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Human Activities Recognition Based on Neuro-Fuzzy Finite State Machine

School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham NG11 8NS, UK
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Technologies 2018, 6(4), 110; https://doi.org/10.3390/technologies6040110
Received: 7 November 2018 / Revised: 19 November 2018 / Accepted: 22 November 2018 / Published: 26 November 2018
(This article belongs to the Special Issue The PErvasive Technologies Related to Assistive Environments (PETRA))
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Abstract

Human activity recognition and modelling comprise an area of research interest that has been tackled by many researchers. The application of different machine learning techniques including regression analysis, deep learning neural networks, and fuzzy rule-based models has already been investigated. In this paper, a novel method based on Fuzzy Finite State Machine (FFSM) integrated with the learning capabilities of Neural Networks (NNs) is proposed to represent human activities in an intelligent environment. The proposed approach, called Neuro-Fuzzy Finite State Machine (N-FFSM), is able to learn the parameters of a rule-based fuzzy system, which processes the numerical input/output data gathered from the sensors and/or human experts’ knowledge. Generating fuzzy rules that represent the transition between states leads to assigning a degree of transition from one state to another. Experimental results are presented to demonstrate the effectiveness of the proposed method. The model is tested and evaluated using a dataset collected from a real home environment. The results show the effectiveness of using this method for modelling the activities of daily living based on ambient sensory datasets. The performance of the proposed method is compared with the standard NNs and FFSM techniques. View Full-Text
Keywords: activities of daily living; activities of daily working; finite state machine; fuzzy finite state machine; learning; ADL; ADW; FSM; activity recognition activities of daily living; activities of daily working; finite state machine; fuzzy finite state machine; learning; ADL; ADW; FSM; activity recognition
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Mohmed, G.; Lotfi, A.; Pourabdollah, A. Human Activities Recognition Based on Neuro-Fuzzy Finite State Machine. Technologies 2018, 6, 110.

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