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Human vital sign determination using tactile sensing and fuzzy triage system
Expert Systems with Applications ( IF 8.5 ) Pub Date : 2021-03-04 , DOI: 10.1016/j.eswa.2021.114781
Emmett Kerr , T.M. McGinnity , Sonya Coleman , Andrea Shepherd

The ability to quickly and accurately triage a person’s medical condition in an emergency situation or other critical scenarios could mean the difference between life and death. Endowing a robotic system with vision and tactile capabilities, similar to those of medical professionals, and thus enabling robots to assess a patient’s status in an emergency is a highly sought after characteristic in healthcare robotics. This paper presents a novel fuzzy triage system exploiting visual and tactile sensing, to equip a robot with the skills to accurately determine key vital signs in humans. There are three key signs of human health: respiratory rate, pulse rate (Beats Per Minute (BPM)) and capillary refill time. Using ground truth from a medical professional, the fuzzy triage system is trained and validated initially with informed synthetic data and then further evaluated using vital signs data collected from subjects in a pilot study. Results from this pilot study indicate that the fuzzy triage system is capable of classifying a patient’s health using the novel approaches for collecting BPM, Respiratory Rate (RR) and Capillary Refill Time (CRT) which replicate, to some extent, the approaches used by medical professionals for measuring vital signs. Furthermore, the intelligent system proved capable of determining whether a pulse was regular or arrhythmic, whether respiratory rate was regular or irregular, and determining the subject’s capillary refill time. Such results imply that this system could ultimately be used, for example, in a home assistance robot for elderly or disabled persons, or as a first responder robot. Ultimately the aim would be that these methods could be utilised by robotic systems in emergency scenarios or disaster zones.



中文翻译:

利用触觉和模糊分类系统确定人的生命体征

在紧急情况下或其他紧急情况下快速准确地对一个人的医疗状况进行分类的能力可能意味着生与死之间的差异。与医疗专业人员相似,赋予机器人系统以视觉和触觉能力的能力,从而使机器人能够在紧急情况下评估患者的状况是医疗保健机器人的高度追求的特征。本文提出了一种新颖的模糊分类系统,该系统利用视觉和触觉感应,使机器人具备准确确定人体关键生命体征的技能。人体健康的三个主要指标是:呼吸频率,脉搏频率(每分钟心跳数(BPM))和毛细血管补充时间。利用医学专家的实情,首先,对模糊分类系统进行了训练和验证,并使用了知情的合成数据,然后使用从试点研究中的受试者收集的生命体征数据进一步进行了评估。这项初步研究的结果表明,模糊分类系统能够使用新颖的BPM,呼吸频率(RR)和毛细血管补充时间(CRT)收集方法对患者的健康状况进行分类,这些方法在一定程度上可以复制医学上使用的方法。测量生命体征的专业人员。此外,该智能系统被证明能够确定脉搏是否正常或心律不齐,呼吸频率是否正常或不规则,并确定受试者的毛细血管充盈时间。这样的结果意味着该系统最终可以用于例如老人或残疾人的家庭辅助机器人中,或作为第一响应机器人。最终目标是在紧急情况或灾区中由机器人系统使用这些方法。

更新日期:2021-03-19
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