COMPUTERIZED ARTIFACT DETECTION FOR VENTILATORY INDUCTANCE PLETHYSMOGRAPHIC APNEA MONITORS
COMPUTERIZED ARTIFACT DETECTION FOR VENTILATORY INDUCTANCE PLETHYSMOGRAPHIC APNEA MONITORS
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DOI：
10.1007/bf01627449
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发表时间：
1989-07-01
期刊：
影响因子：
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通讯作者：
WATERFALL, BT
中科院分区：
文献类型：
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作者：
EAST, KA;EAST, TD;WATERFALL, BT
呼吸机感应体积描记术可以对患者的呼吸进行无创监测。与呼吸无关的患者运动会导致呼吸机感应体积图测量的严重误差，并限制其用途。这项研究的目的是开发和测试一种基于微处理器的实时数字信号处理器，该处理器使用自适应滤波器来检测与呼吸无关的患者运动。对20名男性志愿者进行了自适应过滤器处理器的回溯性鉴定，他们在安静的仰卧呼吸期间进行了以下特定动作：抬起胳膊和腿(缓慢、快速、一次和多次)、坐起、深呼吸和快速呼吸，以及从仰卧姿势滚动到侧卧位。同时用连接在口器上的气体流量计直接测量流量。采用多元线性回归的方法，连续计算出与肺通气图和呼吸机诱导体积图信号相关的校准常数。然后对呼吸诱导体积图数据进行处理，并对结果进行评分。共有166个动作。在166个动作中，有146个动作(88%)的校正系数发生了显著变化。这些运动在计算通风诱导体积图流量时会产生较大误差。这些变化持续了运动的持续时间，并在两到三次呼吸内恢复到基线。在安静的仰卧呼吸中，系数的变化比基线附近的变异性大五倍或更多。所有的整体身体运动和呼吸模式的变化都被准确地检测出来。过滤器检测到了53个上半身运动中的46个，36个下半身运动中的34个，38个全身运动中的38个，以及19个呼吸模式改变中的19个。过滤器能够检测到146个动作中的94%。这些结果有助于提高呼吸诱导体积描记术在接受硬膜外麻醉的患者中作为呼吸暂停监测仪的有效性。在睡眠研究、肺部评估或运动评估中也可以进行更准确的呼吸评估。
Ventilatory inductive plethysmography allows noninvasive monitoring of patient ventilation. Patient movements unrelated to breathing introduce severe errors in ventilator inductive plethysmographic measurements and restrict its usefulness. The purpose of this research was to develop and test a microprocessor-based real-time digital signal processor that uses an adaptive filter to detect patient movements unrelated to breathing. The adaptive filter processor was tested for retrospective identification of artifacts in 20 male volunteers who performed the following specific movements between epochs of quiet, supine breathing: raising arms and legs (slowly, quickly, once, and several times), sitting up, breathing deeply and rapidly, and rolling from a supine to a lateral decubitis position. Flow was simultaneously measured directly with a pneumotachograph attached to a mouthpiece. A multilinear regression was used to continuously calculate the calibration constants that relate the pneumotachographic and ventilatory inductive plethysmographic signals. Ventilatory inductive plethysmographic data were then processed, and results scored. There were a total of 166 movements. The calibration coefficients changed dramatically in 146 (88%) of the 166 movements. These movements would have significant errors on ventilatory inductive plethysmographic flow calculation. The changes lasted for the duration of the movements and returned to baseline within two to three breaths. The changes in the coefficients were five or more times larger than the variability around baseline during quiet, supine breathing. All of the total body movements and changes in breathing patterns were detected accurately. The filter detected 46 of 53 upper body movements, 34 of 36 lower body movements, 38 of 38 total body movements, and 19 of 19 breathing pattern changes where the calibration changed. The filter was able to detect 94% of the total 146 movements. These results could help improve the effectiveness of ventilatory inductive plethysmography as an apnea monitor for use in patients receiving epidural narcotics. More accurate respiratory assessments could also be made during sleep studies, pulmonary evaluations, or exercise evaluations.