Person:
Howard, Ayanna M.

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Publication Search Results

Now showing 1 - 10 of 167
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    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.
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    State of the Science in Technologies to Support Successful Aging with Disability: Personal Technologies Track Panel
    (Georgia Institute of Technology, 2017-03-28) Howard, Ayanna M. ; Kesavadas, Thenkurussi ; Mynatt, Elizabeth D.
    Panel discussion on personal technologies for older adults and people with disabilities.
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    Musical Robots For Children With ASD Using A Client-Server Architecture
    (Georgia Institute of Technology, 2016-07) Zhang, Ruimin ; Barnes, Jaclyn ; Ryan, Joseph ; Jeon, Myounghoon ; Park, Chung Hyuk ; Howard, Ayanna M.
    People with Autistic Spectrum Disorders (ASD) are known to have difficulty recognizing and expressing emotions, which affects their social integration. Leveraging the recent advances in interactive robot and music therapy approaches, and integrating both, we have designed musical robots that can facilitate social and emotional interactions of children with ASD. Robots communicate with children with ASD while detecting their emotional states and physical activities and then, make real-time sonification based on the interaction data. Given that we envision the use of multiple robots with children, we have adopted a client-server architecture. Each robot and sensing device plays a role as a terminal, while the sonification server processes all the data and generates harmonized sonification. After describing our goals for the use of sonification, we detail the system architecture and on-going research scenarios. We believe that the present paper offers a new perspective on the sonification application for assistive technologies.
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    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.
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    Towards a Canine-Human Communication System Based on Head Gestures
    (Georgia Institute of Technology, 2015-11) Valentin, Giancarlo ; Alcaidinho, Joelle ; Howard, Ayanna M. ; Jackson, Melody Moore ; Starner, Thad
    We explored symbolic canine-human communication for working dogs through the use of canine head gestures. We identified a set of seven criteria for selecting head gestures and identified the first four deserving further experimentation. We devised computationally inexpensive mechanisms to prototype the live system from a motion sensor on the dog’s collar. Each detected gesture is paired with a predetermined message that is voiced to the humans by a smart phone. We examined the system and proposed gestures in two experiments, one indoors and one outdoors. Experiment A examined both gesture detection accuracy and a dog’s ability to perform the gestures using a predetermined routine of cues. Experiment B examined the accuracy of this system on two outdoor working-dog scenarios. The detection mechanism we presented is sufficient to point to improvements into system design and provide valuable insights into which gestures fulfill the seven minimum criteria.
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    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.
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    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.
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    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.
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    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.
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    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.