No abstract

The clinical demand for a device to monitor blood pressure (BP) in ambulatory scenarios with minimal use of inflation cuffs is increasing. Based on the so-called pulse wave velocity (PWV) principle, this paper introduces and evaluates a novel concept of BP monitor that can be fully integrated within a chest sensor. After a preliminary calibration, the sensor provides nonocclusive beat-by-beat estimations of mean arterial pressure (MAP) by measuring the pulse transit time (PTT) of arterial pressure pulses travelling from the ascending aorta toward the subcutaneous vasculature of the chest. In a cohort of 15 healthy male subjects, a total of 462 simultaneous readings consisting of reference MAP and chest PTT were acquired. Each subject was recorded at three different days: D, D+3, and D+14. Overall, the implemented protocol induced MAP values to range from 80 ± 6 mmHg in baseline, to 107 ± 9 mmHg during isometric handgrip maneuvers. Agreement between reference and chest-sensor MAP values was tested by using intraclass correlation coefficient (ICC = 0.78) and Bland-Altman analysis (mean error = 0.7 mmHg, standard deviation = 5.1 mmHg). The cumulative percentage of MAP values provided by the chest sensor falling within a range of ±5 mmHg compared to reference MAP readings was of 70%, within ±10 mmHg was of 91%, and within ±15 mmHg was of 98%. These results point at the fact that the chest sensor complies with the British Hypertension Society requirements of Grade A BP monitors, when applied to MAP readings. Grade A performance was maintained even two weeks after having performed the initial subject-dependent calibration. In conclusion, this paper introduces a sensor and a calibration strategy to perform MAP measurements at the chest. The encouraging performance of the presented technique paves the way toward an ambulatory compliant, continuous, and nonocclusive BP monitoring system.

POI was frequent in the present study. Overall compliance to the ERAS protocol and minimally invasive surgery helped to prevent POI, which was significantly correlated with medical complications.

No abstract

Lung and cardiovascular monitoring applications of electrical impedance tomography (EIT) require localization of relevant functional structures or organs of interest within the reconstructed images. We describe an algorithm for automatic detection of heart and lung regions in a time series of EIT images. Using EIT reconstruction based on anatomical models, candidate regions are identified in the frequency domain and image-based classification techniques applied. The algorithm was validated on a set of simultaneously recorded EIT and CT data in pigs. In all cases, identified regions in EIT images corresponded to those manually segmented in the matched CT image. Results demonstrate the ability of EIT technology to reconstruct relevant impedance changes at their anatomical locations, provided that information about the thoracic boundary shape (and electrode positions) are used for reconstruction.