This paper aims to develop an alternative heart rate measurement system using low-cost sensors to obtain vibrations caused by the heart in the ribcage when a heartbeat is generated. The use of recurrent neural networks is used to estimate the photoplethysmographic signal by acquiring seismocardiography signals. A training method is determined together with the sensor that will generate the lowest error results and with the most accurate estimation.
