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| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 賴飛羆 | |
| dc.contributor.author | Yu-Han Hung | en |
| dc.contributor.author | 洪鈺涵 | zh_TW |
| dc.date.accessioned | 2021-07-11T15:46:34Z | - |
| dc.date.available | 2023-08-21 | |
| dc.date.copyright | 2018-08-21 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-08-06 | |
| dc.identifier.citation | [1] 台灣內政部統計處網站http://www.moi.gov.tw/stat/index.aspx
[2] ASUS ZENBO https://zenbo.asus.com/tw/ [3] Sajatovic M, Strejilevich SA, Gildengers AG, et al. A report on older-age bipolar disorder from the International Society for Bipolar Disorders Task Force. Bipolar Disord. 2015;17(7):689–704. [4] Leandro da Costa Lane valiengo, Florindo Stella, Orestes vicente Forlenza. Mood disorders in the elderly: prevalence, functional impact, and management challenges. Neuropsychiatric Disease and Treatment 2016:12 2105–2114. [5] Guerra M, Prina AM, Ferri CP, et al. A comparative cross-cultural study of the prevalence of late life depression in low and middle income countries. J Affect Disord. 2016;190:362–368. [6] Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62(6):593–602. [7] Maratos A, Gold C, Wang X, Crawford M. Music therapy for depression. Cochrane Database of Systematic Reviews 2008, Issue 1. Art. No.: CD004517. DOI: 10.1002/14651858.CD004517.pub2. [8] Alfredo Raglio, Lapo Attardo, Giulia Gontero, Silvia Rollino, Elisabetta Groppo, Enrico Granieri. Effects of music and music therapy on mood in neurological patients. World J Psychiatr 2015 March 22; 5(1): 68-78 ISSN 2220-3206. [9] Nomura T, Tejima N. Critical considerations of applications of affective robots to mental therapy from psychological and sociological perspectives. In: Proceedings of the 11th IEEE International workshop on robot and human interactive communication. 2002. p. 99–104. [10] LibinAV, LibinEV. Person–robotinteractionsfromtherobopsychologists’point of view: the robotic psychology and robotherapy approach. Proceedings of the IEEE 2004;92(11):1789–803. [11] Kazuyoshi Wada and Takanori Shibata, Member, IEEE. Living With Seal Robots—Its Sociopsychological and Physiological Influences on the Elderly at a Care House. IEEE Transactions on Robotics, Vol. 23, No. 5, October 2007 [12] M. Turk and A. Pentland. Eigenfaces for recognition (PDF). Journal of Cognitive Neuroscience. 1991, 3 (1): 71–86. doi:10.1162/jocn.1991.3.1.71 [13] Picard, Rosalind (1998). Affective Computing. M.I.T Media Laboratory Perceptual Computing Section Technical Report No. 321 [14] J. Wang, R. Knipling, and M. Goodman. “The role of driver in attention in crashes; new statistics from the 1995 Crashworthiness Data System (CDS),” in Annual Conference of the Association for the Advancement of Automotive Medicine, Des Plaines, IL, 1996. [15] Amit Konar and Aruna Chakraborty, Christos D. Katsis, George Rigas, Yorgos Goletsis and Dimitrios I. Fotiadis. Emotion Recognition in Car Industry. Emotion Recognition: A Pattern Analysis Approach. DOI: 10.1002/9781118910566.ch20 [16] Hua Gao, Anil Yüce, Jean-Philippe Thiran. Detecting emotional stress from facial expressions for driving safety. Image Processing (ICIP), 2014 IEEE International Conference on, 2014. [17] Yean Seanglidet, Bu Sung Lee, Chai Kiat Yeo. Mood Prediction from Facial Video with Music “Therapy” on a Smartphone. Wireless Telecommunications Symposium (WTS), 2016. [18] Android studio website https://developer.android.com/studio/ [19] Microsoft Azure https://azure.microsoft.com/zh-tw/ [20] 台灣行政院環境保護署https://taqm.epa.gov.tw/taqm/tw/b0201.aspx [21] 行政院環境保護署。環境資源資料開放平臺https://opendata.epa.gov.tw [22] Google Map Android API https://developers.google.com/maps/documentation/android-api/?hl=zh-tw [23] American Music Therapy Association https://www.musictherapy.org [24] Chan, M. F., Wong, Z. Y., Onishi, H., Thayala, N. V. (2011). “Effects of Music on Depression in Older People: A Randomized Controlled Trial”. Journal of Clinical Nursing. 21: 776 – 783G. [25] Paul M. Lehrer; David H. (FRW) Barlow; Robert L. Woolfolk; Wesley E. Sime (2007). Principles and Practice of Stress Management, Third Edition. New York: Guilford Press. pp. 46–47. ISBN 1-59385-000-X. [26] 楊沛仁(2001)，音樂史與欣賞，美樂出版社，台北。 [27] 謝汝光(2002)，微宇宙音樂穿透 DNA─進入生命中的身心靈，自然風文化事業股份有限公司，台北。 [28] Chen, HC, Wu, CH, Lee, YJ, et al.: Validity of the five-item brief symptom rating scale among subjects admitted for general health screening. J Formos Med Assoc 2005; 104(11): 824-9. [29] Lee, MB, Lee, YJ, Yen, LL, et al.: Reliability and validity of using a brief psychiatric symptom rating scale in clinical practice. J Formos Med Assoc 1990; 89(12): 1801-7. [30] 屏東縣政府衛生局(BSRS-5 English Version) https://www.ptshb.gov.tw/eng/cp.aspx?n=8BEFBD0CE914BD76 [31] Kanade, T., Cohn, J. F., & Tian, Y. (2000). Comprehensive database for facial expression analysis. Paper presented at the Fourth IEEE International Conference on Automatic Face and Gesture Recognition. [32] P. Lucey, J. F. Cohn, T. Kanade, J. Saragih, Z. Ambadar, and I. Matthews, “The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion- specified expression,” in IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2010, pp. 94–101 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79132 | - |
| dc.description.abstract | 根據內政部在2018年三月所發表的數據，六十五歲以上的老年人口佔台灣總人口數的百分之十四，大約311萬人，甚至比兒童人口還多，而且兩者的差距正在增加。老年人因情緒產生的問題或是疾病也日漸的明顯。我們希望可以透過居家陪伴機器人ZENBO改善老年人因情緒而產生的疾病問題並且降低老年人因抑鬱而增加的社交成本。
本研究主要為使用ZENBO機器人並且配合其語音系統開發一個Android系統的Application，主要功能有四個：(1) 拍照並且做情緒辨識 (2) 輔助音樂治療做音樂播放 (3) 目前所在位置空氣品質指標查詢 (4) BSRS-5問卷憂鬱問卷調查。使用者可以用ZENBO拍照或是選擇相簿中的照片，App會擷取照片中的人臉，並把照片傳送到Microsoft Azure做情緒預測，情緒預測的結果會傳回App。預測結果簡單的分為兩類：開心及不開心，App根據不一樣的情緒結果讓使用者可以使用音樂播放功能輔助音樂治療效果或是使用者可以選擇外出，ZENBO會定位目前位置並且抓取距離最近的測站位置去提醒使用者空氣品質指標 (AQI)為何，適不適合外出。主要的目的是希望使用者透過ZENBO的陪伴以及語音輔助再加上撥放舒壓愉快的音樂，或是建議出外走走曬曬太陽去達到心情轉換或是維持。 最後，此研究加上了心情溫度計-簡式健康量表 (Brief Symptom Rating Scale, BSRS-5)，主要在作為精神症狀之篩檢表，使用者可以透過ZENBO語音去填寫問卷，並傳送至FIREBASE資料庫，後端管理者便能從使用者所填寫的問卷答案去觀察使用者的情緒變化，或是經由精神科醫師評估。從這些情緒變化的數據也可以去做分析，檢視實際的情緒變化與預期變化相差多遠。 | zh_TW |
| dc.description.abstract | According to the statistics released by the Ministry of the Interior in Taiwan by March 2018, the elderly population over the age of 65 accounts for 14% of the total, and the elderly population is nearly 80,000 more than the children. The gap between the two is growing. As for the adjustment of the mood of the elderly, the issue of the mood adjustment becomes more and more obvious. We hope ZENBO, a home-companion robot, will improve the mood of the elderly and reduce the social cost caused by depression in the elderly.
The research is mainly, based on the ZENBO robot, to develop an Android app that allows users to take pictures with the ZENBO. The system captures the photos in the application and transmits them to the backstage to make a mood prediction. After the user's mood is predicted, the user's mood is transmitted back to the app. The predicted mood can be divided into happy and unhappy, depending on the user's mood to play different music to reach the therapy effect or they can choose to go outside. The purpose is that the users can play a joyful music to achieve the change of mood or to maintain the pleasure of the mood. Finally, with the use of Brief Symptom Rating Scale, a simple questionnaire, users can click on the questionnaire within the application to fill out the questionnaire and then back to the backstage to evaluate the user's mood changes. By using these feelings changes in the data to do the analysis, we know whether there is significant difference or not between the actual and the expected moods. | en |
| dc.description.provenance | Made available in DSpace on 2021-07-11T15:46:34Z (GMT). No. of bitstreams: 1 ntu-107-R05945042-1.pdf: 2538555 bytes, checksum: 80b2e2983191f873d99a77e3a7d4dd35 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌 謝 ii 中文摘要 iii Abstract iv CONTENTS v LIST OF FIGURES vii LIST OF TABLES viii Chapter 1 Introduction 1 1.1 Background 1 1.2 Motivation and objective 4 Chapter 2 Literature review and discussion 6 2.1 Mood disorders occur in elderly 6 2.2 The effect of music therapy 7 2.3 Robot application in home care or elderly care 8 2.4 Facial emotion recognition application 9 Chapter 3 Research methodology 12 3.1 Procedure of usage 12 3.2 Method designed 14 3.2.2 Android Studio 18 3.2.3 Firebase 19 3.3 Prediction of mood 20 3.4 Air quality index 22 3.5 Music therapy 24 3.6 Brief symptom rating scale 26 3.7 Clinical feasibility assessment 27 Chapter 4 Anticipated results and achievements 30 4.1 Main functions of the emotion application 30 4.1.1 Picture selection and Emotion detection 33 4.1.2 Music player with music therapy 36 4.1.3 Air quality index reminder 38 4.1.4 Mental condition 40 4.2 Clinical feasibility and generalization of ZENBO-emotion 43 Chapter 5 Discussion 49 Chapter 6 Conclusion and future work 52 6.1 Conclusion 52 6.2 Future work 54 6.2.1 Emotion recognition 54 6.2.2 Smart home 57 6.2.3 Professional music therapy 58 Reference 59 | |
| dc.language.iso | en | |
| dc.subject | 簡式健康量表 | zh_TW |
| dc.subject | ZENBO應用程式 | zh_TW |
| dc.subject | 情緒管理 | zh_TW |
| dc.subject | 音樂治療 | zh_TW |
| dc.subject | 老人健康照護 | zh_TW |
| dc.subject | 陪伴式機器人 | zh_TW |
| dc.subject | ZENBO applications | en |
| dc.subject | Brief Symptom Rating Scale | en |
| dc.subject | music therapy | en |
| dc.subject | health care for the elderly | en |
| dc.subject | emotion management | en |
| dc.subject | home-companion robot | en |
| dc.title | 利用機器人ZENBO發展情緒辨識以及音樂輔助系統 | zh_TW |
| dc.title | Developing an Emotion Recognition and Music Therapy System Based on Robot ZENBO | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 黃國晉,戴浩志,趙坤茂,蔡坤霖 | |
| dc.subject.keyword | ZENBO應用程式,陪伴式機器人,情緒管理,老人健康照護,音樂治療,簡式健康量表, | zh_TW |
| dc.subject.keyword | ZENBO applications,home-companion robot,emotion management,health care for the elderly,music therapy,Brief Symptom Rating Scale, | en |
| dc.relation.page | 61 | |
| dc.identifier.doi | 10.6342/NTU201802441 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-08-07 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 生醫電子與資訊學研究所 | zh_TW |
| dc.date.embargo-lift | 2023-08-21 | - |
| Appears in Collections: | 生醫電子與資訊學研究所 | |
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| File | Size | Format | |
|---|---|---|---|
| ntu-107-R05945042-1.pdf Restricted Access | 2.48 MB | Adobe PDF |
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