Motion artefact minimisation from a photoplethysmography based non-invasive sensor

The collection of photoplethysmography (PPG) signals from optical based sensor probes has been used extensively for the monitoring of heart rate (HR), respiration rate, blood pressure, oxygen saturation (SpO2), haemoglobin concentration (Hb). One of the drawbacks of PPG based measurement is that the signal is strongly degraded by motion artefact. Much research has been undertaken relating to the removal of motion artefact noise resulting from the wearer’s movement. Research reports show that the autonomic nervous system (ANS) of the human body, as part of the peripheral nervous system, can be disturbed by body motion events, leading to unconsciously varying vital physiological parameters including body temperature, blood pressure, respiration rate, eye pupils, and heartbeat. The PPG signal, as a recordable biosignal, can also be affected by ANS when accompanied by variations in physiological events e.g., exercise, breathing and motion, in general. An accelerometer and a wearable chest respiration monitor are introduced into the PPG sensor device to remove/minimise the low frequency noise induced by such physiological events. The results have shown that the baseline of PPG signal is affected by acceleration, particularly in the vertical direction as opposed to acceleration in the horizontal plane for the system under test. Experimental results from a total of 23 subjects demonstrated that PPG signals during motion events are influenced by the variation of local blood pressure at the point of measurement which is in turn induced from: (1) the vertical height difference between the measuring site and the reference level (the heart level); and (2) the ANS variation. Furthermore, a novel proposed filtering method based on envelope algorithm (not previously reported work) has been proposed with the analysis and comparison of existing artefact removal techniques. All data have been brought together to enable measurement of vital physiological parameters without corruption by noises including motion artefact, blood pressure and respiration variations