Contact-Free Simultaneous Sensing of Human Heart Rate and Canine Breathing Rate for Animal Assisted Interactions

Timothy R. N. Holder, Mushfiqur Rahman, E. Summers, David L. Roberts, Chau-Wai Wong, A. Bozkurt
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Abstract

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.
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人类心率和犬类呼吸频率在动物辅助互动中的无接触同步传感
动物辅助干预(AAIs)涉及人与动物之间愉快的互动,并可能使两种类型的参与者都受益。这一领域的研究可能有助于揭示跨物种键合、动态影响检测以及环境因素对二元相互作用的影响的普遍见解。然而,评估这些结果的实验仅限于定性、主观和繁琐的方法,因为与将传感器连接到身体有关的人体工程学挑战。当前的人工智能方法在超越受控的临床环境或研究背景时也面临着挑战。它们也常常忽略了动物在整个互动过程中的测量。在这里,我们提出了我们对无接触方法的初步努力,通过使用消费级相机对人类和犬类的生理感知来促进AAI评估。这项初步工作的重点是验证在人类受试者和狗受试者交互时遥感心率信号和呼吸频率信号的技术可行性。通过我们定制设计的基于视觉的算法,轻拍和无意识的身体抖动等少量动作都可以被容忍。实验结果表明,我们的算法得到的生理测量值与标准参比装置提供的测量值一致。随着进一步的验证和扩展到其他生理参数,本文提出的方法在从AAI研究领域到兽医、外科和临床应用的许多场景中都有很大的前景。
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