Abstract
AbstractCardiopulmonary resuscitation (CPR) is one of the most critical emergency interventions for sudden cardiac arrest. In this paper, a robust sinusoidal model-fitting method based on a Evolution Strategy inspired algorithm for CPR quality parameters – naming chest compression frequency and depth – as measured by an inertial measurement unit (IMU) attached to the wrist is presented. The proposed approach will allow bystanders to improve CPR as part of a continuous closed-loop support system once integrated into a smartphone or smartwatch application. By evaluating the model’s precision with data recorded by a training mannequin as reference standard, a variance for the compression frequency of $$\pm 2.22$$
±
2.22
compressions per minute (cpm) has been found for the IMU attached to the wrist. It was found that this previously unconsidered position and thus, the use of smartwatches is a suitable alternative to the typical placement of phones in hand for CPR training.
Funder
Niedersächsische Ministerium für Wissenschaft und Kultur
Hochschule für Angewandte Wissenschaften Hamburg (HAW Hamburg)
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology
Cited by
3 articles.
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1. Wearable Inertial and Pressure Sensors-Based Chest Compression Quality Assessment to Improve Accuracy and Robustness;IEEE Sensors Journal;2024-02-01
2. Cardiac Massage Practice Application using Barometer in a Smart Phone and Sealed Bag;Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing;2023-10-08
3. EA-based smartwatch application for training and assistance in cardiopulmonary resuscitation;Proceedings of the Companion Conference on Genetic and Evolutionary Computation;2023-07-15