Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...

Abstract: In this paper, a new class of orthogonal circulant matrices built from deterministic sequences is proposed for convolution-based compressed sensing (CS). In contrast to random convolution, ...

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UD's Applied Sensing Laboratory is a center for applied remote sensing research, with a particular focus on the research and development of signal and image processing, computer vision, and pattern ...

Six studies (67%) showed that mobile sensing data could predict depressive episodes or symptom severity. Four studies reported the predictive accuracy for depression using mobile sensing data from ...

Small-molecule biosensors are critical tools for monitoring environments, controlling cellular behavior, and enabling new biotechnologies; yet, they remain challenging to design. The plant hormone ...