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.

No abstract

No abstract

We present two case studies on creating wearables for dogs and discuss them in terms of challenges of safety, space, weight and comfort, that motivated them. You can use these case studies and our design process as a practical primer for designing wearables for working dogs.

Working dogs are dogs with one or more specific skills that enable them to perform essential tasks for humans. In this paper we examined motion gestures that working dogs could use to unambiguously communicate with their human companions. We analyzed these gestures in terms of true positives and propensity for false positives by comparing their dynamic time warping distances against a set of everyday gesture libraries (EGL) representing their daily movements. We found four gestures that could be concretely defined, trained, and recognized. These gestures were recognized with 75-100% accuracy, and their false positive rate averaged to less than one per hour.