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Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …
application areas. Since multi-sensor is defined by the presence of more than one model or …
Deep learning in human activity recognition with wearable sensors: A review on advances
Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …
tracking, wellness monitoring, and human–computer interaction, that measure and improve …
Deep learning for sensor-based human activity recognition: Overview, challenges, and opportunities
The vast proliferation of sensor devices and Internet of Things enables the applications of
sensor-based activity recognition. However, there exist substantial challenges that could …
sensor-based activity recognition. However, there exist substantial challenges that could …
A survey on wearable sensor modality centred human activity recognition in health care
Increased life expectancy coupled with declining birth rates is leading to an aging
population structure. Aging-caused changes, such as physical or cognitive decline, could …
population structure. Aging-caused changes, such as physical or cognitive decline, could …
Sensor-based datasets for human activity recognition–a systematic review of literature
The research area of ambient assisted living has led to the development of activity
recognition systems (ARS) based on human activity recognition (HAR). These systems …
recognition systems (ARS) based on human activity recognition (HAR). These systems …
The dilemma of analyzing physical activity and sedentary behavior with wrist accelerometer data: challenges and opportunities
Physical behaviors (eg, physical activity and sedentary behavior) have been the focus
among many researchers in the biomedical and behavioral science fields. The recent shift …
among many researchers in the biomedical and behavioral science fields. The recent shift …
Applied human action recognition network based on SNSP features
Recognition of human action is a daunting challenge considering action sequences'
embodied and dynamic existence. Recently designed material depth sensors and the …
embodied and dynamic existence. Recently designed material depth sensors and the …
Action recognition using interrelationships of 3D joints and frames based on angle sine relation and distance features using interrelationships
Human action recognition is still an uncertain computer vision problem, which could be
solved by a robust action descriptor. As a solution, we proposed an action recognition …
solved by a robust action descriptor. As a solution, we proposed an action recognition …
RGB-D based human action recognition using evolutionary self-adaptive extreme learning machine with knowledge-based control parameters
Abstract Human Action Recognition (HAR) has gained considerable attention due to its
various applications such as monitoring activities, robotics, visual surveillance, to name a …
various applications such as monitoring activities, robotics, visual surveillance, to name a …
Sensor Type, Axis, and Position‐Based Fusion and Feature Selection for Multimodal Human Daily Activity Recognition in Wearable Body Sensor Networks
This research addresses the challenge of recognizing human daily activities using surface
electromyography (sEMG) and wearable inertial sensors. Effective and efficient recognition …
electromyography (sEMG) and wearable inertial sensors. Effective and efficient recognition …