Human Activity Recognition using Inertial, Physiological and Environmental Sensors: a Comprehensive Survey
In the last decade, Human Activity Recognition (HAR) has become a vibrant research area, especially due to the spread of electronic devices such as smartphones, smartwatches and video cameras present in our daily lives. In addition, the advance of deep learning and other machine learning algorithms has allowed researchers to use HAR in various domains including sports, health and well-being applications. For example, HAR is considered as one of the most promising assistive technology tools to support elderly's daily life by monitoring their cognitive and physical function through daily activities. This survey focuses on critical role of machine learning in developing HAR applications based on inertial sensors in conjunction with physiological and environmental sensors.
Code (0)
등록된 구현이 없습니다.
Tasks
Activity RecognitionBIG-bench Machine LearningHuman Activity RecognitionSimilar Papers 제목 키워드 기반
Classifying Human Activities with Inertial Sensors: A Machine Learning Approach
Human Activity Recognition (HAR) is an ongoing research topic. It has applications in medical support, sports, fitness, social networking, human-computer interfaces, senior care, entertainment, surveillance, and the list…
Activity RecognitionBIG-bench Machine LearningHuman Activity RecognitionMukhtasir-Khail-Net: An Ultra-Efficient Convolutional Neural Network for Sports Activity Recognition with Wearable Inertial Sensors
The current prevalent approach of the Internet of Health and Medical Things entails proactively preventing disease onset through routine monitoring of individuals’ physical activities, making Human Activity Recognition (…
Activity RecognitionHuman Activity RecognitionSports Activity RecognitionDomain Adaptation for Inertial Measurement Unit-based Human Activity Recognition: A Survey
Machine learning-based wearable human activity recognition (WHAR) models enable the development of various smart and connected community applications such as sleep pattern monitoring, medication reminders, cognitive heal…
Activity RecognitionDomain AdaptationHuman Activity RecognitionSports Analytics+1HARMES: A Multi-Modal Dataset for Wearable Human Activity Recognition with Motion, Environmental Sensing and Sound
With each sensing modality exhibiting inherent strengths and limitations, multi-modal approaches for wearable Human Activity Recognition (HAR) are becoming increasingly relevant -- particularly for recognizing Activities…
Human Activity RecognitionTS-MoCo: Time-Series Momentum Contrast for Self-Supervised Physiological Representation Learning
Limited availability of labeled physiological data often prohibits the use of powerful supervised deep learning models in the biomedical machine intelligence domain. We approach this problem and propose a novel encoding …
Activity RecognitionClassificationEmotion RecognitionHuman Activity Recognition+3