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Jackson, Melody Moore

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Author: Starner, Thad ×

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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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    FIDO—Facilitating interactions for dogs with occupations: wearable communication interfaces for working dogs
    (Georgia Institute of Technology, 2015-01) Jackson, Melody Moore ; Valentin, Giancarlo ; Freil, Larry ; Burkeen, Lily ; Zeagler, Clint ; Gilliland, Scott ; Currier, Barbara ; Starner, Thad
    Working dogs have improved the lives of thousands of people throughout history. However, communication between human and canine partners is currently limited. The main goal of the FIDO project is to research fundamental aspects of wearable technologies to support communication between working dogs and their handlers. In this study, the FIDO team investigated on-body interfaces for dogs in the form of wearable technology integrated into assistance dog vests. We created five different sensors that dogs could activate based on natural dog behaviors such as biting, tugging, and nose touches. We then tested the sensors on-body with eight dogs previously trained for a variety of occupations and compared their effectiveness in several dimensions. We were able to demonstrate that it is possible to create wearable sensors that dogs can reliably activate on command, and to determine cognitive and physical factors that affect dogs’ success with body–worn interaction technology.
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    Canine Reachability of Snout-based Wearable Inputs
    (Georgia Institute of Technology, 2014-09) Valentin, Giancarlo ; Alcaidinho, Joelle ; Friel, Larry ; Zeagler, Clint ; Jackson, Melody Moore ; Starner, Thad
    We designed an experiment with the goal of assessing wearable reachability for canines. We investigated the effect of placement on the ability of dogs to reach on-body interfaces with their snouts. In our pilot study, seven placements along the front legs, rib cage, hip and chest are tested with six dogs. The results showed that the front leg placements are reachable with the least amount of training and are also the most invariant to small changes in location. With training, the lower half of the rib cage area had the fastest access times across subjects. We hope that these results may be useful in mapping the constraint space of placements for snout interactions.
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    Facilitating Interactions for Dogs with Occupations: Wearable Dog - Activated Interfaces
    (Georgia Institute of Technology, 2013-09) Jackson, Melody Moore ; Zeagler, Clint ; Valentin, Giancarlo ; Martin, Alex ; Martin, Vincent ; Delawalla, Adil ; Blount, Wendy ; Eiring, Sarah ; Hollis, Ryan ; Kshirsagar, Yash ; Starner, Thad
    Working dogs have improved the lives of thousands of people. However, communication between human and canine partners is currently limited. The main goal of the FIDO project is to research fundamental aspects of wearable technologies to support communication between working dogs and their handlers. In this pilot study, the FIDO team investigated on-body interfaces for assistance dogs in the form of wearable technology integrated into assistance dog vests. We created four different sensors that dogs could activate (based on biting, tugging, and nose gestures) and tested them on-body with three assistance-trained dogs. We were able to demonstrate that it is possible to create wearable sensors that dogs can reliably activate on command.
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    Recognizing Sign Language from Brain Imaging
    (Georgia Institute of Technology, 2009) Mehta, Nishant A. ; Starner, Thad ; Jackson, Melody Moore ; Babalola, Karolyn O. ; James, George Andrew
    The problem of classifying complex motor activities from brain imaging is relatively new territory within the fields of neuroscience and brain-computer interfaces. We report positive sign language classification results using a tournament of pairwise support vector machine classifiers for a set of 6 executed signs and also for a set of 6 imagined signs. For a set of 3 contrasted pairs of signs, executed sign and imagined sign classification accuracies were highly significant at 96.7% and 73.3% respectively. Multiclass classification results also were highly significant at 66.7% for executed sign and 50% for imagined sign. These results lay the groundwork for a brain-computer interface based on imagined sign language, with the potential to enable communication in the nearly 200,000 individuals that develop progressive muscular diseases each year.