Pressure sensitive mats for patient monitoring in the NICU

压敏垫(PSM)正被积极研究并应用于监测成年患者，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，并以图像的形式产生数据。这些数据在成年患者群体中被广泛用于评估各种健康指标。它们特别适合持续监测患者，因为它们是非侵入性和非侵入性的，通常被放置在床垫下面。然而，关于使用压敏垫监测新生儿，特别是新生儿重症监护病房(NICU)中的新生儿的研究很少。NICU中的患者一直使用生理监护仪进行仔细监测。对生理数据的持续监测有助于临床医生做出诊断和预后。特别是，仔细跟踪血氧，每当新生儿的氧气水平降至设定的阈值以下时，就会发出警报。误报警率非常高，从而导致“报警疲劳”，进而可能导致漏报，而误报则会被错误地排除。这些错误警报中的许多是由SpO2导联上的运动诱导伪影引起的。此外，目前估计呼吸频率的方法是众所周知的不可靠的。这项研究将调查PSM在准确测量呼吸和检测患者活动方面的潜力。PSM和生理数据之间的传感器融合可能会改善对新生儿的监测，降低误警率。这项研究将首先确定PSM在新生儿患者监测中的适用性；他们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，CHEO NICU将开始收集实际的患者数据，PSM数据将与SpO2、ECG和临床事件和干预的床边观察同步收集。这些数据将被用于开发新的数据分析算法，用于基于PSM的呼吸频率估计以及检测和抑制运动诱导的错误警报。

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.