Results 41 to 50 of about 7,011 (253)

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

Arthritis Care &Research, EarlyView.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah, Melanie Morris, Cristina Daraban, Sophia Johnson, Susan L. Murphy   +4 more
wiley   +1 more source

Designing Mindfulness Conversational Agents for People With Early-Stage Dementia and Their Caregivers: Thematic Analysis of Expert and User Perspectives

JMIR Aging, 2022
BackgroundThe number of people with dementia is expected to grow worldwide. Among the ways to support both persons with early-stage dementia and their caregivers (dyads), researchers are studying mindfulness interventions. However,
Cassandra E L Seah, Zheyuan Zhang, Sijin Sun, Esther Wiskerke, Sarah Daniels, Talya Porat, Rafael A Calvo   +6 more
doaj   +1 more source

Conversational Agents for Health and Wellbeing [PDF]

Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020
Conversational agents have increasingly been deployed in healthcare applications. However, significant challenges remain in developing this technology. Recent research in this area has highlighted that: i) patient safety was rarely evaluated; ii) health outcomes were poorly measured, and iii) no standardised evaluation methods were employed.
Ahmet Baki Kocaballi, Juan C. Quiroz, Liliana Laranjo, Dana Rezazadegan, Rafal Kocielnik, Leigh Clark, Q. Vera Liao, Sun Young Park, Robert J. Moore, Adam S. Miner   +9 more
openaire   +1 more source

An All‐Textile, Mechano‐Capacitive Subtle Movement Sensor

Advanced Functional Materials, EarlyView.
A robust all‐textile capacitive sensor is introduced for measuring subtle body movements without long‐term degradation. By separating mechanical deformation from electrical sensing elements, accuracy, responsiveness, and durability are improved. Simple fabrication methods are presented, electrode effects are analyzed, and performance is validated ...
Easa AliAbbasi, Rachel Freire, Valentin Martinez‐Missir, Vineetha Rallabandi, Paul Strohmeier   +4 more
wiley   +1 more source

Developing multimodal conversational agents for an enhanced e-learning experience

Advances in Distributed Computing and Artificial Intelligence Journal, 2014
Conversational agents have become a strong alternative to enhance educational systems with intelligent communicative capabilities, provide motivation and engagement, and increment significant learning and helping in the acquisition of meta-cognitive ...
David GRIOL, Jose Manuel MOLINA, Araceli SANCHÍS DE MIGUEL   +2 more
doaj   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

Advanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

A Model-Driven Approach Employing DSL and Generation Templates to Accelerate the Development of Conversational Agents for Smart Tourism

IEEE Access
Conversational agents are intelligent, ubiquitous software applications widely used across various sectors, such as commerce, tourism, and more. Their key benefits include automating tasks, improving customer service, and ensuring service availability ...
Charaf Ouaddi, Lamya Benaddi, Adnane Souha, Hamza Abdelmalek, Abdeslam Jakimi, Rachid Saadane   +5 more
doaj   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source