A Closed-loop Automatic Chest Compressions Cpr Optimization Control Research

Objective: Chest compression （CC） has been one of the cornerstones ofcardiopulmonary resuscitation （CPR） since its important role in maintaining blood flowduring ventricular fibrillation was discovered by Kouwenhoven and colleagues in1960.The purpose of CC during CPR is to create blood flow and oxygen delivery to themyocardium and brain for effective defibrillation by increasing intrathoracic pressureand directly compressing the heart. In order to improve the blood perfusion, in recentyears, the importance of the chest compression depth is re-emphasized. The2010American Heart Association Guidelines for Cardiopulmonary Resuscitation andEmergency Cardiovascular Care Circulation （2010AHA guidelines） even suggests thatCC with a depth greater than5cm will result in a larger proportion of survivors.It is known that increasing CC depth produces better pressures and blood flow inCPR. However, there is also an increased risk of breaking ribs, which then dramaticallyeffects chest pump function and reduces the effectiveness of CPR. More than that, therib and sterna fracture will injure lung, liver and other internal organs and endangerpatients’ lives. It should be fully recognized that the widespread application of CC as afirst aid measure inevitably has the potential to be both harmful and beneficial. Thus, therecommended level of sternal displacement must be determined from a combination ofsafety, feasibility, and blood flow considerations. However, relatively little attention hasbeen paid to this potential problem. Although2010AHA guidelines provided arecommended CC depth of at least5cm, the specific CC depth or a detailed CC depthscope was not presented. Most rescuers performed CC only according to their clinicalexperiences, without expertise on the delivery of safe and effective compressions. Inaddition, a large proportion of mechanical CC devices perform CC with a constantdepth on different patients, without effective assessment of the risks and benefitsresulting from their own CCs. The trade-off between the risks of rib fracture, liverlaceration or other injuries versus the benefits of enhanced blood flow is stillunresolved.The present study was therefore undertaken to develop an optimal CC closed-loopcontrol strategy （OCCCS） and algorithm （OCCCA） for automatic mechanical CCdevices that will provide an effective trade-off between the risk of chest injury and thebenefit of enhanced blood flow during CPR. Methods and Contents: With the intention to make an optimal trade-off betweenthe benefit of enhanced blood flow and the risk of chest injury, a series of studies werecarried out based on the theories of resuscitation and intelligent control. This paperincludes four major studies: identification of degree of blood flow and chest injury,design of OCCCS and OCCCA for automatic mechanical CC, development of CCclosed-loop resuscitation system and experimental tests.（1） Identification of degree of blood flow and chest injury: Based on surveysinvestigating several physiological indexes related to circulation and fracture, partialpressure of end-tidal CO₂（PETCO₂） and chest stiffness （Kchest） were chosen toevaluate the degree of blood flow and chest injury in emergency, respectively. Afterinvestigating the relationship between PETCO₂and blood flow, Kchest and sternalfracture, an effective evaluation rule and identification methods were proposed usingseveral key physiological characteristic values. In addition, a computer simulationmodel for cardiopulmonary resuscitation （CPR） was built. With the help of this model,the change rules of key physiological parameters during CC were summarized, whichwould provide the theoretic foundation for OCCCS and OCCCA.（2） Design of OCCCS and OCCCA for automatic mechanical CC: Based onclinical experience and fuzzy control algorithm, a robust and highly adaptable real-timeOCCCA for automatic mechanical CC device was proposed with the identificationalgorithm for trade-off between the risk and the benefit and the computer simulationmodel for CPR. The OCCCA includes five parts: signal preprocessing, input saturateprocessing, fuzzy control decision, output saturate processing and fuzzy PID automaticadjusting. The tasks implemented by the five parts are filtering and amplifying inputsignal, limiting the scope of input signal, making decision with fuzzy control strategy,limiting the scope of output signal, adjusting CC depth with fuzzy PID controller.（3） Development of CC closed-loop resuscitation system: Based on LabVIEWvirtual instrument, CC closed-loop resuscitation system （CCRS） was developed with thedesigning idea of virtual medical instrument. This system contains a physiologicalsignal detecting and processing model, a LabVIEW virtual instrument platform, anautomatic CC controller and a CC mechanism. The physical signal detecting andprocessing model was used to perform input signal （PETCO₂and Kchest） collectionand processing. The optimal CC depth was obtained based on the LabVIEW virtualinstrument platform, and then sent to the automatic CC controller. According to the optimal CC depth, the CC mechanism is driven by automatic CC controller withbrushless DC motor （BLDC） to perform optimal closed-loop CC.（4） Experimental tests: In order to verify the effectiveness of OCCCA, a computersimulation test was implemented based on the computer simulation model. For furtherexploring the performance of OCCCA in CPR practice and evaluating the effectivenessof the CCRS, a hardware simulation test was also performed to compare CCperformance between the CCRS and the traditional pneumatic mechanical compressor（Thumper） based on a physiological parameters model for mechanical chest compressor.Result: For verifying the effectiveness of OCCCA and CCRS, a computersimulation test and a hardware simulation test were both performed.（1） A computer simulation test: The OCCCA obtained a greater BRI and a bettertrade-off between risk and benefit than the traditional mechanical CC method （TMCM）in6out of a total9cases, and the OCCCA also resulted in a significantly improvedcardiac output （CO） and PETCO₂in6of the9cases. The mean BRI, CO and PETCO₂resulting from the OCCCA were5.69,1.45L/min and15.51mmHg, respectively, whilethe mean BRI, CO and PETCO₂resulting from TMCM were4.76,1.18L/min and13.26mmHg, respectively.（2） A hardware simulation test: The result of the hardware simulation test is similarto that of the computer simulation test. The CCRS obtained a greater BRI and a bettertrade-off between risk and benefit than Thumper in7out of a total9cases, and theCCRS also resulted in a significantly improved cardiac output （CO） and PETCO₂in6of the9cases. The mean BRI, CO and PETCO₂resulting from the CCRS were6.08,1.35L/min and15.7mmHg, respectively, while the mean BRI, CO and PETCO₂resulting from TMCM were5.21,1.14L/min and13.76mmHg, respectively.Both of a computer simulation test and a hardware simulation test showed thatOCCCA not only improved CO, PETCO₂and BRI in most cases, but also preventedgreat risk of chest injury. In contrast, because CC depth of TMCM is constant withdifferent chest stiffness, TMCM can not further improve blood flow in a large benefitlevel when chest is soft. More importantly, TMCM was likely to result in rib or sternalfracture when the risk factor （RF） is in a great risk level （γ=14N/cm2,15N/cm2）.Conclusion: With a strong ability to achieve trade-off between the benefit ofenhanced blood flow and the risk of chest injury, an OCCCA can provide safer and moreeffective CC during CPR compared to the TMCM. With the OCCCA, it is likely for the patients with a soft chest to obtain more blood flow, while those with a stiff chest avoidchest injuries. The OCCCA described by the present study may be taken into account asa good trade-off method of CC and applied in future mechanical CC devicedevelopment. With the help of the OCCCA, the efficiency of CC and the survival rate ofcardiac arrest patient will be both significantly improved, and the automation process ofCPR will also be promoted.