東華大學圖書館 |

語系: 繁體中文

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

A Wearable Computer Vision System fo...

Likitlersuang, Jirapat.

FindBook

Google Book

Amazon

博客來

A Wearable Computer Vision System for Monitoring Hand Use at Home.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A Wearable Computer Vision System for Monitoring Hand Use at Home./
作者:	Likitlersuang, Jirapat.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
面頁冊數:	114 p.
附註:	Source: Dissertations Abstracts International, Volume: 81-06, Section: B.
Contained By:	Dissertations Abstracts International81-06B.
標題:	Engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13904873
ISBN:	9781392874004

A Wearable Computer Vision System for Monitoring Hand Use at Home.
Likitlersuang, Jirapat.

A Wearable Computer Vision System for Monitoring Hand Use at Home. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 114 p.

Source: Dissertations Abstracts International, Volume: 81-06, Section: B.

Thesis (Ph.D.)--University of Toronto (Canada), 2019.

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

Impairments in hand function lead to reduced independence and quality of life after cervical spinal cord injury (SCI). In order to develop effective rehabilitation interventions for individuals with cervical SCI, it is important to assess hand function throughout the rehabilitation process. Currently, the efficacy of new treatments is measured by assessments limited to a controlled setting or based on self-report; there is currently no viable method to collect quantitative information once the patient has returned to the community. This thesis attempts to solve this gap by developing a computer vision-based wearable camera system for monitoring hand use. Our research involved (1) the collection of egocentric video that represents activities of daily living, (2) the development of an algorithm that captures interactions between the hand and objects in the environment, and (3) the evaluation of the system in both laboratory and home settings.Four studies were executed, involving three video datasets (20 able-bodied participants and 17 participants with SCI in a home simulation laboratory, as well as 3 participants with SCI in their home). We introduced the concept of hand-object interaction detection, defined as a binary decision about whether or not the hand is manipulating an object for a functional purpose. The datasets were used in the development and evaluation of an algorithmic pipeline consisting of hand detection and segmentation, followed by hand-object interaction detection. For this step, a random forest classifier was trained on hand motion, hand shape and scene colour features. The frame-by-frame binary output data over time was further analysed to extract three functional hand-use metrics: (1) the amount of total interaction as a percentage of testing time, (2) the average duration of interactions in seconds, and (3) the number of interactions per hour. The final study investigated the views of participants with SCI on the use of wearable cameras.With appropriate strategies determined by input from individuals with SCI, this thesis demonstrates the potential of a wearable egocentric camera as a unique tool to allow researchers and clinicians to gauge the user's level of independence at home in activities involving upper limb function.

ISBN: 9781392874004Subjects--Topical Terms:

586835
Engineering.
Subjects--Index Terms:

Community-based rehabilitation

A Wearable Computer Vision System for Monitoring Hand Use at Home.
LDR:03496nmm a2200385 4500 001 2268723
005 20200824072436.5
008 220629s2019 ||||||||||||||||| ||eng d
020 $a 9781392874004
035 $a (MiAaPQ)AAI13904873
035 $a AAI13904873
040 $a MiAaPQ $c MiAaPQ
100 1 $a Likitlersuang, Jirapat. $3 3546024
245 1 0 $a A Wearable Computer Vision System for Monitoring Hand Use at Home.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 114 p.
500 $a Source: Dissertations Abstracts International, Volume: 81-06, Section: B.
500 $a Advisor: Zariffa, Jose.
502 $a Thesis (Ph.D.)--University of Toronto (Canada), 2019.
506 $a This item must not be sold to any third party vendors.
520 $a Impairments in hand function lead to reduced independence and quality of life after cervical spinal cord injury (SCI). In order to develop effective rehabilitation interventions for individuals with cervical SCI, it is important to assess hand function throughout the rehabilitation process. Currently, the efficacy of new treatments is measured by assessments limited to a controlled setting or based on self-report; there is currently no viable method to collect quantitative information once the patient has returned to the community. This thesis attempts to solve this gap by developing a computer vision-based wearable camera system for monitoring hand use. Our research involved (1) the collection of egocentric video that represents activities of daily living, (2) the development of an algorithm that captures interactions between the hand and objects in the environment, and (3) the evaluation of the system in both laboratory and home settings.Four studies were executed, involving three video datasets (20 able-bodied participants and 17 participants with SCI in a home simulation laboratory, as well as 3 participants with SCI in their home). We introduced the concept of hand-object interaction detection, defined as a binary decision about whether or not the hand is manipulating an object for a functional purpose. The datasets were used in the development and evaluation of an algorithmic pipeline consisting of hand detection and segmentation, followed by hand-object interaction detection. For this step, a random forest classifier was trained on hand motion, hand shape and scene colour features. The frame-by-frame binary output data over time was further analysed to extract three functional hand-use metrics: (1) the amount of total interaction as a percentage of testing time, (2) the average duration of interactions in seconds, and (3) the number of interactions per hour. The final study investigated the views of participants with SCI on the use of wearable cameras.With appropriate strategies determined by input from individuals with SCI, this thesis demonstrates the potential of a wearable egocentric camera as a unique tool to allow researchers and clinicians to gauge the user's level of independence at home in activities involving upper limb function.
590 $a School code: 0779.
650 4 $a Engineering. $3 586835
650 4 $a Computer science. $3 523869
650 4 $a Health sciences. $3 3168359
653 $a Community-based rehabilitation
653 $a Egocentric vision
653 $a Outcome measure
653 $a Rehabilitation engineering
653 $a Tetraplegia
653 $a Upper extremity
690 $a 0537
690 $a 0984
690 $a 0566
710 2 $a University of Toronto (Canada). $b Biomedical Engineering. $3 2101094
773 0 $t Dissertations Abstracts International $g 81-06B.
790 $a 0779
791 $a Ph.D.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13904873