Latest AI and machine learning research in exercise & fitness for healthcare professionals.
Machine learning approaches, such as contextual multi-armed bandit (cMAB) algorithms, offer a promising strategy to reduce sedentary behavior by delivering personalized interventions to encourage physical activity. However, cMAB algorithms typically require large participant samples to learn effectively and may overlook key psychological factors that are not explicitly encoded in the model. In t...
Minoritised ethnic people are marginalised in society, and therefore at a higher risk of adverse online harms, including those arising from the loss of security and privacy of personal data. Despite this, there has been very little research focused on minoritised ethnic people's security and privacy concerns, attitudes, and behaviours. In this work, we provide the results of one of the first stu...
Multi-agent AI systems, which simulate diverse instructional roles such as teachers and peers, offer new possibilities for personalized and interact...
With the increasing awareness of health and the growing desire for aesthetic physique, fitness has become a prevailing trend. However, the potential...
We present pyCub, an open-source physics-based simulation of the humanoid robot iCub, along with exercises to teach students the basics of humanoid ...
Mental health disorders like depression, anxiety, and stress (DAS) are rising globally. Understanding how diet and lifestyle influence these condition...
BACKGROUND: Wearable fitness trackers generate extensive physiological and activity data, offering potential to monitor health and predict outcomes. M...
Driven by the progress in efficient embedded processing, there is an accelerating trend toward running machine learning models directly on wearable Br...
Osteoporosis (OP) affects approximately 18Â % of the global population, with osteoporosis-associated fractures impacting up to 37 million people annual...
Reflective writing is widely used in health sciences education, but overreliance on generative artificial intelligence (GenAI) could undermine the ref...
The prevalence of hearing loss (HL) has emerged as an escalating public health concern globally. The objective of this study was to leverage data from...
OBJECTIVES: This study compares the effects of an artificial intelligence app-based exercise program with group exercise therapy on pain intensity and...
The lack of physical activity presents a significant public health concern, particularly for individuals with disabilities who face heightened risks d...
BACKGROUND: Heart failure (HF) is a highly prevalent condition characterized by exercise intolerance, an important metric for ambulatory prognosticati...
Diabetes mellitus, a chronic metabolic disorder, is characterized by high blood glucose levels. External insulin administration, along with diet and e...
The continuous-flow aerobic granular sludge-membrane bioreactor (AGS-MBR) system represents an efficient and sustainable technology for wastewater tre...
Group conversations are valuable for second language (L2) learners as they provide opportunities to practice listening and speaking, exercise comple...
In recent years, with the spread and popularization of health knowledge, more and more people have begun to participate in fitness exercises to streng...
This paper assesses the presentation of Gradient Boosting Regression (GBR), Ridge Regression (RR), and Particle Swarm Optimization (PSO) models in imp...
Machine learning technology has been extensively applied in the medical field, particularly in the context of disease prediction and patient rehabilit...