Key result
Open-source PSM outperforms commercial devices in signal-to-noise ratio, achieving ~12 dB for ECG.
p-value: p=<0.001
The proposed open-source hardware platform for physiological measurements demonstrates high signal-to-noise ratio, outperforming other commercial devices.
Low-cost open-source platform aids affective computing experiments; leaves open clinical validation before cardiovascular adoption.
In this article we present a new low-cost physiological signal acquisition platform in compliance with Open-Source Hardware philosophy. The device contains an electrocardiography circuit; two electrodermal activity channels that implement a time-multiplexing technique to remove inter-channel coupling interference; and a skin temperature module. These features make the platform suitable for experiments involving Affective Computing. We have assessed the performance of this device in terms of Signal-to-Noise Ratio (SNR) and Background Noise Level (BNL), an adapted MPEG7 feature for electrocardiography signals. This platform outperforms other commercial devices and most similar state-of-art studies on SNR. Results show values of 11.96, 30.01, 68.40 dB for ECG, EDA and ST, respectively, for SNR, and -28.31 dB for BNL in ECG. Both features were obtained by sampling physiological signals at a frequency of 256 Hz.
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Castro-García et al. (2019) studied Healthy volunteer (hardware validation) (n=1). Physiological Signal Module (PSM) vs. Commercial devices (e-Health v2, Q-Sensor, g.MOBIlab+) was evaluated on Signal-to-Noise Ratio (SNR) (p=<0.001). The Physiological Signal Module (PSM) outperformed commercial devices in Signal-to-Noise Ratio, achieving 11.96 dB for ECG, 30.01 dB for EDA, and 68.40 dB for skin temperature.
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