An innovative multiparametric wearable system for monitoring cardiorespiratory parameters in a pregnant woman and detecting fetal movements

The assessment of cardiorespiratory fitness may be useful in different scenarios, such as to assess patients’ health, athletes’ and workers’ status, and performances. Among others, heart rate (HR) and respiratory rate (RR) are very informative cardiorespiratory parameters. Therefore, their continuous monitoring may be beneficial in the abovementioned scenarios. In addition, the knowledge of these two parameters may be useful during a physiological woman condition: pregnancy. In this condition, it may also be useful to monitor fetal movements since it can be considered an important physiological indicator to assess the baby’s health. Many solutions have been proposed to monitor either HR and RR or fetal movements, but the literature and market lack an integrated solution able to monitor both the HR and RR of a pregnant woman and fetal movements.In this paper, we proposed a multiparametric wearable solution that can monitor both a pregnant woman’s physiological parameters (i.e., HR and RR) and detect fetal movements. The system is based on the use of optical sensors (i.e., fiber Bragg grating sensors) sensitive to strain. The high performance of the system allows for detecting the chest wall movements caused by both breathing and heart beating of the pregnant woman and by the fetal movements. The encapsulation of the sensor within a polymeric mask allowed for improving the system sensitivity to movement and the comfort perceived by the wearer due to the skin-like mechanical characteristics of the polymer.The proposed system has been assessed on a single pregnant woman in terms of capability to monitor HR and RR of the woman and fetal movements. The results were promising: the system coupled with specific bespoke algorithms allows the estimation of both mother’s HR and RR and counting fetal movements. This solution may be considered a first effort to face a challenging task by using a wearable multiparametric system based on a single sensing unit.