[HTML][HTML] How do context-aware artificial intelligence algorithms used in fitness recommender systems? A literature review and research agenda
P Venkatachalam, S Ray - International Journal of Information Management …, 2022 - Elsevier
Recommender Systems (RS) help the user in the decision-making process when there is a
problem of plenty or lack of information. The context-aware recommender systems (CARS) …
problem of plenty or lack of information. The context-aware recommender systems (CARS) …
Advances for indoor fitness tracking, coaching, and motivation: A review of existing technological advances
T Wang, Y Gan, SD Arena… - IEEE Systems, Man …, 2021 - ieeexplore.ieee.org
There is growing consumer demand for digital technologies that help users track, motivate,
and receive coaching for both aerobic and anaerobic activities. In this article, we provide a …
and receive coaching for both aerobic and anaerobic activities. In this article, we provide a …
Leveraging active learning and conditional mutual information to minimize data annotation in human activity recognition
A difficulty in human activity recognition (HAR) with wearable sensors is the acquisition of
large amounts of annotated data for training models using supervised learning approaches …
large amounts of annotated data for training models using supervised learning approaches …
An automatic and personalized recommendation modelling in activity eCoaching with deep learning and ontology
Electronic coaching (eCoach) facilitates goal-focused development for individuals to
optimize certain human behavior. However, the automatic generation of personalized …
optimize certain human behavior. However, the automatic generation of personalized …
Machine learning and ontology in eCoaching for personalized activity level monitoring and recommendation generation
Leading a sedentary lifestyle may cause numerous health problems. Therefore, passive
lifestyle changes should be given priority to avoid severe long-term damage. Automatic …
lifestyle changes should be given priority to avoid severe long-term damage. Automatic …
IDIoT: Towards ubiquitous identification of IoT devices through visual and inertial orientation matching during human activity
As Internet-of-Things (IoT) devices become pervasive, opportunities for new, useful services
open up. Leveraging existing devices in the environment to enhance the information …
open up. Leveraging existing devices in the environment to enhance the information …
Smart hospital emergency system: Via mobile-based requesting services
In recent years, the UK's emergency call and response has shown elements of great strain
as of today. The strain on emergency call systems estimated by a 9 million calls (including …
as of today. The strain on emergency call systems estimated by a 9 million calls (including …
IDIoT: Multimodal framework for ubiquitous identification and assignment of human-carried wearable devices
IoT (Internet of Things) devices, such as network-enabled wearables, are carried by
increasingly more people throughout daily life. Information from multiple devices can be …
increasingly more people throughout daily life. Information from multiple devices can be …
Human activity and correlated posture monitoring using earlobe-Worn wearable sensor system and deep learning algorithm
H Han, G Kim, S Choi, A Basu… - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
An approach for monitoring human activities and correlated postures using an earlobe-worn
wearable sensor and a deep learning algorithm is proposed. The herein-used miniaturized …
wearable sensor and a deep learning algorithm is proposed. The herein-used miniaturized …
AI and semantic ontology for personalized activity eCoaching in healthy lifestyle recommendations: a meta-heuristic approach
Background Automated coaches (eCoach) can help people lead a healthy lifestyle (eg,
reduction of sedentary bouts) with continuous health status monitoring and personalized …
reduction of sedentary bouts) with continuous health status monitoring and personalized …