Genetic-fuzzy logic model for a non-invasive measurement of a stroke volume.

BACKGROUND

Despite the importance of stroke volume readings in understanding the work of the cardiovascular system in patients, its routine daily measurement outside of a hospital in the absence of special equipment presents a problem for a comprehensive assessment of the heart performance.

OBJECTIVE

The purpose of this study was to develop a new non-invasive technique for measuring a stroke volume based on the relationship between time skin warming and a blood flow.

METHODS

. Ninety two randomly selected volunteers (54 males, aged 30.1 ± 11.9 years old, and 38 females, aged 35.8 ± 12.4 years old) were recruited for this study. The time skin warming was determined by applying on the wrist above the arterial pulsation a thermoelectric cooler using the Peltier effect. During recording the participants were in the supine position. Blood pressure was measured by sphygmomanometer. Heart performance was assessed by Murata ballistocardiographic sensor, detecting displacement of the whole body during each cardiac ejection of blood. The data provided by this sensor included heart rate, respiratory rate, heart rate variability and a stroke volume. Linear, non-linear statistical regression models and fuzzy logic were used to analyse the degree of interrelation between BCG-measured stroke volume and the time skin warming.

RESULTS

Comparative analysis of results indicated that the generic-fuzzy logic model demonstrated a high level of dependency (R = 0.803) between input (participants' time skin warming, pulse pressure and age) and output (ballistocardiographic stroke volume) parameters.

CONCLUSIONS

The method described in the paper offers a simple, portable, and low-cost solution that can even be used in a home setting to measure the stroke volume. The principle of the proposed method is based on the interrelation between time skin warming and blood flow. The latter, corrected by corresponding age and pulse pressure, expresses the participant's stroke volume. Adopting the genetic-fuzzy model significantly improved the accuracy of stroke volume's measurement and made the proposed method reliable for assessing of the cardiovascular system. This daily practice technique would help healthcare provider get an early diagnosis of cardiac dysfunctions and track heart changes during stress, e.g., in sport.