR) systems for rehabilitation purposes with motion capture systems to accurately keep track of the users' movements and better analyze their kinematic performance. The current state-of-the-art motion capture technology is limited to the clinical setting due to its cost, the necessity for a controlled environment, requirement of additional equipment, among others. Given the benefits of home-based rehabilitation protocols, more portable and cost-effective technology is being coupled with the VR systems. In this work, we focus on validating the accuracy of the Kinect™ camera from Microsoft. We compare its performance to a current state-of-the-art motion capture system. Namely, we 1) analyze the difference between the outcome metrics computed with data collected with the Kinect™ camera and the outcome metrics computed with data collected with the motion capture system, and 2) compare the spatial trajectories generated by both systems for the hand, elbow, and shoulder joints. Data were collected from ten able-bodied adults to quantify these comparisons. In general, results from both analyzes support the validity and feasibility of using the Kinect™ camera for home-based rehabilitation purposes.
Increasing Super Pop VR™ Users' Intrinsic Motivation by Improving the Game's Aesthetics

(Georgia Institute of Technology, 2015-08) García-Vergara, Sergio ; Li, Hongfei ; Howard, Ayanna M.

During physical therapy intervention protocols, it's important to consider the individual's intrinsic motivation to perform in-home recommended exercises. Physical therapy exercises can become tedious thus limiting the individual's progress. Not only have researchers developed serious gaming systems to increase user motivation, but they have also worked on the design aesthetics since results have shown positive effects on the users' performance for attractive models. As such, we improved the aesthetics of a previously developed serious game called Super Pop VR™. Namely, we improved the game graphics, added new game features, and allowed for more game options to provide users the opportunity to tailor their own experience. The conducted user studies show that participants rank the version of the game with the improved aesthetics higher in terms of the amount of interest/enjoyment it generates, thus allowing for an increase in intrinsic motivation when interacting with the system.
Retrieving Experience: Interactive Instance-based Learning Methods for Building Robot Companions

(Georgia Institute of Technology, 2015-05) Park, Hae Won ; Howard, Ayanna M.

A robot companion should adapt to its user’s needs by learning to perform new tasks. In this paper, we present a robot playmate that learns and adapts to tasks chosen by the child on a touchscreen tablet. We aim to solve the task learning problem using an experience-based learning framework that stores human demonstrations as task instances. These instances are retrieved when confronted with a similar task in which the system generates predictions of task behaviors based on prior actions. In order to automate the processes of instance encoding, acquisition, and retrieval, we have developed a framework that gathers task knowledge through interaction with human teachers. This approach, further referred to as interactive instance-based learning (IIBL), utilizes limited information available to the robot to generate similarity metrics for retrieving instances. In this paper, we focus on introducing and evaluating a new hybrid IIBL framework using sensitivity analysis with artificial neural networks and discuss its advantage over methods using k-NNs and linear regression in retrieving instances.
An Adaptive Robotic Tablet Gaming System for Post-Stroke Hand Function Rehabilitation

(Georgia Institute of Technology, 2015-03) English, Brittney A. ; Howard, Ayanna M.

Physical therapy is a common treatment for the rehabilitation of hemiparesis, or the weakness of one side of the body. Stroke is a common cause of hemiparesis. Stroke survivors regularly struggle with motivation and engagement, especially in-between sessions when the therapist is absent from the exercising process. As a solution, we have developed a robotic tablet gaming system to facilitate post-stroke hand function rehabilitation. Healthy subject pilot studies have been completed to verify that this system increases engagement and is capable of encouraging specific therapeutic motions. In the future, a learning model algorithm will be added to the system to assess the patient’s progress and optimize the recovery time.
Increasing Motor Learning During Hand Rehabilitation Exercises Through the Use of Adaptive Games: A Pilot Study

(Georgia Institute of Technology, 2015-03) English, Brittney A. ; Howard, Ayanna M.

Physical therapy is a common treatment for the rehabilitation of hemiparesis, or the weakness of one side of the body [1]. Unfortunately, a recent study found that about one third of stroke patients who are prescribed rehabilitation in hospital settings are ranked as poor participators in physical therapy [2]. In an attempt to increase morale and participation of stroke survivors in hand function motor therapy, a robotic rehabilitation system is being designed to counteract these hindrances to hand function recovery. For this system, an adaptive game that is only controllable through hand movement has been designed to optimize the challenges and rewards presented to the user. A healthy subjects pilot study was conducted to assess the adaptive game’s ability to increase the motor learning of participants during rehabilitation exercises. During this experiment, participants were asked to wear a robotic wrist sensor that functions as a game controller and play a rehabilitative tablet game that encourages therapeutic motions. To play this game users had to reach various targets in the game scenario by moving their hand in pre-determined ranges of motion. Two game scenarios presented the participant with a constant level of challenge, one of which was an easy scenario and the other a hard scenario, while a third scenario adjusted the game difficulty in order to maintain a constant balance of challenge and reward. When participants were presented with a constant level of challenge, their performance did not increase or decrease linearly during the session. This lack of linear growth or decay suggests that the participants did not experience significant learning and their performances were not hindered by negative emotions such as frustration or boredom. Participants that played the adaptive scenario performed similarly to the fixed difficulty levels when presented with an easy scenario for the beginning portion of the gaming experience and a difficult portion at the end. However, if participants were presented with a difficult scenario at the beginning of their gaming experience and an easy scenario at the end, they performed similarly to the fixed difficulty during the hard portion yet much better than the fixed difficulty during the easy portion. The averages for the easy portion of the adaptive level and the fixed easy level were 90.33% and 82.72%, respectively, and the standard deviations were 10.25% and 17.82%, respectively.
The Effect of Robot Performance on Human-‐Robot Trust in Time-‐Critical Situations

( 2015-01) Robinette, Paul ; Wagner, Alan R. ; Howard, Ayanna M.

We vary the ability of robots to mitigate a participant’s risk in a navigation guidance task to determine the effect this has on the participant’s trust in the robot in a second round. A significant loss of trust was found after a single robot failure.
Encouraging Specific Intervention Motions via a Robotic System for Rehabilitation of Hand Function: A Healthy Pilot Study

(Georgia Institute of Technology, 2014-12) English, Brittney A. ; Howard, Ayanna M.

A knowledge gap exists for how to improve hand rehabilitation after stroke using robotic rehabilitation methods, and non-robotic hand rehabilitation methods show only small patient improvements. A proposed solution for this knowledge gap is to integrate the strengths of three of the most favorable rehabilitation strategies for post-stroke rehabilitation of hand function, which are constraint-induced movement therapy (CIMT), high-intensity therapy, and repetitive task training, with a robotic rehabilitation gaming system. To create a system that is composed of collaborative therapy efforts, we must first understand how to encourage rehabilitation intervention motions. An experiment was conducted in which healthy participants were asked to complete six levels of a rehabilitation game, each level designed to encourage a specific therapeutic intervention, and a control, where participants were asked to complete undefined exercise motions. The results showed that participants’ motions were significantly different than the control while playing each of the levels. Upon comparing the actual paths of participants to the paths encouraged by the levels, it was discovered that the participants followed the intended path while encouragement was being provided for them to do so. When the encouraged motions required quick, hard motions, the participants would follow an aliased version of the intended path. This study suggests that robotic rehabilitation systems can not only change how a participant moves, but also encourage specific motions designed to mimic therapeutic interventions.
Robot Learners: Interactive Instance-based Learning and Its Application to Therapeutic Tasks

(Georgia Institute of Technology, 2014-11) Park, Hae Won ; Howard, Ayanna M.

Programming a robot to perform tasks requires training that is beyond the skill level of most individuals. To address this issue, we focus on developing a method that identifies keywords used to convey task knowledge among people and a framework that uses these keywords as conditions for knowledge acquisition by the robot learner. The methodology includes generalizing task modeling and providing a robot learner the ability to learn and improve its skills through accumulated experience gained from interaction with humans. More specifically, the aim of this research addresses the issues of knowledge encoding, acquisition, and retrieval through interactive instance-based learning (IIBL). In interaction studies, the benefit of using such a robot learner is in promoting social behaviors that results from the participant taking on an active role as teacher. Our recent experiment with 33 participants, including 19 typically developing children, and a pilot study with two children with autism spectrum disorder showed that IIBL provides a framework for designing an effective robot learner, and that the robot learner successfully increases the amount of social interactions initiated by the participants.
Robotic Resource Allocation for the Observation of Ablating Target Sources

(Georgia Institute of Technology, 2014-10) Coogle, Richard A. ; Howard, Ayanna M.

Icebergs generated from ice ablation processes continue to be a threat for operations conducted in polar regions. Systems that have been developed to track and observe these threats often use either space-based radar imaging or visual observation by the crew of the ship. Both of these methods have disadvantages, mostly in terms of real-time observation or the physical abilities of the crew. We propose a robotic solution for in-situ observation of icebergs, so that countermeasures may be quickly implemented. Our focus in this work is the problem of allocating resources to observation regions: once areas of iceberg activity have been identified, how are robot observers assigned to these regions and what cost metric may be used to determine the best placement of robot observers. Our solution is currently demonstrated and evaluated in simulation.