Abstract
BackgroundTo reduce the risk of patient damage and complications during the cardiopulmonary resuscitation (CPR) process in emergency situations, it is necessary to monitor the status of the patient and the quality of CPR while CPR processing without additional bio-signal measurement devices. In this study, an algorithm is proposed to estimate the mechanical impedance (MI) between an actuator of the CPR machine and the chest of the patient, and to estimate the power delivered to the chest of the patient during the CPR process.MethodsTwo sensors for force and depth measurement were embedded into a custom-made CPR machine and the algorithm for MI and power estimation was implemented. The performance of the algorithm was evaluated by comparing the results from the kinetic model, the conventional discrete Fourier transform (DFT), and the proposed method.ResultsThe estimations of the proposed method showed similar increasing/decreasing trends with the calculations from the kinetic model. In addition, the proposed method showed statistically equivalent performance in the MI estimation, and at the same time, showed statistically superior performance in the power estimation compared with the calculations from the conventional DFT. Furthermore, the MI and power estimation could be performed almost in real-time during the CPR process without excessive hands-off periods, and the intensity of random noise contained in the input signals did not seriously affect the MI and power estimations of the proposed method.ConclusionWe expect that the proposed algorithm can reduce various CPR-related complications and improve patient safety.
Highlights
To reduce the risk of patient damage and complications during the cardiopulmonary resuscitation (CPR) process in emergency situations, it is necessary to monitor the status of the patient and the quality of CPR while CPR processing without additional bio-signal measurement devices
For the P1 condition, the magnitude of the mechanical impedance (MI) was fixed at a constant value (64.9 Kgf s/m) regardless of the variations in the depth of chest compression in the kinetic model, and was 68.1 ± 3.8, 70.4 ± 3.4, and 64.8 ± 2.5 Kgf s/m when the depth of chest compression was 3, 4, and 5 cm, respectively, in the proposed method (Fig. 3a)
When ke = 680 Kgf/m, the magnitude of MI was 64.9, 65.9 ± 1.3, and 64.7 ± 2.5 Kgf s/m in the kinetic model, the conventional discrete Fourier transform (DFT), and the proposed method; in addition, the magnitude of the power delivered to the chest was 21.8, 14.7 ± 0.4, and 18.5 ± 0.8 W in the same tests
Summary
To reduce the risk of patient damage and complications during the cardiopulmonary resuscitation (CPR) process in emergency situations, it is necessary to monitor the status of the patient and the quality of CPR while CPR processing without additional bio-signal measurement devices. When emergency situations occur that induce stopping of the heart (e.g., drowning or cardiac arrest), it is important to perform the correct cardiopulmonary resuscitation (CPR) process as soon as possible to recover the autonomic beating of the native heart and prevent serious brain damage [1]. When such an emergency situation occurs in locations outside of a hospital due to accidents or disease, emergency services should be immediately contacted and manual CPR process needs to be performed repetitively until the arrival of the trained paramedics. To reduce such risk of patient harm, it is necessary to consistently monitor the status of patient and the quality of CPR during the operation of the CPR machine [3]
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