Assessing blood pressure unobtrusively by smart chair

We developed a smart chair with unobtrusive sensors that measure functional-health parameters of a person sitting on the chair. Capacitive sensors are placed in the chair's backrest and seat, while the armrests support a combination of U-shaped electrodes and incorporated photoplethysmographic (PPG) sensors for synchronous electrocardiographic (ECG) and PPG measurements. In a set of experiments with 11 young males, the two types of signals were acquired. Time distances were estimated between the ECG R-wave peaks and the PPG foots as detected by our heartbeat search, yielding the so called pulse transit times (PTTs). The experiments were conducted in two phases: the first one at rest and the second one after a minute of intensive squats. Referential systolic and diastolic blood pressures were taken just before every trial by a Critikon Dinamap Pro 300 sphygmomanometric device. Our goal was to model the relationship between blood pressure and estimated PTTs in both experimental phases. The obtained linear models revealed an interesting observation. Subjects reacted in two different physiological ways; 6 out of 11 participants conformed to a different model as the other 5 did. The main difference is the rate of decrease of either systolic or diastolic pressure per 1-ms change of the PTT.

[1]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[2]  Damjan Zazula,et al.  Short-Term Photoplethysmography Embedded in Household Appliances , 2015 .

[3]  Devin B. McCombie,et al.  Motion based adaptive calibration of pulse transit time measurements to arterial blood pressure for an autonomous, wearable blood pressure monitor , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  Jesús Lázaro,et al.  Pulse transit time and pulse width as potential measure for estimating beat-to-beat systolic and diastolic blood pressure , 2013, Computing in Cardiology 2013.

[5]  Qiao Zhang,et al.  Noninvasive cuffless blood pressure estimation using pulse transit time and Hilbert-Huang transform , 2013, Comput. Electr. Eng..

[6]  Sokwoo Rhee,et al.  Design and analysis of artifact-resistive finger photoplethysmographic sensors for vital sign monitoring , 2000 .

[7]  Yuan-Ting Zhang,et al.  Theoretical Study on the Effect of Sensor Contact Force on Pulse Transit Time , 2007, IEEE Transactions on Biomedical Engineering.

[8]  B. D. Zislin,et al.  The history of oximetry , 2006, Meditsinskaia tekhnika.

[9]  A. Patzak,et al.  Continuous blood pressure measurement by using the pulse transit time: comparison to a cuff-based method , 2011, European Journal of Applied Physiology.

[10]  Janis Spigulis,et al.  Micro-circulation of skin blood: optical monitoring by advanced photoplethysmography techniques , 2003, SPIE Microtechnologies.