Prolonged sitting detection for office workers syndrome prevention using kinect

Conference proceedings article

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

ไม่พบข้อมูลที่เกี่ยวข้อง

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Paliyawan P., Nukoolkit C., Mongkolnam P.

ผู้เผยแพร่: Hindawi

ปีที่เผยแพร่ (ค.ศ.): 2014

ISBN: 9781479929924

นอก: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84905400896&doi=10.1109%2fECTICon.2014.6839785&partnerID=40&md5=29711b90ef4cd6ea9258ca655b1c4aa4

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

This research has focused on detection of prolonged sitting of office workers by performing data mining classification on the real-time skeleton data stream captured by a single Kinect camera set up in an office worker's work station area. The system classifies the input stream into sequences of stills or moves. The performance of several classification methods such as decision tree, neural network, naive Bayes, and k-Nearest Neighbors are compared in order to acquire the optimal classifier. The proposed system can effectively monitor the user's postures with 98% accuracy and give the user real-time feedback based on the three levels of healthy in ergonomics. In addition, the proposed work includes development of an alerting device using a microcontroller, and provision of data visualization for a daily summary report. ฉ 2014 IEEE.

คำสำคัญ

Ergonomics, Health and Medical Informatics, Office Workers Syndrome