Real-Time Processing Library for Open-Source Hardware Biomedical Sensors
|Author/s||Molina Cantero, Alberto Jesús
Castro García, Juan Antonio
Gómez González, Isabel María
Merino Monge, Manuel
|Department||Universidad de Sevilla. Departamento de Tecnología Electrónica|
|Abstract||Applications involving data acquisition from sensors need samples at a preset frequency
rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel
software architecture based on ...
Applications involving data acquisition from sensors need samples at a preset frequency rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel software architecture based on open-software hardware platforms which allows programmers to create data streams from input channels and easily implement filters and frequency analysis objects. The performances of the different classes given in the size of memory allocated and execution time (number of clock cycles) were analyzed in the low-cost platform Arduino Genuino. In addition, 11 people took part in an experiment in which they had to implement several exercises and complete a usability test. Sampling rates under 250 Hz (typical for many biomedical applications) makes it feasible to implement filters, sliding windows and Fourier analysis, operating in real time. Participants rated software usability at 70.2 out of 100 and the ease of use when implementing several signal processing applications was rated at just over 4.4 out of 5. Participants showed their intention of using this software because it was percieved as useful and very easy to use. The performances of the library showed that it may be appropriate for implementing small biomedical real-time applications or for human movement monitoring, even in a simple open-source hardware device like Arduino Genuino. The general perception about this library is that it is easy to use and intuitive.
|Citation||Molina Cantero, A.J., Castro García, J.A., Lebrato-Vázquez, C., Gómez González, I.M. y Merino Monge, M. (2018). Real-Time Processing Library for Open-Source Hardware Biomedical Sensors. Sensors, 18 (4)|