語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
iMOST: Intelligent Motion-Sensing Ap...
~
Choi, Sarah.
FindBook
Google Book
Amazon
博客來
iMOST: Intelligent Motion-Sensing Approaches for Tracking Emotion.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
iMOST: Intelligent Motion-Sensing Approaches for Tracking Emotion./
作者:
Choi, Sarah.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:
63 p.
附註:
Source: Masters Abstracts International, Volume: 80-08.
Contained By:
Masters Abstracts International80-08.
標題:
Computer Engineering. -
電子資源:
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:
1567821
Computer Engineering.
Subjects--Index Terms:
IoT
iMOST: Intelligent Motion-Sensing Approaches for Tracking Emotion.
LDR
:02085nmm a2200349 4500
001
2267748
005
20200821052155.5
008
220629s2019 ||||||||||||||||| ||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
3545010
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
1567821
650
4
$a
Computer science.
$3
523869
653
$a
IoT
653
$a
Sensing
690
$a
0464
690
$a
0984
710
2
$a
University of Missouri - Kansas City.
$b
Computer Science.
$3
1680874
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
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9419982
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入