The use of dual accelerometers improves measurement of chest compression depth

Oh, Jaehoon; Song, Yeongtak; Kang, Boseung; Kang, Hyun–Sook; Lim, Taeho; Suh, Yoon Seok; Chee, Youngjoon

doi:10.1016/j.resuscitation.2011.09.028

Cited by 50 publications

(32 citation statements)

References 14 publications

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“…Perkins et al (7) reported that when used on a bed, accelerometer devices overestimate chest compression depth, indicating that these devices report accurate chest compression depths only when used on a hard floor. Oh et al (8) reported a solution to this problem involving two accelerometers used simultaneously; however, this technique is not available for commercial use. The results of our study confirmed our hypothesis.…”

Section: Discussionmentioning

confidence: 99%

Are chest compression depths measured by the Resusci Anne SkillReporter and CPRmeter the same?

Kim

2017

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Section: Discussionmentioning

confidence: 99%

Are chest compression depths measured by the Resusci Anne SkillReporter and CPRmeter the same?

Kim

2017

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“…However, the signal-processing algorithm was to reset integrals at each cycle to avoid error propagation by imposing cyclic boundary conditions. In another work, authors removed the drift of the integrated signal afterward making difficult an online processing [24] .…”

Section: Discussionmentioning

confidence: 99%

Using an inertial navigation algorithm and accelerometer to monitor chest compression depth during cardiopulmonary resuscitation

Boussen

Ibouanga-Kipoutou

Fournier

et al. 2016

Medical Engineering & Physics

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“…This limitation is also caused by using an accelerometer. 24 In addition to the feedback function, many other helpful functions are necessary for CPR-related apps. To implement a completion app, we will validate the app with the mannequin for large numbers of rescuers.…”

Section: Discussionmentioning

confidence: 99%

A New Chest Compression Depth Feedback Algorithm for High-Quality CPR Based on Smartphone

Song

Chee

2015

Telemedicine and e-Health

Self Cite

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Background: Although many smartphone application (app) programs provide education and guidance for basic life support, they do not commonly provide feedback on the chest compression depth (CCD) and rate. The validation of its accuracy has not been reported to date. This study was a feasibility assessment of use of the smartphone as a CCD feedback device. In this study, we proposed the concept of a new real-time CCD estimation algorithm using a smartphone and evaluated the accuracy of the algorithm. Materials and Methods: Using the double integration of the acceleration signal, which was obtained from the accelerometer in the smartphone, we estimated the CCD in real time. Based on its periodicity, we removed the bias error from the accelerometer. To evaluate this instrument's accuracy, we used a potentiometer as the reference depth measurement. The evaluation experiments included three levels of CCD (insufficient, adequate, and excessive) and four types of grasping orientations with various compression directions. We used the difference between the reference measurement and the estimated depth as the error. The error was calculated for each compression. Results: When chest compressions were performed with adequate depth for the patient who was lying on a flat floor, the mean (standard deviation) of the errors was 1.43 (1.00) mm. When the patient was lying on an oblique floor, the mean (standard deviation) of the errors was 3.13 (1.88) mm. Conclusions: The error of the CCD estimation was tolerable for the algorithm to be used in the smartphone-based CCD feedback app to compress more than 51 mm, which is the

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The use of dual accelerometers improves measurement of chest compression depth

Cited by 50 publications

References 14 publications

Are chest compression depths measured by the Resusci Anne SkillReporter and CPRmeter the same?

Are chest compression depths measured by the Resusci Anne SkillReporter and CPRmeter the same?

Using an inertial navigation algorithm and accelerometer to monitor chest compression depth during cardiopulmonary resuscitation

A New Chest Compression Depth Feedback Algorithm for High-Quality CPR Based on Smartphone

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