VitalSeer: The development of a contactless sensing technology based on a user-centric data-driven clinical approach.

The COVID-19 pandemic presented challenges to the healthcare system while catalyzing the adoption of virtual care. The need for remote assessment and real-time monitoring of physiological vital signs has driven towards a need for virtual care solutions. This paper presents the outcome of a multidisciplinary collaboration to ensure clinical usability of a remote contactless sensing technology, VitalSeer, and to help close gaps between emerging technologies and clinical practice. The paper describes the user-centric data-driven clinical approach to address the needs as identified by clinical experts through the iterative and agile development cycle. It highlights findings from preliminary studies to validate proof-of-concept VitalSeer's adoptability, accessibility and usability. The studies on volunteers demonstrated the accuracy of VitalSeer's heart rate model at a low MAE of 0.74 (bpm) and a RMSE of 1.2 bpm, below the threshold of clinical grade contact-based sensors. The paper concludes with a discussion on the technology implications in emergency medicine and community care.

Automatic evaluation of vessel diameter variation from 2D X-ray angiography.

PURPOSE: Early detection of blood vessel pathologies can be made through the evaluation of functional and structural abnormalities in the arteries, including the arterial distensibility measure. We propose a feasibility study on computing arterial distensibility automatically from monoplane 2D X-ray sequences for both small arteries (such as coronary arteries) and larger arteries (such as the aorta). METHODS: To compute the distensibility measure, three steps were developed: First, the segment of an artery is extracted using our graph-based segmentation method. Then, the same segment is tracked in the moving sequence using our spatio-temporal segmentation method: the Temporal Vessel Walker. Finally, the diameter of the artery is measured automatically at each frame of the sequence based on the segmentation results. RESULTS: The method was evaluated using one simulated sequence and 4 patients' angiograms depicting the coronary arteries and three depicting the ascending aorta. Results of the simulated sequence achieved a Dice index of 98%, with a mean squared error in diameter measurement of [Formula: see text] mm. Results obtained from patients' X-ray sequences are consistent with manual assessment of the diameter by experts. CONCLUSIONS: The proposed method measures changes in diameter of a specific segment of a blood vessel during the cardiac sequence, automatically based on monoplane 2D X-ray sequence. Such information might become a key to help physicians in the detection of variations of arterial stiffness associated with early stages of various vasculopathies.

A graph-based approach for spatio-temporal segmentation of coronary arteries in X-ray angiographic sequences.

The segmentation and tracking of coronary arteries (CAs) are critical steps for the computation of biophysical measurements in pediatric interventional cardiology. In the literature, most methods are focused on either segmenting the vessel lumen or on tracking the vessel centerline. However, they do not simultaneously combine the segmentation and tracking of a specific CA. This paper introduces a novel algorithm for CA segmentation and tracking from 2D X-ray angiography sequences. The proposed algorithm is based on the Temporal Vessel Walker (TVW) segmentation method, which combines graph-based formulation and temporal priors. Moreover, superpixel groups are used by TVW as image primitives to ensure a better extraction of the CA. The proposed algorithm, TVW with superpixels (SP-TVW), returns an accurate result to segment and track the artery along the angiogram. Quantitative results over 12 sequences of young patients show the accuracy of the proposed framework. The results return a mean recall of 84% in the dataset. In addition, the proposed method returned a Dice index of 70% in segmenting and tracking right coronary arteries and circumflex arteries. The performance of the proposed method surpasses the existing polyline method in tracking the centerline of CA with a more precise localization of the centerline, resulting in a smaller distance error of 0.23mm compared to 0.94mm.