@article{martin_holder_nichols_park_roberts_bozkurt_2022, title={Comparing Accelerometry and Depth Sensing-Based Computer Vision for Canine Tail Wagging Interpretation}, DOI={10.1145/3565995.3566025}, abstractNote={This paper presents a preliminary effort to evaluate alternative sensing modalities for automated, high-resolution tracking of dog tail position and movement as a behavioral communication tool. We compare two different methods: (1) inertial measurement devices placed on dog outfits, and (2) remotely positioned cameras supported with custom vision-based tail wag detection algorithms. The small size and non-invasiveness of the inertial sensors and the non-contact and remote nature of the camera system both promote subject comfort and continuous signal acquisition while not affecting the mechanics of dog tail movement. The preliminary findings support that the higher-resolution and continuous interpretations on the dog tail movements and positions can pave the way for assessing their emotional states and designing more appropriate training and play environments.}, journal={NINTH INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2022}, author={Martin, Devon and Holder, Timothy and Nichols, Colt and Park, Jeremy and Roberts, David and Bozkurt, Alper}, year={2022} }
 @article{holder_rahman_summers_roberts_wong_bozkurt_2022, title={Contact-Free Simultaneous Sensing of Human Heart Rate and Canine Breathing Rate for Animal Assisted Interactions}, DOI={10.1145/3565995.3566039}, abstractNote={Animal Assisted Interventions (AAIs) involve pleasant interactions between humans and animals and can potentially benefit both types of participants. Research in this field may help to uncover universal insights about cross-species bonding, dynamic affect detection, and the influence of environmental factors on dyadic interactions. However, experiments evaluating these outcomes are limited to methodologies that are qualitative, subjective, and cumbersome due to the ergonomic challenges related to attaching sensors to the body. Current approaches in AAIs also face challenges when translating beyond controlled clinical environments or research contexts. These also often neglect the measurements from the animal throughout the interaction. Here, we present our preliminary effort toward a contact-free approach to facilitate AAI assessment via the physiological sensing of humans and canines using consumer-grade cameras. This initial effort focuses on verifying the technological feasibility of remotely sensing the heart rate signal of the human subject and the breathing rate signal of the dog subject while they are interacting. Small amounts of motion such as patting and involuntary body shaking or movement can be tolerated with our custom designed vision-based algorithms. The experimental results show that the physiological measurements obtained by our algorithms were consistent with those provided by the standard reference devices. With further validation and expansion to other physiological parameters, the presented approach offers great promise for many scenarios from the AAI research space to veterinary, surgical, and clinical applications.}, journal={NINTH INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2022}, author={Holder, Timothy and Rahman, Mushfiqur and Summers, Emily and Roberts, David and Wong, Chau-Wai and Bozkurt, Alper}, year={2022} }
 @article{wu_holder_foster_williams_enomoto_lascelles_bozkurt_roberts_2022, title={Spatial and Temporal Analytic Pipeline for Evaluation of Potential Guide Dogs Using Location and Behavior Data}, url={https://doi.org/10.1145/3565995.3566033}, DOI={10.1145/3565995.3566033}, abstractNote={Training guide dogs for visually-impaired people is a resource-consuming task for guide dog schools. This task is further complicated by a dearth of capabilities to objectively measure and analyze candidate guide dogs’ temperaments as they are placed with volunteer raisers away from guide dog schools for months during the raising process. In this work, we demonstrate a preliminary data analysis workflow that is able to provide detailed information about candidate guide dogs’ day to day physical exercise levels and gait activities using objective environmental and behavioral data collected from a wearable collar-based Internet of Things device. We trained and tested machine learning models to analyze different gait types including walking, pacing, trotting and mixture of walk and trot. By analyzing data both spatially and temporally, a location and behavior summary for candidate dogs is generated to provide insight for guide dog training experts, so that they can more accurately and comprehensively evaluate the future success of the candidate. The preliminary analysis revealed movement patterns for different location types which reflected the behaviors of candidate guide dogs.}, journal={NINTH INTERNATIONAL CONFERENCE ON ANIMAL-COMPUTER INTERACTION, ACI 2022}, author={Wu, Yifan and Holder, Timothy and Foster, Marc and Williams, Evan and Enomoto, Masataka and Lascelles, B. Duncan X. and Bozkurt, Alper and Roberts, David L.}, year={2022} }
 @article{ahmmed_holder_foster_castro_patel_torfs_bozkurt_2021, title={Noncontact Electrophysiology Monitoring Systems for Assessment of Canine-Human Interactions}, ISSN={["1930-0395"]}, url={http://dx.doi.org/10.1109/sensors47087.2021.9639748}, DOI={10.1109/SENSORS47087.2021.9639748}, abstractNote={Canine-assisted interactions have enormous potential in coping with psychological disorders and stress. It has been actively used for improving the mood of hospitalized patients, especially those suffering from chronic diseases like cancer. However, little progress has been made to enable the assessment of these interactions between the patient and the animal in a quantitative and undisruptive way. In this paper, we present a capacitively coupled biopotential recording system custom-designed for animal-human dyads. This system uses noncontact electrodes to monitor the heart rate and its variability to evaluate the physiological basis of the animal-assisted therapies. Preliminary in vivo evaluation of the system in humans and canines demonstrates promising measurement accuracy. The mean absolute error of the estimated heart rate was less than 0.25 BPM in reference to a commercial electrocardiography device. The future integration of this system into ergonomic form factors could enable a better understanding of animal-human interactions during canine-assisted therapy sessions by realizing an unobtrusive and continuous monitoring platform.}, journal={2021 IEEE SENSORS}, publisher={IEEE}, author={Ahmmed, Parvez and Holder, Timothy and Foster, Marc and Castro, Ivan D. and Patel, Aakash and Torfs, Tom and Bozkurt, Alper}, year={2021} }
 @misc{holder_gruen_roberts_somers_bozkurt_2020, title={A Systematic Literature Review of Animal-Assisted Interventions in Oncology (Part II): Theoretical Mechanisms and Frameworks}, volume={19}, ISSN={["1552-695X"]}, DOI={10.1177/1534735420943269}, abstractNote={Animal-assisted interventions (AAIs) can improve patients’ quality of life as complementary medical treatments. Part I of this 2-paper systematic review focused on the methods and results of cancer-related AAIs; Part II discusses the theories of the field’s investigators. Researchers cite animal personality, physical touch, physical movement, distraction, and increased human interaction as sources of observed positive outcomes. These mechanisms then group under theoretical frameworks such as the social support hypothesis or the human-animal bond concept to fully explain AAI in oncology. The cognitive activation theory of stress, the science of unitary human beings, and the self-object hypothesis are additional frameworks mentioned by some researchers. We also discuss concepts of neurobiological transduction connecting mechanisms to AAI benefits. Future researchers should base study design on theories with testable hypotheses and use consistent terminology to report results. This review aids progress toward a unified theoretical framework and toward more holistic cancer treatments.}, journal={INTEGRATIVE CANCER THERAPIES}, author={Holder, Timothy R. N. and Gruen, Margaret E. and Roberts, David L. and Somers, Tamara and Bozkurt, Alper}, year={2020}, month={Jul} }