Smart Health Lab, Department of Digital Health, Samsung Advanced Institute for Health Science & Technology (SAIHST), Sungkyunkwan University, Seoul, Republic of Korea.
Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Stud Health Technol Inform. 2023 May 18;302:651-655. doi: 10.3233/SHTI230229.
Despite the increasing presence of social robots (SRs) in Human-Robot Interaction, there are few studies that quantify these interactions and explore children's attitudes by analyzing real-time data as they communicate with SRs. Therefore, we attempted to explore the interaction between pediatric patients and SRs by analyzing the interaction log collected from real-time. This study is a retrospective analysis of data collected in a prospective study conducted on 10 pediatric cancer patients at tertiary hospitals in Korea. Using the Wizard of Oz method, we collected the interaction log during the interaction between pediatric cancer patients and the robot. Out of the collected data, 955 sentences from the robot and 332 sentences from the children were available for analysis, except for the logs that were missing due to environmental errors. we analyzed the delay time from saving the interaction log and the sentence similarity of the interaction log. The interaction log delay time between robot and child was 5.01 seconds. And the child's delay time averaged 7.2 seconds, which was longer than the robot's delay time of 4.29 seconds. Additionally, as a result of analyzing the sentence similarity of the interaction log, the robot (97.2%) was higher than the children (46.2%). The results of the sentiment analysis of the patient's attitude toward the robot were 73% neutral, 13.59% positive, and 12.42% negative. The observational evaluations of pediatric psychological experts identified curiosity (n=7, 70.0%), activity (n=5, 50.0%), passivity (n=5, 50.0%), sympathy (n=7, 70.0%), concentration (n=6, 60.0%), high interest (n=5, 50.0%), positive attitude (n=9, 90.0%), and low interaction initiative (n=6, 60.0%). This study made it possible to explore the feasibility of interaction with SRs and to confirm differences in attitudes toward robots according to child characteristics. To increase the feasibility of human-robot interaction, measures such as improving the completeness of log records by enhancing the network environment are required.
尽管社交机器人 (SRs) 在人机交互中越来越常见，但很少有研究通过分析与 SR 交互时的实时数据来量化这些交互并探索儿童的态度。因此，我们试图通过分析实时收集的交互日志来探索儿科患者与 SR 之间的交互。本研究是对在韩国三家三级医院对 10 名儿科癌症患者进行的前瞻性研究中收集的交互日志进行的回顾性分析。使用 Wizard of Oz 方法，我们收集了儿科癌症患者与机器人交互时的交互日志。在收集的数据中，除了由于环境错误而丢失的日志外，机器人有 955 条句子，儿童有 332 条句子可供分析。我们分析了交互日志的延迟时间和交互日志的句子相似度。机器人和儿童之间的交互日志延迟时间为 5.01 秒。而儿童的延迟时间平均为 7.2 秒，长于机器人的 4.29 秒延迟时间。此外，通过分析交互日志的句子相似度，机器人（97.2%）高于儿童（46.2%）。对患者对机器人态度的情绪分析结果为 73%中性、13.59%积极和 12.42%消极。儿科心理专家的观察评估确定了好奇心（n=7，70.0%）、活跃度（n=5，50.0%）、被动性（n=5，50.0%）、同情心（n=7，70.0%）、专注力（n=6，60.0%）、高兴趣（n=5，50.0%）、积极态度（n=9，90.0%）和低交互主动性（n=6，60.0%）。本研究使得探索与 SR 进行交互的可行性并确认根据儿童特征对机器人的态度差异成为可能。为了提高人机交互的可行性，需要采取措施通过增强网络环境来提高日志记录的完整性。
