Towards wearable blood pressure measurement systems from biosignals: a review

Abstract

Blood pressure is the pressure by the blood to the vein wall. High blood pressure, which is called silent death, is the cause of nearly 13% of mortality all over the world. Blood pressure is not only measured in the medical environment, but the blood pressure measurement is also a need for people in their daily life. Blood pressure estimation systems with low error rates have been developed besides the new technologies and algorithms. Blood pressure measurements are differentiated as invasive blood pressure (IBP) measurement and noninvasive blood pressure (NIBP) measurement methods. Although IBP measurement provides the most accurate results, it cannot be used in daily life because it can only be performed by qualified medical staff with specialized medical equipment. NIBP measurement is based on measuring physiological signals taken from the body and producing results with decision mechanisms. Oscillometric, pulse transit time (PTT), pulse wave velocity, and feature extraction methods are mentioned in the literature as NIBP.In the oscillometric method of the sphygmomanometer, an electrocardiogram is used in PTT methods as a result of the comparison of signals such as electrocardiography, photoplethysmography, ballistocardiography, and seismocardiography.The increase in the human population and worldwide deaths due to the highly elevated blood pressure makes the need for precise measurements and technological devices more clear. Today, wearable technologies and sensors have been frequently used in the health sector. In this review article, the invasive and noninvasive blood pressure methods, including various biosignals, have been investigated and then compared with each other concerning the measurement of comfort and robust estimation.

Holter Monitörü için Elektrokardiyografi Sinyali Tabanlı Yeni Bir Kan Basıncı Hesaplama Yöntemi

“…Osilometrik dalga formları kan basıncının hesaplanmasında kullanılabilir [7], [9]. Ancak bu sinyallerin işlenmesinde ve elde edilmesinde farklı mekanizmalar gerekebilir.…”

“…Bazı çalışmalarda Fotopletismografi sinyali kullanılırken [5]- [7], diğer bir çalışmada ECG ve PPG birlikte kullanılmıştır [8]. Bazı çalışmalarda elde edilmesi zor bir süreç olan osilometrik dalga formlarıda tercih edilmektedir [7], [9]. Çalışmalarda yöntem olarak sıklıkla makine öğrenmesi ve derin öğrenme yöntemleri tercih edilmiştir [9].…”

“…Bazı çalışmalarda elde edilmesi zor bir süreç olan osilometrik dalga formlarıda tercih edilmektedir [7], [9]. Çalışmalarda yöntem olarak sıklıkla makine öğrenmesi ve derin öğrenme yöntemleri tercih edilmiştir [9]. Literatürdeki bu çalışmalar incelendiğinde mikroişlemcilere uygulanabilir uygulamalara ihtiyaç duyulmaktadır.…”

Porous Microstructure‐Assisted Flexible and Highly Sensitive Polymer Piezoresistive Pressure Sensor

“…[ 8 ] A great potential exists for their use in electronic skin (e‐skin), [ 9 ] soft robots, [ 10 ] and sensing of biosignals. [ 11 ] In addition to being flexible, such sensors are lightweight and have low cost, which make them quite viable commercially. Elastomers such as poly(‐dimethysiloxane)(PDMS) [ 12 ] and Ecoflex [ 13 ] are commonly used substrate materials for flexible pressure sensors.…”

New normal: cooperative paradigm for COVID-19 timely detection and containment using Internet of things and deep learning

“…Moreover, there are advancements in extracting images from video streams to perform various detection using YOLOv2 [12], which can provide accurate detection. We believe that the nature of the COVID spread and social impact requires multiple aspects of containment, instead of relying on single information [13]. A study in [14] proposes a fuzzy system for mortality prediction of COVID-19 and outlines risk, clinical and miscellaneous factors.…”