"Finally, using a technique called principal component analysis, the algorithm decomposes the resulting signal into several constituent signals, which represent aspects of the remaining movements that don’t appear to be correlated with each other. Of those signals, it selects the one that appears to be the most regular and that falls within the typical frequency band of the human pulse."
Given the filtering of the signal using principal component analysis. I wonder how sensitive this technique could be for arrhythmia detection, since many arrhythmias are inherently irregular. The potential for measuring cardiac output is already awesome, though, as it's useful for diagnosis of heart disease.
Given the filtering of the signal using principal component analysis. I wonder how sensitive this technique could be for arrhythmia detection, since many arrhythmias are inherently irregular. The potential for measuring cardiac output is already awesome, though, as it's useful for diagnosis of heart disease.