Human Activity Recognition using Machine Learning
نویسندگان
چکیده
منابع مشابه
Machine Learning for Activity Recognition
This paper surveys the activity recognition task from a machine learning perspective. I give a definition of this problem, and I classify different activity recognition problems into two categories. I show the activities can be hierarchical, and based on such hierarchies I synthesize a language to describe activities. I give a general criteria set to evaluate activity recognition methods. I sum...
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Human activity detection has seen a tremendous growth in the last decade playing a major role in the field of pervasive computing. This emerging popularity can be attributed to its myriad of reallife applications primarily dealing with human-centric problems like healthcare and eldercare. Many research attempts with data mining and machine learning techniques have been undergoing to accurately ...
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High-level human activity recognition is an important method for the automatic event detection and recognition application, such as, surveillance system and patient monitoring system. In this paper, we propose a human activity recognition method based on FSM model. The basic actions with their properties for each person in the interested area are extracted and calculated. The action stream with...
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Human Activity Recognition has a lot of applications such as patient monitoring, rehabilitation and assisting disabled. When mobile sensors are hold to the subject’s body, they permit continuous monitoring of numerous signals patterns from the phone. This has appealing use in healthcare applications. In order to improve the state of global healthcare, numeroushealthcare devices have been introd...
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Human activity recognition aims at capturing current state of human in the immediate environment. This article poses a novel approach to predict the human activity by exploiting the data collected from smartphone’s triaxial accelerometer sensor. This approach employs a time domain wave analysis on the collected data and extracts relevant features that intuitively distinguish various activities ...
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ژورنال
عنوان ژورنال: International Journal for Research in Applied Science and Engineering Technology
سال: 2021
ISSN: 2321-9653
DOI: 10.22214/ijraset.2021.35694