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A ballistocardiogram (BCG) is a versatile bio-signal that enables ambient remote monitoring of heart failure (HF) patients in a home setting, achieved through embedded sensors in the surrounding environment. Numerous methods of analysis are available for extracting physiological information using the BCG; however, most have been developed based on non-clinical subjects. While the difference between clinical and non-clinical populations are expected, quantification of the difference may serve as a useful tool. In this work, the differences in resting-state BCGs of the two cohorts in a sitting posture were quantified. An instrumented chair was used to collect the BCG from 29 healthy adults and 26 NYHA HF class I and II patients while seated without any stress test for five minutes. Five 20-second epochs per subject were used to calculate the waveform fluctuation metric at rest (WFMR). The WFMR was obtained in two steps. The ensemble average of the segmented BCG heartbeats within an epoch were calculated first. Mean square errors (MSE) between different ensemble average pairs were then retrieved. The MSEs were averaged to produce the WFMR. The comparison showed that the clinical cohort had higher fluctuation than the non-clinical population and had at least 82.2% separation, suggesting that greater errors may result when existing algorithms were used. The WFMR acts as a bridge that may enable important features, including the addition of error margins in parameter estimation and ways to devise a calibration strategy when resting-state BCG is unstable.

Effective management of neurogenic orthostatic hypotension and supine hypertension (SH-OH) due autonomic failure requires a frequent and timely adjustment of medication throughout the day to maintain the blood pressure (BP) within the normal range, i.e., an accurate depiction of BP is a key prerequisite of effective management. One of the emerging technologies that provide one’s circadian and long-term physiological status with increased usability is unobtrusive zero-effort monitoring. In this paper, a zero-effort device, a floor tile, was used to develop an unobtrusive BP monitoring technique. Namely, RJ-interval, the time between the J-peak of a ballistocardiogram and the R-peak of an electrocardiogram, was used to develop a classifier that can detect changes in systolic BP (SBP) induced by the Valsalva maneuver on healthy adults (i.e., a simulated SH-OH). A t-test was used to show statistical differences between the mean RJ-intervals of decreased SBP, baseline, and increased SBP. Following the t-test, a classifier that detected a change in SBP was developed based on a naïve Bayes classifier (NBC). The t-test showed a clear statistical difference between the mean RJ-intervals of the increased SBP, baseline, and decreased SBP. The NBC-based classifier was able to detect increased SBP with 89.3% true positive rate (TPR), 100% true negative rate (TNR), and 94% accuracy and detect decreased SBP with 92.3% TPR, 100% TNR, and 95% accuracy. The analysis showed strong potential in using the developed classifier to assist monitoring of people with SH-OH; the algorithm may be used clinically to detect a long-term trend of symptoms of SH-OH.

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Exercise imposes increased pulmonary vascular afterload based on rises in pulmonary artery (PA) wedge pressure, declines in PA compliance, and resistance‐compliance time. In health, afterload stress stabilizes during steady‐state exercise. Our objective was to examine alterations of these exercise‐associated stresses in states of pre‐ and post‐capillary pulmonary hypertension (PH). PA hemodynamics were evaluated at rest, 2 and 7 min of steady‐state exercise at moderate intensity in patients who exhibited Pre‐capillary (n = 22) and post‐capillary PH (n = 22). Patients with normal exercise hemodynamics (NOR‐HD) (n = 32) were also studied. During exercise in all groups, PA wedge pressure increased at 2 min, with no further change at 7 min. In post‐capillary PH and NOR‐HD, increases in PA diastolic pressure and diastolic pressure gradient remained stable at 2 and 7 min of exercise, while in pre‐capillary PH, both continued to increase at 7 min. The behavior of the diastolic pressure gradient was linearly related to the duration of resistance‐compliance time at rest (r2 = 0.843) and exercise (r2 = 0.760). Exercise resistance‐compliance time was longer in pre‐capillary PH associated with larger increases in diastolic pressure gradient. Conversely, resistance‐compliance time was shortest in post‐capillary PH compared to pre‐capillary PH and NOR‐HD and associated with limited increases in exercise diastolic pressure gradient. During steady‐state, modest‐intensity exercise‐specific patterns of pulmonary vascular afterload responses were observed in pre‐ and post‐capillary PH relative to NOR‐HD. Longer resistance‐compliance time related to greater increases in PA diastolic pressure and diastolic pressure gradients in pre‐capillary PH, while shorter resistance‐compliance time appeared to limit these increases in post‐capillary PH.