Developing a Smart IoT Solution to Monitor on-Bed Movement Patterns

Conference proceedings article

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Youngkong P., Panpanyatep W., Thamrongaphichartkul K.

ผู้เผยแพร่: Hindawi

ปีที่เผยแพร่ (ค.ศ.): 2020

หน้าแรก: 306

หน้าสุดท้าย: 309

จำนวนหน้า: 4

ISBN: 9781728166940

นอก: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100185168&doi=10.1109%2fInCIT50588.2020.9310930&partnerID=40&md5=eac8c27861d5a836577bda262bec181a

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

IoT devices and systems become a part of modern living. They are mostly used to monitor daily activities, especially related to personal health and fitness. In fact, it is getting more crucial during the COVID-19 pandemic. In this study, a smart monitoring and alarming IoT system called 'NEF' was modified to recognize on-bed movement patterns including prone position applying different machine learning techniques. On-bed movement patterns were collected from 7 subjects. Considering only prone and supine positions, the models obtained from multilayer perceptron was the best. However, random forest yielded the highest overall correctly classified percentage. Further investigation is likely to include beddings such as pillows and blankets. © 2020 IEEE.

คำสำคัญ

Monitor and Alarm, On-Bed Movement, Prone Position