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심폐소생술에서 두 개의 가속도 센서를 활용한 흉부 압박 깊이 추정
송영탁,오재훈,서영수,지영준,Song, Yeong-Tak,Oh, Jae-Hoon,Suh, Young-Soo,Chee, Young-Joon 대한의용생체공학회 2010 의공학회지 Vol.31 No.5
During the cardiopulmonary resuscitation (CPR), the correct chest compression depth and period are very important to increase the resuscitation possibility. For the feedback of chest compression depth, the depth monitoring device based on the accelerometer is developed and widely used. But this method tends to overestimate the compression depth on the bed. To overcome this limitation, the chest compression depth estimation method using two accelerometers is suggested With the additional accelerometer between the patient and mattress on the bed, the compression of the mattress is also measured and it is used to compensate the overestimation error. The experimental results show that the single accelerometer estimates as 61.4mm for the actual compression depth of 43.6mm on the mattress. The depth estimation with the dual accelerometer was 44.6mm which is close to the actual depth. With the automatic zeroing in every single compression, the integration error for the depth can be reduced. The dual accelerometer method is effective to increase the accuracy of the chest compression depth estimation.
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송영탁,김민우,김진성,오재훈,지영준,Song, Yeongtak,Kim, Minwoo,Kim, Jinsung,Oh, Jaehoon,Chee, Youngjoon 대한의용생체공학회 2014 의공학회지 Vol.35 No.6
This study is to develop a basic life support (BLS) app using the android based smartphone and to evaluate the function of the app. Suggested app contains chest compression feedback function, the map of automated external defibrillator (AED), direct emergency call and the basic knowledge of BLS. Using the accelerometer of the smartphone, we implemented a real-time algorithm that estimates the chest compression depth and rate for high quality cardiopulmonary resuscitation (CPR). The accuracy of algorithm was evaluated by manikin experiment. We made contents which were easy to learn the BLS for the layperson and implemented a function that provides the AED location information based on the user's current location. From the manikin experiment, the chest compression depth and rate were no significant differences between the manikin data and the app's feedback data (p > 0.05). Developed BLS app was uploaded on Google Play Store and it was free to download. We expected that this app is useful to learn the BLS for the layperson.
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임태호,오재훈,조영석,강형구,김원희,지영준,송영탁,김인영,이준철 연세대학교의과대학 2016 Yonsei medical journal Vol.57 No.2
Purpose: During cardiopulmonary resuscitation (CPR), chest compression (CC) depth is influenced by the surface on which the patient is placed. We hypothesized that training healthcare providers to perform a CC depth of 6–7 cm (instead of 5–6 cm) on a manikinplaced on a mattress during CPR in the hospital might improve their proper CC depth. Materials and Methods: This prospective randomised controlled study involved 66 premedical students without CPR training. The control group was trained to use a CC depth of 5–6 cm (G 5–6), while the experimental group was taught to use a CC depth of 6–7 cm (G 6–7) with a manikin on the floor. All participants performed CCs for 2 min on a manikin that was placed on a bed 1 hour and then again 4 weeks after the training without a feedback. The parameters of CC quality (depth, rate, % of accurate depth) were assessed and compared between the 2 groups. Results: Four students were excluded due to loss to follow-up and recording errors, and data of 62 were analysed. CC depth and % of accurate depth were significantly higher among students in the G 6–7 than G 5–6 both 1 hour and 4 weeks after the training (p<0.001), whereas CC rate was not different between two groups (p>0.05). Conclusion: Training healthcare providers to perform a CC depth of 6–7 cm could improve quality CC depth when performing CCs on patients who are placed on a mattress during CPR in a hospital setting.
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