Giyilebilir Sensörler ile Insan Hareketlerini Izleme

Translated title of the contribution: Giyilebilir Sensörler ile Insan Hareketlerini Izleme Human Activity Monitoring via Wearable Sensors

Mucahit Altintas, Nilay Tufek, Murat Yalcin, Yi Li, Senem Kursun Bahadir

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

Abstract

In recent years, the use of wearable devices in many areas has emerged. Recognition of human behavior and movements has become almost the essential component of wearable devices. Monitoring human behavior enhances human life in many fields, especially in the health sector. Wearable sensors are preferred for motion tracking because they can work independently of the location, cause less discomfort to users in terms of privacy than other sensing devices, and are inexpensive. In this study, using data from wearable sensors, human behavior has been predicted with deep learning methods. The contributions of the spectrogram, wavelet transform and time-based feature spaces to the prediction performance are analyzed. The prediction performance of our developed model is comparable to the state-of-art studies in the literature.

Translated title of the contributionGiyilebilir Sensörler ile Insan Hareketlerini Izleme Human Activity Monitoring via Wearable Sensors
Original languageTurkish
Title of host publication2022 30th Signal Processing and Communications Applications Conference, SIU 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665450928
DOIs
Publication statusPublished - 2022
Event30th Signal Processing and Communications Applications Conference, SIU 2022 - Safranbolu, Turkey
Duration: 15 May 202218 May 2022

Publication series

Name2022 30th Signal Processing and Communications Applications Conference, SIU 2022

Conference

Conference30th Signal Processing and Communications Applications Conference, SIU 2022
Country/TerritoryTurkey
CitySafranbolu
Period15/05/2218/05/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

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