Pressure sensitive mats for patient monitoring in the NICU

压敏垫（PSM）正在积极研究和应用于监测成人患者，无论是在医院还是在他们的家里。PSM使用传感器网格测量接触压力，并以图像形式生成数据。这些数据已被广泛用于成人患者人群，以评估各种健康指标。它们特别适用于连续的患者监测，因为它们是非侵入性的，通常放置在床垫下面。然而，很少有关于使用压敏垫监测新生儿的研究，特别是在新生儿重症监护室（NICU）中。 NICU中的患者在任何时候都使用生理监测器进行仔细监测。持续监测生理数据有助于临床医生进行诊断和分析。特别地，血氧被仔细地跟踪，并且每当新生儿的氧气水平低于设定阈值时，就会产生警报。误报率非常高，导致“警报疲劳”，这反过来又会导致错误地忽略警报。这些假警报中有许多是由SpO 2电极导线上的运动诱导伪影引起的。此外，已知估计呼吸速率的当前方法是不可靠的。** 本研究将调查PSM准确测量呼吸和检测患者运动的潜力。PSM和生理数据之间的传感器融合可能会改善新生儿的监测，降低误报率。本研究将首先确定PSM用于新生儿患者监测的适用性;新生儿的低质量对检测和监测提出了独特的挑战。将在CHEO的患者模拟设施中进行台架测试，以建立基于PSM的新生儿运动和呼吸检测的基线潜力。然后将在CHEO NICU开始收集实际患者数据，在那里将同时收集PSM数据和SpO 2、ECG以及临床事件和干预措施的床旁观察结果。这些数据将用于开发新的数据分析算法，用于基于PSM的呼吸率估计以及检测和抑制运动引起的假警报。

Pressure-sensitive mats (PSM) are being actively investigated and applied to monitoring adult patients, both in hospital and in their home. PSM measure contact pressure using a grid of sensors and produce data in the form of an image. These data have been widely used among adult patient populations to assess a variety of health indicators. They are particularly appropriate for continuous patient monitoring since they are non-invasive and non-intrusive, often being placed below the mattress. However, there is little research into the use of pressure-sensitive mats in monitoring neonates, particularly those in the neonatal intensive care unit (NICU).** Patients in the NICU are carefully monitored at all times using physiological monitors. Continuous monitoring of physiologic data assists clinicians in making diagnoses and prognoses. In particular, blood oxygen is carefully tracked and alarms are generated whenever a neonate's oxygen levels fall below set thresholds. The rate of false alarms is very high leading to "alarm fatigue" which, in turn, can lead to missed alarms which are incorrectly dismissed. Many of these false alarms are caused by motion-induced artifacts on the SpO2 leads. Furthermore, the current method of estimating respiration rate is known to be unreliable. ** This research will investigate the potential for PSM to accurately measure respiration and to detect patient movements. Sensor fusion between PSM and physiological data may lead to improved monitoring of neonates with reduced false alarm rates. This research will first establish the suitability of PSM for patient monitoring of neonates; their low mass presents unique challenges for detection and monitoring. Bench testing will be conducted in the patient simulation facility at CHEO to establish baseline potential for PSM-based detection of movement and respiration for neonates. The collection of actual patient data will then be initiated in the CHEO NICU, where PSM data will be collected simultaneously with SpO2, ECG, and bedside observations of clinical events and interventions. These data will be used to develop novel data analytics algorithms for PSM-based estimation of respiration rates and the detection and suppression of motion-induced false alarms.******