SBIR Phase I: Objective Assessment of Agitation and Sedation

该小型企业创新研究I期项目将研究为重症监护室（ICU）患者开发客观的激动和镇静评估算法的可行性。研究了使用机器学习来识别临床相关信息以表征患者的躁动和镇静状态。此外，计划？校准？并验证由算法提供的躁动和镇静评分将被设计。对于接受重症监护的患者来说，躁动和镇静评估是一个具有挑战性的问题。躁动主要表现为过度的粗大运动，74%的成年人在ICU住院期间经历过躁动。激动的患者可能会因过度的肌肉骨骼活动而移动重要的生命支持和监测设备，从而对自己造成身体伤害。过度镇静会增加患者的风险，因为镇静剂导致意识水平降低和呼吸抑制，可能无法从机械通气中解脱出来。目前，评估由临床工作人员进行，并且不存在用于此类评估的技术。预计通过这项研究，新的算法，可靠的检测病人？该项目更广泛的影响/商业潜力包括减少临床工作人员的工作量和医疗保健成本。目前的临床实践中，在病人的重症监护需要护理人员评估病人的躁动和镇静状态，并提供镇静剂，以改善病人的躁动。该过程依赖于主观评估，可能导致过度镇静，这反过来又增加了干预次数、机械通气时间和ICU停留时间，因此增加了医疗费用。一个客观的激动和镇静评估系统的发展可以有很大的影响，在重症监护环境中的护理质量。这样的系统可以实现连续的患者监测并提高护理质量。目前，临床工作人员需要照顾多名患者，对患者进行连续监测是不可行的。此外，在没有自动化的激动和镇静评估算法的情况下，由于患者重症监护问题的复杂性质和临床工作人员的工作量，可能会忽略镇静不足或镇静过度的早期指示。

This Small Business Innovation Research Phase I project is will investigate the feasibility of developing an objective agitation and sedation assessment algorithm for patients in the intensive care unit (ICU). Use of machine learning to identify clinically relevant information to characterize the agitation and sedation state of the patients is investigated. Furthermore, a plan to ?calibrate? and validate the agitation and sedation score provided by the algorithm will be designed. Agitation and sedation assessment is a challenging problem for patients undergoing critical care. Agitation, which is primarily characterized by excessive gross motor movement, is experienced by 74% of adults during ICU stay. Agitated patients may do physical harm to themselves by dislodging vital life support and monitoring devices with excessive musculoskeletal activity. Oversedation increases risk to the patient since liberation from mechanical ventilation may not be possible due to a diminished level of consciousness and respiratory depression from sedative. Currently, the assessment is performed by the clinical staff and no technology exists for such assessment. It is anticipated that through this research, novel algorithms for reliable detection of a patient?s agitation and sedation state using their physiological signals will be developed.The broader impact/commercial potential of this project includes reduction in clinical staff workload and healthcare costs. Current clinical practice in patient critical care requires the nursing staff to assess the patient's agitation and sedation state and provide sedatives to ameliorate the patient's agitation. The process relies on subjective assessments and may result in oversedation, which in turn increases the number of interventions, length of mechanical ventilation, and duration of stay in the ICU, and hence, increases healthcare costs. Development of an objective agitation and sedation assessment system can have a great impact on the quality of care in a critical care setting. Such a system can enable continuous patient monitoring and increase quality of care. Currently, clinical staff need to attend to multiple patients and continuous monitoring of patients is not feasible. In addition, in the absence of an automated agitation and sedation assessment algorithm, early indications of undersedation or oversedation can be overlooked due to the complex nature of the patient critical care problem and clinical staff's workload.