A Detection System for Measuring the Patient’s Interest in Animal Robot Therapy Observation

The effectiveness of PARO, animal-like robots, as robot-assisted therapy has shown a positive impact on non-pharmacological therapy. However, the effectiveness of caregivers presenting PARO to patients needs to be evaluated due to the different skills possessed by caregivers. The way caregivers present PARO to patients will impact the patients’ interest response towards PARO. We propose a system that can measure patients’ interest in PARO by recognizing the reciprocal attention between PARO and humans. We built the system by integrating human skeleton tracking and PARO’s posture detection. Human skeleton tracking is reconstructed from multiple Kinect Azure devices, while PARO’s posture detection is achieved using a single RGBD camera placed on top of the field. We extract the attention parameter by calculating the difference in gaze direction between PARO and humans. The results showed that the proposed method successfully detected the gaze interaction between PARO and humans with an average accuracy rate of 97.59%.

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Publication Details

Journal
Journal of Robotics and Mechatronics
Published
2025-06-19
DOI
https://doi.org/10.20965/jrm.2025.p0666
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
0.00

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article

A Detection System for Measuring the Patient’s Interest in Animal Robot Therapy Observation

Azhar Aulia Saputra, Yoshiki Shimomura, Dwi Kurnia Basuki, Naoyuki Kubota et al.
Journal of Robotics and Mechatronics
Social Robot Interaction and HRI
article

A Detection System for Measuring the Patient’s Interest in Animal Robot Therapy Observation

Azhar Aulia Saputra, Yoshiki Shimomura, Dwi Kurnia Basuki, Naoyuki Kubota, Kaoru Inoue, Kazuyoshi Wada
article en

Abstract

The effectiveness of PARO, animal-like robots, as robot-assisted therapy has shown a positive impact on non-pharmacological therapy. However, the effectiveness of caregivers presenting PARO to patients needs to be evaluated due to the different skills possessed by caregivers. The way caregivers present PARO to patients will impact the patients’ interest response towards PARO. We propose a system that can measure patients’ interest in PARO by recognizing the reciprocal attention between PARO and humans. We built the system by integrating human skeleton tracking and PARO’s posture detection. Human skeleton tracking is reconstructed from multiple Kinect Azure devices, while PARO’s posture detection is achieved using a single RGBD camera placed on top of the field. We extract the attention parameter by calculating the difference in gaze direction between PARO and humans. The results showed that the proposed method successfully detected the gaze interaction between PARO and humans with an average accuracy rate of 97.59%.

Journal of Robotics and MechatronicsVol. 37(3)
Tokyo Metropolitan University (JP)
Japan Science and Technology Agency
Openalex Percentile: Top 84%
Social Robot Interaction and HRI
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