The Thoracic Electrical Bioimpedance(TEB)helps to determine the stroke volume during cardiac arrest.While measuring cardiac signal it is contaminated with artifacts.The commonly encountered artifacts are Baseline wand...The Thoracic Electrical Bioimpedance(TEB)helps to determine the stroke volume during cardiac arrest.While measuring cardiac signal it is contaminated with artifacts.The commonly encountered artifacts are Baseline wander(BW)and Muscle artifact(MA),these are physiological and nonstationary.As the nature of these artifacts is random,adaptive filtering is needed than conventional fixed coefficient filtering techniques.To address this,a new block based adaptive learning scheme is proposed to remove artifacts from TEB signals in clinical scenario.The proposed block least mean square(BLMS)algorithm is mathematically normalized with reference to data and error.This normalization leads,block normalized LMS(BNLMS)and block error normalized LMS(BENLMS)algorithms.Various adaptive artifact cancellers are developed in both time and frequency domains and applied on real TEB quantities contaminated with physiological signals.The ability of these techniques is measured by calculating signal to noise ratio improvement(SNRI),Excess Mean Square Error(EMSE),and Misadjustment(Mad).Among the considered algorithms,the frequency domain version of BENLMS algorithm removes the physiological artifacts effectively then the other counter parts.Hence,this adaptive artifact canceller is suitable for real time applications like wearable,remove health care monitoring units.展开更多
Objective: This study was conducted to compare the cardiac output by using Electrical Cardiometry (EC), a noninvasive method of continuous cardiac output monitoring during cardiac surgery with pulmonary artery cathete...Objective: This study was conducted to compare the cardiac output by using Electrical Cardiometry (EC), a noninvasive method of continuous cardiac output monitoring during cardiac surgery with pulmonary artery catheter (PAC) derived cardiac output. Design: Prospective observational clinical study. Setting: Cardiac surgery operating room of a tertiary care cardiac center. Participants: Twenty five patients undergoing coronary artery bypass surgery with cardiopulmonary bypass. Measurements and Main Results: A total of 150 double data of cardiac output were compared with Thermodilution Cardiac Output (TDCO) and Thoracic Electrical Bioimpedance (TEBCO). The TDCO value ranges from 1.8-6.9 litre·min-1 with a mean of 4.39 ± 1.16 litre·min-1 and TEBCO ranges from 1.8-7.1 litre·min-1 with a mean of 4.21 ± 1.16 litre·min-1. The averaged Bland-Altman analysis for TDCO and TEBCO revealed that a mean bias was 0.18 and limit of agreement was -1.25 - 0.89 litre·min-1 and the percentage error (PE) ranged from 22%-32%. The precision for the TDCO was measured to be ±16.2% and the precision for TEBCO was ±19.6%. Receiver Operating Characteristic (ROC) curve analysis between TDCO and TEBCO with a cutoff of 15% shows a sensitivity of 84% and specificity of 63 and area under ROC curve of 0.80. Mountain plot between TDCO and TEBCO shows that a median percentile is 0.25 and value of 97.5 percentile is 1.525. Conclusions: The present study indicates that the electric cardiometry device yields numerically comparable results to cardiac outputs derived from the PAC during the cardiac surgery. Therefore, electrical cardiometry can be used to evaluate haemodynamic variables with clinically acceptable accuracy, when invasive methods are to be avoided or not available.展开更多
文摘The Thoracic Electrical Bioimpedance(TEB)helps to determine the stroke volume during cardiac arrest.While measuring cardiac signal it is contaminated with artifacts.The commonly encountered artifacts are Baseline wander(BW)and Muscle artifact(MA),these are physiological and nonstationary.As the nature of these artifacts is random,adaptive filtering is needed than conventional fixed coefficient filtering techniques.To address this,a new block based adaptive learning scheme is proposed to remove artifacts from TEB signals in clinical scenario.The proposed block least mean square(BLMS)algorithm is mathematically normalized with reference to data and error.This normalization leads,block normalized LMS(BNLMS)and block error normalized LMS(BENLMS)algorithms.Various adaptive artifact cancellers are developed in both time and frequency domains and applied on real TEB quantities contaminated with physiological signals.The ability of these techniques is measured by calculating signal to noise ratio improvement(SNRI),Excess Mean Square Error(EMSE),and Misadjustment(Mad).Among the considered algorithms,the frequency domain version of BENLMS algorithm removes the physiological artifacts effectively then the other counter parts.Hence,this adaptive artifact canceller is suitable for real time applications like wearable,remove health care monitoring units.
文摘Objective: This study was conducted to compare the cardiac output by using Electrical Cardiometry (EC), a noninvasive method of continuous cardiac output monitoring during cardiac surgery with pulmonary artery catheter (PAC) derived cardiac output. Design: Prospective observational clinical study. Setting: Cardiac surgery operating room of a tertiary care cardiac center. Participants: Twenty five patients undergoing coronary artery bypass surgery with cardiopulmonary bypass. Measurements and Main Results: A total of 150 double data of cardiac output were compared with Thermodilution Cardiac Output (TDCO) and Thoracic Electrical Bioimpedance (TEBCO). The TDCO value ranges from 1.8-6.9 litre·min-1 with a mean of 4.39 ± 1.16 litre·min-1 and TEBCO ranges from 1.8-7.1 litre·min-1 with a mean of 4.21 ± 1.16 litre·min-1. The averaged Bland-Altman analysis for TDCO and TEBCO revealed that a mean bias was 0.18 and limit of agreement was -1.25 - 0.89 litre·min-1 and the percentage error (PE) ranged from 22%-32%. The precision for the TDCO was measured to be ±16.2% and the precision for TEBCO was ±19.6%. Receiver Operating Characteristic (ROC) curve analysis between TDCO and TEBCO with a cutoff of 15% shows a sensitivity of 84% and specificity of 63 and area under ROC curve of 0.80. Mountain plot between TDCO and TEBCO shows that a median percentile is 0.25 and value of 97.5 percentile is 1.525. Conclusions: The present study indicates that the electric cardiometry device yields numerically comparable results to cardiac outputs derived from the PAC during the cardiac surgery. Therefore, electrical cardiometry can be used to evaluate haemodynamic variables with clinically acceptable accuracy, when invasive methods are to be avoided or not available.
文摘目的观察依托咪酯乳剂全麻诱导对高龄和休克病人血液动力学的影响.方法选择100例ASAⅡ～Ⅲ级老年或出血性休克的手术病人,用芬太尼4μg/kg、维库溴铵0.1mg/kg、依托咪酯0.2～0.3 mg/kg进行麻醉诱导,监测平均动脉压(MAP)、心率(HR)、每搏量(SV)、每膊指数(SI)、心排血量(CO)、心脏指数(CI)、心脏加速度(ACI)、左心功(LCW)及左心功指数(LCWI).分别于诱导前、静注依托咪酯1、2、3min以及气管内插管后3min,记录上述指标.结果与诱导前比较,静注依托咪酯后1～3 min MAP、HR、SV、SI、CO、CI、ACI、LCW、LCWI均有不同程度降低(P＜0.05).气管插管后3 min,MAP、HR、CO、CI、ACI较诱导前明显升高(P＜0.05),其余指标均恢复至基础值水平.整个诱导过程中心功能的各指标的最大改变均不超过20%.结论依托咪酯麻醉诱导对高龄和休克病人血液动力学的影响轻微.对于血液动力学不稳定病人,依托咪酯是麻醉诱导的较佳选择.
