Why the study?
Serious practical issues remain for physiological signal acquisition from users in their own environments using commodity sensors.
The paper describes a novel robust processing algorithm to improve signal acquisition and detection from noisy mobile ECG sensors in real-world environments.
Could facilitate ambulatory ECG with capacitive sensors; leaves open prospective clinical validation.
We discuss selected emerging technologies in physiological signal processing, low-cost pervasive sensors, diagnostic pattern recognition, and some research issues they entail. Serious practical issues remain for signal acquisition from users in their own environments using these commodity sensors. To illustrate the technical issues, we describe a novel robust processing algorithm for mobile ECG sensors (i.e. non-contact capacitive sensors with low signal-to-noise ratios). We describe the detection techniques designed to function effectively with such noisy ECG data.
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Stanford et al. (2019) studied this question.
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