國立虎尾科技大學 |

Language: English

Back

iMOST: Intelligent Motion-Sensing Ap...

University of Missouri - Kansas City.

iMOST: Intelligent Motion-Sensing Approaches for Tracking Emotion.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	iMOST: Intelligent Motion-Sensing Approaches for Tracking Emotion./
Author:	Choi, Sarah.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	63 p.
Notes:	Source: Masters Abstracts International, Volume: 80-08.
Contained By:	Masters Abstracts International80-08.
Subject:	Computer Engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13425889
ISBN:	9780438855434

iMOST: Intelligent Motion-Sensing Approaches for Tracking Emotion.
Choi, Sarah.

iMOST: Intelligent Motion-Sensing Approaches for Tracking Emotion. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 63 p.

Source: Masters Abstracts International, Volume: 80-08.

Thesis (M.S.)--University of Missouri - Kansas City, 2019.

This item must not be sold to any third party vendors.

The aged, minor, and disease members often find it hard to express themselves. They are not fully aware of their need for any help or how to ask for help. The lack of communication ability decreases the quality of life and endangers the life of those members. The purpose of iMOST (Intelligent Motion-Sensing Approaches for Tracking Emotion) is to track the caretaker’s emotion in time by harnessing lightweight gait monitoring de-vices. In this thesis, we identified several tracking case scenarios for dementia patients and proposed a couple of efficient event detection algorithms. We performed feasibility tests by using conventional sensors such as IMU (Inertial Measurement Unit) sensor and smartphone apps. We identified several specific actions commonly happened to patients and gathered data from the field experiments. We analyzed the gait data, proposed efficient real-time algorithms for identifying the emotional status, and finally compared the performance and usability of each algorithm.

ISBN: 9780438855434Subjects--Topical Terms:

796158
Computer Engineering.
Subjects--Index Terms:

IoT

iMOST: Intelligent Motion-Sensing Approaches for Tracking Emotion.
LDR:02087nam a2200349 4500 001 951785
005 20200821052155.5
008 200914s2019 ||||||||||||||||| ||eng d
020 $a 9780438855434
035 $a (MiAaPQ)AAI13425889
035 $a (MiAaPQ)umkc:11379
035 $a AAI13425889
040 $a MiAaPQ $c MiAaPQ
100 1 $a Choi, Sarah. $3 1241256
245 1 0 $a iMOST: Intelligent Motion-Sensing Approaches for Tracking Emotion.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 63 p.
500 $a Source: Masters Abstracts International, Volume: 80-08.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Song, Sejun.
502 $a Thesis (M.S.)--University of Missouri - Kansas City, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a The aged, minor, and disease members often find it hard to express themselves. They are not fully aware of their need for any help or how to ask for help. The lack of communication ability decreases the quality of life and endangers the life of those members. The purpose of iMOST (Intelligent Motion-Sensing Approaches for Tracking Emotion) is to track the caretaker’s emotion in time by harnessing lightweight gait monitoring de-vices. In this thesis, we identified several tracking case scenarios for dementia patients and proposed a couple of efficient event detection algorithms. We performed feasibility tests by using conventional sensors such as IMU (Inertial Measurement Unit) sensor and smartphone apps. We identified several specific actions commonly happened to patients and gathered data from the field experiments. We analyzed the gait data, proposed efficient real-time algorithms for identifying the emotional status, and finally compared the performance and usability of each algorithm.
590 $a School code: 0134.
650 4 $a Computer Engineering. $3 796158
650 4 $a Computer science. $3 573171
653 $a IoT
653 $a Sensing
690 $a 0464
690 $a 0984
710 2 $a University of Missouri - Kansas City. $b Computer Science. $3 1182463
773 0 $t Masters Abstracts International $g 80-08.
790 $a 0134
791 $a M.S.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13425889

based on 0 review(s)

Multimedia

Reviews

Add a review and share your thoughts with other readers

Export

pickup library