Sensors
Dual-Channel Sensing and Event-Based Feedback for Cardiopulmonary Resuscitation Training
Par Haoxiang Zhang, Xinyu Zhu, Heyan Yang et 2 autres.
Contenu en anglais
Résumé
Coordinated compression and ventilation feedback in manikin-based cardiopulmonary resuscitation (CPR) training requires clear links between sensor measurements, detected events and quality decisions. We characterise these links in an STM32 prototype combining a BF350 strain gauge, an AD620 interface and an HU108 airflow switch. Five static laser-reference pairs used for recalibration yielded a mean system-minus-reference bias of +1.14 mm, MAE of 1.34 mm and RMSE of 1.98 mm. Loading–unloading separation was 0.7–2.3 mm, and refitted conversion coefficients varied with installation. Laser-labelled qualified-compression trials yielded count-based sensitivities of 88.0–93.5% across regular rhythms; false-positive proportions were 46.5% for shallow actions and 20.5% for incomplete release. Controlled forward-flow tests detected 30/30 routine pulses and 3/30 weakest pulses, with 99.89% specificity in the defined one-second no-flow windows. Across 100 electrical input-to-LED-driver tests, mean delay was 26.4 ms and the observed range was 17.5 ms. These results define an operating envelope for the prototype and identify calibration, action qualification and airflow intensity as distinct determinants of feedback reliability. The reported endpoints are calibration-set agreement, count-based classification and electrical driver timing; accuracy on held-out data, physical compression-to-light/sound latency and educational effectiveness require separate evaluation.



