Machine learning techniques in adaptive and personalized systems for health and wellness

O Oyebode, J Fowles, D Steeves… - International Journal of …, 2023 - Taylor & Francis
Traditional health systems mostly rely on rules created by experts to offer adaptive
interventions to patients. However, with recent advances in artificial intelligence (AI) and …

Ontology-based physical exercise recommender system for underweight using ontology and semantic web rule language

CL Juliant, ZKA Baizal… - Journal of Information …, 2023 - ejurnal.seminar-id.com
Inactive lifestyles and unhealthy diets are often the result of people's busy lives. because of
these bad habits, many people are underweight. diet and lack of physical activity are factors …

Klasifikasi Physical Activity Berbasis Sensor Accelorometer, Gyroscope, dan Gravity menggunakan Algoritma Multi-class Ensemble GradientBoost

F Aziz, S Usman, J Jeffry - Jurnal Media …, 2021 - ejurnal.stmik-budidarma.ac.id
Abstrak− Generasi smartphone saat ini semakin canggih dengan dilengkapi beberapa
sensor seperti accelerometer, gravity sensor, dan gyroscope yang dapat digunakan untuk …

Device-Free Fine-Grained Dining Activity Sensing

MG Moghaddam, AAN Shirehjini… - 2023 IEEE Sensors …, 2023 - ieeexplore.ieee.org
Device-free human activity recognition has become a topic of much interest in recent years.
While there is much effort into course-grained human activity recognition, the recognition of …

[PDF][PDF] Combined CNN-LSTM Deep Learning Algorithms for Recognizing Human Physical Activities in Large and Distributed Manners: A Recommendation System

A Ellouze, N Kadri, A Alaerjan… - Computers, Materials & …, 2024 - researchgate.net
Recognizing human activity (HAR) from data in a smartphone sensor plays an important role
in the field of health to prevent chronic diseases. Daily and weekly physical activities are …

Micro-Behavioral Accidental Click Detection System for Preventing Slip-Based Human Error

A Almehmadi - Sensors, 2021 - mdpi.com
Accidentally clicking on a link is a type of human error known as a slip in which a user
unintentionally performs an unintended task. The risk magnitude is the probability of …

Review paper of human activity recognition using smartphone

S Porwal, S Singh, N Yadav… - 2021 5th International …, 2021 - ieeexplore.ieee.org
Human recogntion technologies are gaining significant research attention, where the model
can be trained to be more precise to recognize the poses performed by objects. Activity …

A survey on personalized health recommender systems for diverse healthcare applications

D Roy, M Dutta - 2023 4th International Conference on …, 2023 - ieeexplore.ieee.org
Health recommender systems are computer algorithms designed to suggest personalized
health information to individuals based on their unique needs and preferences. These …

MACHINE LEARNING MODELLING BASED ON SMARTPHONE SENSOR DATA OF HUMAN ACTIVITY RECOGNITION.

R Husain, R Khan, RK Tyagi - I-Manager's Journal on …, 2023 - search.ebscohost.com
Smartphone sensors produce high-dimensional feature vectors that can be utilized to
recognize different human activities. However, the contribution of each vector in the …

A User-Centric approach for Personalization based on Human Activity Recognition

DG Boucharas, C Androutsos… - 2022 44th Annual …, 2022 - ieeexplore.ieee.org
The objective of this work focuses on multiple independent user profiles that capture
behavioral, emotional, medical, and physical patterns in the working and living environment …