Mar 21, 2019 · We develop a machine learning framework for fall detection and daily living activity recognition. We use acceleration and angular velocity data from two public ...
We develop a machine learning framework for fall detection and daily living activity recognition. We use acceleration and angular velocity data from two public ...
accepted approach by the researchers on this topic. In this paper, we propose a machine learning framework for fall detection and activity recognition. Our ...
A Machine Learning Approach for Fall Detection and Daily Activity Recognition using KNN and QSVM Algorithm. Author : Nagama B. Deshmukh and Chandu R. Barde.
A Machine Learning Approach for Fall Detection and Daily Living Activity Recognition. Chelli, Ali; ;; Patzold, Matthias. Abstract. Publication: IEEE Access. Pub ...
Aug 15, 2020 · Abstract: Elder people are increasing all over the world as a result certain fall occur in their daily life. This fall lead to several.
Jul 13, 2022 · This study focuses on the application of classification methods for monitoring devices to detect fall/nonfall movements of farmworkers.
This article discusses the development of a machine learning framework for fall detection and daily activity recognition using data from wearable sensors.
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Jul 26, 2023 · We investigated different machine learning models for the near-fall detection including support vector machines, AdaBoost, convolutional neural networks, and ...
May 23, 2024 · Development of an efficient machine learning algorithm using accelerometer data from wearable devices to detect falls in the elderly.