An Integrated Compensation System Based on Empirical Mode Decomposition for Robust Noninvasive Blood Pressure Estimation
When it comes to monitoring human health, accuracy is not a choice. Accuracy in blood pressure (BP) estimation is essential for proper diagnosis and management of hypertension. An error of 5 mmHg is so serious, it can be responsible for doubling or halving number of patients diagnosed with hypertension. Motion artifacts are external sources of inaccuracy and can be due to sudden arm motion, muscle tremor, shivering, and transport vehicle vibration. Medium term drift, due to changing environmental factors, such as ambient temperature, can also contribute to the inaccuracy. Long term drift (ageing), can reach 9 mmHg during the first three months of usage. In this thesis, a new stage is added to current cuff based BP devices. This stage is responsible for adjusting the pressure reading before displaying it to end users. The proposed stage is provided with a 3-axis accelerometer, which makes the detection of motion artifacts during measurement possible. Moreover, it monitors changes in the ambient temperature and sensor ageing, so that it will adaptively compensate for these inaccuracies. These sources of inaccuracy are suppressed using algorithms based on Empirical Mode Decomposition (EMD), which has the feature of removing unwanted noise components little effect on the phase or the frequency distribution of the measured signal. With motion artifacts, measurements show that the proposed algorithms considerably improved the accuracy of the blood pressure estimates in comparison with the commonly-used conventional oscillometric algorithm that does not include a stage for artifact suppression, and allowed the estimates to consistent with the international ANSI/AAMI/ISO standard. Moreover, simulations based on experimental results show that the system is able to compensate for drift due to temperature changes and ageing with excellent performance. Results show promise towards building a robust BP monitor, with very low errors due to motion artifacts, environmental changes, and ageing.
Blood pressure, Accelerometer, motion artifact, drift, ageing, EMD
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Université d'Ottawa / University of Ottawa