AIMC Topic: Smartphone

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Deep Learning-Based Positioning of Visually Impaired People in Indoor Environments.

Sensors (Basel, Switzerland)
Wayfinding and navigation can present substantial challenges to visually impaired (VI) people. Some of the significant aspects of these challenges arise from the difficulty of knowing the location of a moving person with enough accuracy. Positioning ...

Predicting the first smoking lapse during a quit attempt: A machine learning approach.

Drug and alcohol dependence
BACKGROUND: Just-in-time adaptive interventions (JITAI) aim to prevent smoking lapse using tailored support delivered via mobile technology in the moments when it is most needed. Effective smoking cessation JITAI rely on the development of accurate d...

Artificial intelligence interventions focused on opioid use disorders: A review of the gray literature.

The American journal of drug and alcohol abuse
BACKGROUND: With the artificial intelligence (AI) paradigm shift comes momentum toward the development and scale-up of novel AI interventions to aid in opioid use disorder (OUD) care, in the identification of overdose risk, and in the reversal of ove...

Using Machine Learning and Smartphone and Smartwatch Data to Detect Emotional States and Transitions: Exploratory Study.

JMIR mHealth and uHealth
BACKGROUND: Emotional state in everyday life is an essential indicator of health and well-being. However, daily assessment of emotional states largely depends on active self-reports, which are often inconvenient and prone to incomplete information. A...

Machine-Learning Analysis of Voice Samples Recorded through Smartphones: The Combined Effect of Ageing and Gender.

Sensors (Basel, Switzerland)
BACKGROUND: Experimental studies using qualitative or quantitative analysis have demonstrated that the human voice progressively worsens with ageing. These studies, however, have mostly focused on specific voice features without examining their dynam...

Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks.

JMIR mHealth and uHealth
BACKGROUND: Schizophrenia spectrum disorders (SSDs) are chronic conditions, but the severity of symptomatic experiences and functional impairments vacillate over the course of illness. Developing unobtrusive remote monitoring systems to detect early ...

Toward automated severe pharyngitis detection with smartphone camera using deep learning networks.

Computers in biology and medicine
PURPOSE: Severe pharyngitis is frequently associated with inflammations caused by streptococcal pharyngitis, which can cause immune-mediated and post-infectious complications. The recent global pandemic of coronavirus disease (COVID-19) encourages th...

Using machine learning for real-time BAC estimation from a new-generation transdermal biosensor in the laboratory.

Drug and alcohol dependence
BACKGROUND: Transdermal biosensors offer a noninvasive, low-cost technology for the assessment of alcohol consumption with broad potential applications in addiction science. Older-generation transdermal devices feature bulky designs and sparse sampli...