Machine learning for engineering design toward smart customization: A systematic review
In today's manufacturing industry, companies are striving to provide customized products to
maintain competitiveness. The challenge of design customization lies in the company's …
maintain competitiveness. The challenge of design customization lies in the company's …
[HTML][HTML] Digital phenotyping of mental health using multimodal sensing of multiple situations of interest: A systematic literature review
Many studies have used Digital Phenotyping of Mental Health (DPMH) to complement
classic methods of mental health assessment and monitoring. This research area proposes …
classic methods of mental health assessment and monitoring. This research area proposes …
Mental-llm: Leveraging large language models for mental health prediction via online text data
Advances in large language models (LLMs) have empowered a variety of applications.
However, there is still a significant gap in research when it comes to understanding and …
However, there is still a significant gap in research when it comes to understanding and …
Xair: A framework of explainable ai in augmented reality
Explainable AI (XAI) has established itself as an important component of AI-driven
interactive systems. With Augmented Reality (AR) becoming more integrated in daily lives …
interactive systems. With Augmented Reality (AR) becoming more integrated in daily lives …
GLOBEM dataset: multi-year datasets for longitudinal human behavior modeling generalization
Recent research has demonstrated the capability of behavior signals captured by
smartphones and wearables for longitudinal behavior modeling. However, there is a lack of …
smartphones and wearables for longitudinal behavior modeling. However, there is a lack of …
Generalization and personalization of mobile sensing-based mood inference models: an analysis of college students in eight countries
Mood inference with mobile sensing data has been studied in ubicomp literature over the
last decade. This inference enables context-aware and personalized user experiences in …
last decade. This inference enables context-aware and personalized user experiences in …
[HTML][HTML] Predicting depression in adolescents using mobile and wearable sensors: multimodal machine learning–based exploratory study
Background: Depression levels in adolescents have trended upward over the past several
years. According to a 2020 survey by the National Survey on Drug Use and Health, 4.1 …
years. According to a 2020 survey by the National Survey on Drug Use and Health, 4.1 …
Towards ubiquitous personalized music recommendation with smart bracelets
Nowadays, recommender systems play an increasingly important role in the music scenario.
Generally, music preferences are related to internal and external conditions. For example …
Generally, music preferences are related to internal and external conditions. For example …
A review of detection techniques for depression and bipolar disorder
D Highland, G Zhou - Smart Health, 2022 - Elsevier
Depression and bipolar disorder are mood disorders affecting millions of people worldwide
that can have severe impacts on one's quality of life. Our ability to detect these illnesses is …
that can have severe impacts on one's quality of life. Our ability to detect these illnesses is …
Detecting social contexts from mobile sensing indicators in virtual interactions with socially anxious individuals
Mobile sensing is a ubiquitous and useful tool to make inferences about individuals' mental
health based on physiology and behavior patterns. Along with sensing features directly …
health based on physiology and behavior patterns. Along with sensing features directly …