Monitoring Discrete Activities of Daily Living of Young & Older Adults using 5.8 GHz Frequency Modulated Continuous Wave Radar and ResNet Algorithm

Umer Saeed, Fehaid Alqahtani, Fatmah Baothman, Syed Yaseen Shah, Syed Ikram Shah, Syed Salman Badshah, Muhammad Ali Imran , Qammer H. Abbasi, Syed Aziz Shah

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

Abstract

With numerous applications in distinct domains, especially healthcare, human activity detection is of utmost significance. The objective of this study is to monitor activities of daily living using the publicly available dataset recorded in nine different geometrical locations for ninety-nine volunteers including young and older adults (65+) using 5.8 GHz Frequency Modulated Continuous Wave (FMCW) radar. In this work, we experimented with discrete human activities, for instance, walking, sitting, standing, bending, and drinking, recorded for 10 s and 5 s. To detect the list of activities mentioned above, we obtained the Micro-Doppler signatures through Short-time Fourier transform using MATLAB tool and procured the spectrograms as images. The acquired data of the spectrograms are trained, validated, and tested exploiting a state-of-the-art deep learning approach known as Residual Neural Network (ResNet). Moreover, the confusion matrix, model loss, and classification accuracy are used as performance evaluation metrics for the trained ResNet model. The unique skip connection technique of ResNet minimises the overfitting and underfitting issue, consequently resulting accuracy rate up to 91% .
Original languageEnglish
Title of host publicationBody Area Networks
Subtitle of host publicationSmart IoT and Big Data for Intelligent Health Management
EditorsMasood Ur Rehman, Ahmed Zoha
PublisherSpringer
Pages28-38
Number of pages11
ISBN (Electronic)978-3-030-95593-9
ISBN (Print)978-3-030-95592-2
DOIs
Publication statusPublished - 2022
Event16th EAI International Conference on Body Area Networks: Smart IoT and big data for intelligent health management - Virtual, Glasgow, United Kingdom
Duration: 25 Oct 202126 Oct 2021
https://bodynets.eai-conferences.org/2021/

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
PublisherSpringer
Volume420
ISSN (Print)1867-8211
ISSN (Electronic)1867-822X

Conference

Conference16th EAI International Conference on Body Area Networks
Abbreviated titleBODYNETS 2021
Country/TerritoryUnited Kingdom
CityGlasgow
Period25/10/2126/10/21
OtherVirtual
Internet address

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