Digital just-in-time adaptive interventions can reduce binge-drinking events (BDEs; consuming ≥4 drinks for women and ≥5 men per occasion) in young adults but need to be optimized timing content. Delivering support messages the hours prior BDEs could improve intervention impact.We aimed determine feasibility of developing a machine learning (ML) model accurately predict future, that is, same-day 1 6 BDEs, using smartphone sensor data identify most informative phone features associated with...

Low cost virtual reality (VR) headsets powered by smartphones are becoming ubiquitous. Their unique position on the user's face opens interesting opportunities for interactive sensing. In this paper, we describe EyeSpyVR, a software-only eye sensing approach smartphone-based VR, which uses phone's front facing camera as sensor and its display passive illuminator. Our proof-of-concept system, using commodity Apple iPhone, enables four modalities: detecting when VR head set is worn, blinks,...

Ocular biometrics in the visible spectrum has emerged as an area of significant research activity. In this paper, we propose two convolution-based models for verifying a pair periocular images containing iris, and compare approaches amongst each other well with baseline model. first approach, perform deep learning unsupervised manner using stacked convolutional architecture, external learned a-priori on facial data, top model applied provided apply different score fusion models. second again...

Background Acute marijuana intoxication can impair motor skills and cognitive functions such as attention information processing. However, traditional tests, like blood, urine, saliva, fail to accurately detect acute in real time. Objective This study aims explore whether integrating smartphone-based sensors with readily accessible wearable activity trackers, Fitbit, enhance the detection of naturalistic settings. No previous research has investigated effectiveness passive sensing...

Facial expressions are an integral part of human cognition and communication, can be applied in various real life applications. A vital precursor to accurate expression recognition is feature extraction. In this paper, we propose SenTion: framework for sensing facial expressions. We a novel person independent scale invariant method extracting Inter Vector Angles (IVA) as geometric features, which proves robust reliable across databases. SenTion employs combining (IVA's) appearance based...

This paper introduces {it EyamKayo}, a first-of-its-kind interactive CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart), using eye gaze facial expression based human interactions, better distinguish humans from software robots. Our system generates sequence of instructions, asking the user follow controlled points, generate expressions. We evaluate comfort usability, validate usability tests.

As we build towards developing interactive systems that can recognize human emotional states and respond to individual needs more intuitively empathetically in personalized context-aware computing time. This is especially important regarding mental health support, with a rising need for immediate, non-intrusive help tailored each individual. Individual the complex nature of emotions call novel approaches beyond conventional proactive reactive-based chatbot approaches. In this position paper,...

Depression, a prevalent and complex mental health issue affecting millions worldwide, presents significant challenges for detection monitoring. While facial expressions have shown promise in laboratory settings identifying depression, their potential real-world applications remains largely unexplored due to the difficulties developing efficient mobile systems. In this study, we aim introduce FacePsy, an open-source sensing system designed capture affective inferences by analyzing...

Depression, a prevalent and complex mental health issue affecting millions worldwide, presents significant challenges for detection monitoring. While facial expressions have shown promise in laboratory settings identifying depression, their potential real-world applications remains largely unexplored due to the difficulties developing efficient mobile systems. In this study, we aim introduce FacePsy, an open-source sensing system designed capture affective inferences by analyzing...

For handheld smartphone AR interactions, bandwidth is a critical constraint. Streaming techniques have been developed to provide seamless and high-quality user experience despite these challenges. To optimize streaming performance in smartphone-based AR, accurate prediction of the user's field view essential. This allows system prioritize loading digital content that likely engage with, enhancing overall interactivity immersion experience. In this paper, we present MotionTrace, method for...

<sec> <title>BACKGROUND</title> Acute marijuana intoxication can impair motor skills and cognitive functions (e.g., attention, information processing). However, existing tools blood, urine, saliva tests) do not accurately reflect ‘real-time’ acute intoxication. </sec> <title>OBJECTIVE</title> Considering the absence of screening to detect impairment-related harms, our objective is examine whether integration smartphone-based sensors with a wearable activity tracker (Fitbit), as more...

<sec> <title>BACKGROUND</title> Digital just-in-time adaptive interventions can reduce binge-drinking events (BDEs; consuming ≥4 drinks for women and ≥5 men per occasion) in young adults but need to be optimized timing content. Delivering support messages the hours prior BDEs could improve intervention impact. </sec> <title>OBJECTIVE</title> We aimed determine feasibility of developing a machine learning (ML) model accurately predict &lt;i&gt;future&lt;/i&gt;, that is, &lt;i&gt;same-day 1 6...