scholarly journals A model sufficiency test using permutation entropy

2022 ◽  
Author(s):  
Xin Huang ◽  
Han Lin Shang ◽  
David Pitt
Keyword(s):  
Permutation Entropy

scholarly journals Employing entropy measures to identify visitors in multi-occupancy environments

2020 ◽  
Author(s):  
Aadel Howedi ◽  
Ahmad Lotfi ◽  
Amir Pourabdollah
Keyword(s):  
Home Environment ◽  
Daily Living ◽  
Wearable Sensors ◽  
Permutation Entropy ◽  
Care Workers ◽  
Entropy Measures ◽  
Novel Method ◽  
High Degree ◽  
Motion Detectors ◽  
To Receive

AbstractHuman activity recognition (HAR) is used to support older adults to live independently in their own homes. Once activities of daily living (ADL) are recognised, gathered information will be used to identify abnormalities in comparison with the routine activities. Ambient sensors, including occupancy sensors and door entry sensors, are often used to monitor and identify different activities. Most of the current research in HAR focuses on a single-occupant environment when only one person is monitored, and their activities are categorised. The assumption that home environments are occupied by one person all the time is often not true. It is common for a resident to receive visits from family members or health care workers, representing a multi-occupancy environment. Entropy analysis is an established method for irregularity detection in many applications; however, it has been rarely applied in the context of ADL and HAR. In this paper, a novel method based on different entropy measures, including Shannon Entropy, Permutation Entropy, and Multiscale-Permutation Entropy, is employed to investigate the effectiveness of these entropy measures in identifying visitors in a home environment. This research aims to investigate whether entropy measures can be utilised to identify a visitor in a home environment, solely based on the information collected from motion detectors [e.g., passive infra-red] and door entry sensors. The entropy measures are tested and evaluated based on a dataset gathered from a real home environment. Experimental results are presented to show the effectiveness of entropy measures to identify visitors and the time of their visits without the need for employing extra wearable sensors to tag the visitors. The results obtained from the experiments show that the proposed entropy measures could be used to detect and identify a visitor in a home environment with a high degree of accuracy.

On the Permutation Entropy Bayesian Estimation

2021 ◽  
pp. 105779
Author(s):  
Fernando E. Pose ◽  
Lucas Bautista ◽  
Franco Gianmuso ◽  
Francisco O. Redelico
Keyword(s):  
Bayesian Estimation ◽  
Permutation Entropy

Complexity of EEG Dynamics for Early Diagnosis of Alzheimer Disease Using Permutation Entropy Neuromarker

2021 ◽  
pp. 106116
Author(s):  
Mesut Şeker ◽  
Yağmur Özbek ◽  
Görsev Yener ◽  
Mehmet Siraç Özerdem
Keyword(s):  
Alzheimer Disease ◽  
Early Diagnosis ◽  
Permutation Entropy
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