An intelligent computing architecture in the Internet of Medical Things to reduce the delay of the continuous monitoring system of patients with low mobility and special patients
Subject Areas : Computer Engineering and IT
reza Ariana
1
,
Mohammad Reza majma
2
,
Somayyeh Jafarali Jassbi
3
1 - Department of Computer Engineering, Technical and Engineering Faculty, Islamic Azad University, Science and Research Unit, Tehran, Iran
2 - Islamic Azad University,Pardis Branch, Tehran, Iran
3 - Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Keywords: Detection of freezing of gait (FOG), Parkinson's disease (PD),
Abstract :
Internet of Things (IoT) technology offers a structured approach to address aspects of health care delivery in terms of health and remote monitoring for patients with specific conditions and life-threatening diseases. The Internet of Things will generate an unprecedented amount of data that can be processed using cloud computing, which will result in huge delays due to resource limitations. But for real-time remote health monitoring applications, the delay caused by transferring data to the cloud and back to the application is unacceptable. we proposed remote monitoring of patient health in smart homes using the concept of fog computing in smart gateway. The FOG detection system implemented under fog computing consisted of a linear map and a Mobius map in combination with fuzzy logic to create a multi-level output (MLFM-map) that exploits different spatial resolutions in motion data analysis. The model architecture and parameters are designed to provide optimal performance while reducing computational complexity and testing time. The proposed approach showed good to excellent classification performance, with an accuracy of more than 90% of FOG episodes detected on average with very low latency in the original dataset
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