利用重症监护室（ICU）中的计算机视觉技术检查探视与活动情况
Leveraging Computer Vision in the Intensive Care Unit (ICU) for Examining Visitation and Mobility
AI总结：
本研究利用基于深度成像的无创计算机视觉系统，监测ICU探视与患者活动情况，发现探视次数与患者病情严重度、谵妄、疼痛存在关联，验证了该类系统用于ICU患者监测的可行性与潜力。
摘要：
尽管密切监测重症监护室（ICU）患者十分重要，但由于医护人员面临时间限制，许多方面的评估仍然十分有限。例如，尽管休息时间的过度探视可能会加剧昼夜节律紊乱和谵妄的风险，但这一点在ICU中并未被记录。同样，虽然活动情况可能是ICU患者康复或病情恶化的重要指标，但它只是被零星记录，甚至完全没有记录。\n在过去几年中，计算机视觉领域通过减轻人类负担，已在许多领域得到应用。在ICU中使用计算机视觉系统，还有可能实现目前尚未开展的评估，或提高现有评估的频率和准确性，同时减少工作人员的工作量。\n在本研究中，我们利用一种基于深度成像的最先进无创计算机视觉系统，来描述ICU探视情况和患者活动特征。随后我们探究了探视与若干患者结局（如疼痛、病情严重度和谵妄）之间的关系。我们发现，患者病情严重度恶化及谵妄的发生与探视次数增加存在关联。相反，通过国防与退伍军人疼痛评定量表（DVPRS）报告的自我报告疼痛与探视次数减少相关。我们的研究结果凸显了使用无创自主系统监测ICU患者的可行性与潜力。
英文摘要：
Despite the importance of closely monitoring patients in the Intensive Care Unit (ICU), many aspects are still assessed in a limited manner due to the time constraints imposed on healthcare providers. For example, although excessive visitations during rest hours can potentially exacerbate the risk of circadian rhythm disruption and delirium, it is not captured in the ICU. Likewise, while mobility can be an important indicator of recovery or deterioration in ICU patients, it is only captured sporadically or not captured at all. In the past few years, the computer vision field has found application in many domains by reducing the human burden. Using computer vision systems in the ICU can also potentially enable non-existing assessments or enhance the frequency and accuracy of existing assessments while reducing the staff workload. In this study, we leverage a state-of-the-art noninvasive computer vision system based on depth imaging to characterize ICU visitations and patients' mobility. We then examine the relationship between visitation and several patient outcomes, such as pain, acuity, and delirium. We found an association between deteriorating patient acuity and the incidence of delirium with increased visitations. In contrast, self-reported pain, reported using the Defense and Veteran Pain Rating Scale (DVPRS), was correlated with decreased visitations. Our findings highlight the feasibility and potential of using noninvasive autonomous systems to monitor ICU patients.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
