Cuffless blood pressure estimation based on haemodynamic principles: progress towards mobile healthcare

Although cuff-sphygmomanometry is used worldwide in medical and healthcare fields, it is a fact that the use of an occlusive cuff to obtain blood pressure (BP) is troublesome and inconvenient. There have therefore been on-going efforts to devise methods that do not require the use of a cuff, almost all being based on the measurement of pulse wave velocity or pulse transit time, but so far few significant developments have been made, especially regarding measurement accuracy. We have previously reported a smartphone-based cuffless method using a linear multiple regression calibration model comprising of BP obtained with a cuff-sphygmomanometer as an objective variable and modified normalized pulse volume (mNPV: a measure of vasoconstrictive activity in a finger) and pulse rate (PR) as explanatory variables. This requires a number of subjects to construct a calibration model and thus is largely dependent on the accuracy due to the model. To address these drawbacks, we report here a new cuffless method to surpass considerably the results of our previous study as well as earlier works.

With this method we can estimate BP, with much higher accuracy, using mNPV and PR, both also obtained from a smartphone-derived photoplethysmogram. The subject firstly performs a cuff-based BP measurement in parallel with the acquisition of mNPV and PR from a smartphone. These parameters are set as initial values (BP _c0, mNPV ₀ and PR ₀; initial calibration procedure). Then, the estimated BP (BP _e) can be calculated from the relation: "BP _e = (BP _c0·PR·mNPV)/(PR ₀·mNPV ₀)", which is derived from the so-called haemodynamic Ohm's law. To validate this method, preliminary experiments using 13 volunteers were carried out to compare results from the new method with those from the cuff-sphygmomanometry, used as a reference.

Altogether 299 paired data sets were analyzed: A good agreement was found between the cuff-based and the estimated BP values, with correlation coefficients of 0.968 for systolic BP (SBP), 0.934 for mean BP (MBP) and 0.844 for diastolic BP (DBP). Bland-Altman analyses for the BP _e (SBP _e, MBP _e, DBP _e) and the BP _c (SBP _c, MBP _c, DBP _c) values also supported these comparison results. Mean absolute differences between the BP _e and the BP _c values in total subjects were less than 5 mmHg. Fairly good tracking availability in terms of time series data of the BP _c against the corresponding BP _e values was also confirmed in each subject during the study periods (1-2 weeks for 12 subjects and about 4 months for one subject).

The present study reported the successful development of the new cuffless BP estimation method, given as the status of a trial stage of investigation. This method could easily be used with various smartphones, smart watches, and finger-based devices, and it appears to have significant potential as a convenient substitute for conventional cuff-sphygmomanometers as well as for practical application to mobile healthcare.