Key result
Singular value decomposition separates heartbeat from gait signals to recover blood pressure time series.
Why the study?
A method was needed to prevent the gait of a jogger from masking the heartbeat signal detected by a photodiode measuring light transmission through wrist tissues.
Answers are grounded in this paper and cite their sources.
A singular value decomposition approach successfully separates gait artifacts from heartbeat signals in wrist photodiode sensors, enabling accurate heart rate and blood pressure time series recovery during jogging.
A blind source signal separation problem that was brought to a Study Group in Limerick in 2013 required a way to prevent the gait of a jogger from masking the heartbeat, when detected by a simple photodiode that measures light transmission through a jogger’s wrist tissues. The group was successful in discovering a singular value decomposition (SVD) approach, which not only allows accurate detection of heart rate but also allows recovery of a good facsimile of the entire blood pressure time series from the mixed photodiode signal.
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Vo et al. (2016) studied Heart rate monitoring during exercise. Singular value decomposition (SVD) was evaluated on Separation of heartbeat from gait signal. Singular value decomposition successfully separated simulated gait and heartbeat signals from a mixed photodiode signal, allowing recovery of the blood pressure time series.
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