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Dive into the research topics where Giancarlo Valentin is active.

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Featured researches published by Giancarlo Valentin.


international symposium on wearable computers | 2013

FIDO - facilitating interactions for dogs with occupations: wearable dog-activated interfaces

Melody Moore Jackson; Clint Zeagler; Giancarlo Valentin; Alex Martin; Vincent Martin; Adil Delawalla; Sarah Eiring; Ryan Hollis; Yash Kshirsagar; Thad Starner

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.


ubiquitous computing | 2015

FIDO--Facilitating interactions for dogs with occupations: wearable communication interfaces for working dogs

Melody Moore Jackson; Giancarlo Valentin; Larry Freil; Lily Burkeen; Clint Zeagler; Scott M. Gilliland; Barbara Currier; Thad Starner

Abstract 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.


issnip biosignals and biorobotics conference biosignals and robotics for better and safer living | 2013

Dealing with childhood obesity: Passive versus active activity monitoring approaches for engaging individuals in exercise

Giancarlo Valentin; Ayanna M. Howard

Childhood obesity is a growing health problem. Indicators show that the rate of obesity for children age 12-19 years old has risen from 5% percent to 18% over the last ten years. Strategies to solve this childhood obesity epidemic range from educating children about nutrition to enabling possibilities for physical exercise. These general approaches, although useful, are ineffective when not adapted into the day-to-day activities of childrens lives. However, given the growing popularity of mobile devices, an opportunity exists to use these technologies to design health-based applications that empower this target demographic. In the following paper, we compare two methods for engaging individuals in exercise based on passive versus active-encouragement. The passive method utilizes a wearable device that records exercise activities throughout the day whereas the active-encouragement approach utilizes a smartphone device to send encouraging reminders to the user during the day. The preliminary results, obtained with adolescents and young adults, show that for average users, active-encouragement using a smartphone can produce higher activity levels than the passive alternative. This provides the precursory evidence necessary for justifying further evaluations with younger children.


human computer interaction with mobile devices and services | 2015

Leveraging Mobile Technology to Increase the Permanent Adoption of Shelter Dogs

Joelle Alcaidinho; Giancarlo Valentin; Stephanie Tai; Brian Nguyen; Krista Sanders; Melody Moore Jackson; Eric Gilbert; Thad Starner

We present the results of an 8-week pilot study with 55 dogs investigating whether using quantimetric monitors and a companion smartphone application can reduce returns and increase the perceived strength of bonds between newly adopted dogs from the Humane Society of Silicon Valley and their adopters. Through this pilot study, we developed guidelines for future research and discovered promising results indicating that providing dog quantimetric data to adopters through the use of a smartphone application could yield reduced rates of re-relinquishment. Additionally, respondents indicated that they felt using the smartphone application helped them to better meet the activity needs of their dog and increased the bond between themselves and their newly adopted dog.


international symposium on wearable computers | 2016

Creating collar-sensed motion gestures for dog-human communication in service applications

Giancarlo Valentin; Joelle Alcaidinho; Ayanna M. Howard; Melody Moore Jackson; Thad Starner

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.


advances in computer entertainment technology | 2015

Towards a canine-human communication system based on head gestures

Giancarlo Valentin; Joelle Alcaidinho; Ayanna M. Howard; Melody Moore Jackson; Thad Starner

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 dogs 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 dogs 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.


international symposium on wearable computers | 2014

Gestural activity recognition for canine-human communication

Giancarlo Valentin

Despite close collaboration existing between humans and working dogs, there are few options for reliable two-way communication between them. The main goal of the FIDO project is to explore and develop wearable technologies to support this communication [5]. In this manuscript, we describe work in progress regarding the use of intentional, motion-based dog gestures as a mechanism of communication. In particular, we are interested in gestures that can be identified with the use of inertial measurement sensors such as accelerometers and gyroscopes.


Proceedings of the Third International Conference on Animal-Computer Interaction | 2016

Search and rescue: dog and handler collaboration through wearable and mobile interfaces

Clint Zeagler; Ceara Byrne; Giancarlo Valentin; Larry Freil; Eric Kidder; James Crouch; Thad Starner; Melody Moore Jackson

Search and Rescue (SAR) is a critical component of disaster recovery efforts. Every second saved in the search increases the chances of finding survivors and the majority of these teams prefer using canines [5]. Our goal is to help enable SAR dog and handler teams to work together more effectively. Using a semi-structured interviews and guidance from K9-SAR experts as we iterate through designs, we develop a two-part system consisting of a wearable computer interface for working SAR dogs that communicates with their handler via a mobile application. Additionally, we discuss the system around a heuristic framework that includes dogs as active participants. Finally, we show the viability of our tool by evaluating it with feedback from three SAR experts.


international symposium on wearable computers | 2014

Canine reachability of snout-based wearable inputs

Giancarlo Valentin; Joelle Alcaidinho; Larry Freil; Clint Zeagler; Melody Moore Jackson; Thad Starner

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.


international symposium on wearable computers | 2015

The challenges of wearable computing for working dogs

Giancarlo Valentin; Joelle Alcaidinho; Melody Moore Jackson

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.

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Melody Moore Jackson

Georgia Institute of Technology

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Joelle Alcaidinho

Georgia Institute of Technology

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Thad Starner

Georgia Institute of Technology

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Larry Freil

Georgia Institute of Technology

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Clint Zeagler

Georgia Institute of Technology

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Ayanna M. Howard

Georgia Institute of Technology

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Ceara Byrne

Georgia Institute of Technology

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Adil Delawalla

Georgia Institute of Technology

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Alex Martin

Georgia Institute of Technology

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Bradley Wittenbrook

Georgia Institute of Technology

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