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題名 通過可穿戴裝置最佳化以活動為基礎的嬰兒潮顾客參與度研究
Optimizing Activity-Based Engagement of Baby Boomers through Wearable Devices
作者 魏曉晨
Wei, Xiao Chen
貢獻者 苑守慈
Yuan, Soe Tysr
魏曉晨
Wei, Xiao Chen
關鍵詞 可穿戴裝置
嬰兒潮人群
行為識別
情緒識別
積極情緒
投入度
優化
介入
wearable device
baby boomer
activity recognition
emotion recognition
positive emotion
engagement
optimization
intervention
日期 2016
上傳時間 9-Aug-2016 10:46:00 (UTC+8)
摘要 現在,資訊技術為了通過實時、交互、有效的方式解決多樣但是具體的問題依然在發展變化著。然而幸運的是,以手機為代表的智慧產品已經發展到一定的階段,因此給了我們服務於不同的使用者提供了更多的機會。大約出生在第二次戰之後二十年的嬰兒潮一代,到現在處在50-65歲這一年齡階段。但是,相當數量的他們在經過幾十年的喧囂忙碌之後並沒有找尋到自己的生活意義。目前市場上的可穿戴裝置並不能滿足嬰兒潮人群的真正需求。在本研究中,我們想開發一個通過可穿戴設備架構起來的服務交互平臺。此研究分為四個階段,分別是感應期,監測期,優化期和自主期。之後資源將通過提供者和受益者之間的互動,達到“價值最大化”的最終目的。我們將要提供的服務,不僅部分預防了某些嚴重疾病的發生,同時也通過可穿戴裝置為嬰兒潮人群提供幫助,以實現有意義地生活。
Information technology nowadays is evolving and changing to solve various but specific human-needs problems through a real-time, interactive, effective way. Smart products exemplified by mobile phones have developed to reach a certain stage that gives us more chances to serve different users. Baby boomers, who were born in about twenty years after the second war, are now about 50-65 years old. A certain number of them confuse leisure in meaning of life after decades of bustle. However, current wearable devices still cannot fulfill the real demands of baby boomers. In this paper, we would like to develop interactive service system of wearable devices in four phases, respectively sensing, monitoring, optimization and autonomy, and then resources are integrated through the interaction among providers and beneficiaries in order to reach the result of “value maximization” from each baby boomer`s perspective. This study aims to design services that not only prevent partly from serious diseases but also offer useful help to have a meaningful life through wearable devices.
參考文獻 1. Anderson, L., & Heyne, L. A. (2012). Therapeutic recreation practice: A strengths approach. Venture Pub.
2. Antheunis, M. L., Vanden Abeele, M. M., & Kanters, S. (2015). The Impact of Facebook Use on Micro-Level Social Capital: A Synthesis. Societies, 5(2), 399-419.
3. Bloch, S., Lemeignan, M., & Aguilera-T, N. (1991). Specific respiratory patterns distinguish among human basic emotions. International Journal of Psychophysiology, 11(2), 141-154.
4. De Deugd, S., Carroll, R., Kelly, K., Millett, B., & Ricker, J. (2006). SODA: service oriented device architecture. IEEE Pervasive Computing, (3), 94-96.
5. Eakman, A. M., Carlson, M. E., & Clark, F. A. (2010). The meaningful activity participation assessment: A measure of engagement in personally valued activities. The International Journal of Aging and Human Development, 70(4), 299-317.
6. Ghosh, R., Ratan, S., Lindeman, D., & Steinmetz, V. (2013). The new era of connected aging: A framework for understanding technologies that support older adults in aging in place. Oakland, CA: Center for Technology and Aging.
7. Gilleard, C., & Higgs, P. (2008). The third age and the baby boomers: Two approaches to the social structuring of later life. International journal of ageing and later life, 2(2), 13-30
8. Grootaert, C., Narayan, D., Jones, V. N., & Woolcock, M. (2003). Integrated questionnaire for the measurement of social capital. The World Bank Social Capital Thematic Group.
9. Jerritta, S., Murugappan, M., Nagarajan, R., & Wan, K. (2011, March). Physiological signals based human emotion recognition: a review. In Signal Processing and its Applications (CSPA), 2011 IEEE 7th International Colloquium on (pp. 410-415). IEEE.
10. Lusardi, A., & Mitchell, O. S. (2007). Baby boomer retirement security: The roles of planning, financial literacy, and housing wealth. Journal of monetary Economics, 54(1), 205-224.
11. MacInnes, J. (2006). Work–life balance in Europe: a response to the baby bust or reward for the baby boomers? European Societies, 8(2), 223-249.
12. Martin, L. G., Freedman, V. A., Schoeni, R. F., & Andreski, P. M. (2009). Health and functioning among baby boomers approaching 60. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, gbn040.
13. Mathie, M. J., Coster, A. C., Lovell, N. H., & Celler, B. G. (2004). Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiological measurement, 25(2), R1.
14. Moraveji, N., Olson, B., Nguyen, T., Saadat, M., Khalighi, Y., Pea, R., & Heer, J. (2011, October). Peripheral paced respiration: influencing user physiology during information work. In Proceedings of the 24th annual ACM symposium on User interface software and technology (pp. 423-428). ACM.
15. Nyan, M. N., Tay, F. E., Manimaran, M., & Seah, K. H. W. (2006, April). Garment-based detection of falls and activities of daily living using 3-axis MEMS accelerometer. In Journal of Physics: Conference Series (Vol. 34, No. 1, p. 1059). IOP Publishing.
16. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. the Journal of Marketing, 41-50.
17. Park, N., Peterson, C., & Seligman, M. E. (2004). Strengths of character and well-being. Journal of social and Clinical Psychology, 23(5), 603-619.
18. Philippot, P., Chapelle, G., & Blairy, S. (2002). Respiratory feedback in the generation of emotion. Cognition & Emotion, 16(5), 605-627.
19. Porter, M. E., & Heppelmann, J. E. (2015). How Smart, Connected Products Are Transforming Companies. HARVARD BUSINESS REVIEW, 93(10), 96-+
20. Prochaska, J. O. (2008). Multiple health behavior research represents the future of preventive medicine. Preventive medicine, 46(3), 281-285.
21. Quine, S., & Carter, S. (2006). Australian baby boomers’ expectations and plans for their old age. Australasian Journal on Ageing, 25(1), 3-8.
22. Sazonov, E., & Neuman, M. R. (Eds.). (2014). Wearable Sensors: Fundamentals, implementation and applications. Elsevier
23. Segerstrom, S. C. (2001). Optimism and attentional bias for negative and positive stimuli. Personality and Social Psychology Bulletin, 27(10), 1334-1343.
24. Seligman, M. E. (2012). Flourish: A visionary new understanding of happiness and well-being. Simon and Schuster.
25. Steger, M. F., Bundick, M. J., & Yeager, D. (2012). Meaning in life. In Encyclopedia of Adolescence (pp. 1666-1677). Springer US.
26. Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of marketing, 68(1), 1-17.
27. Vargo, S. L., Maglio, P. P., & Akaka, M. A. (2008). On value and value co-creation: A service systems and service logic perspective. European management journal, 26(3), 145-152
28. Vargo, S. L., & Morgan, F. W. (2005). Services in society and academic thought: an historical analysis. Journal of Macromarketing, 25(1), 42-53.
29. Yang, C. C., & Hsu, Y. L. (2010). A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors, 10(8), 7772-7788.
描述 碩士
國立政治大學
資訊管理學系
103356044
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0103356044
資料類型 thesis
dc.contributor.advisor 苑守慈zh_TW
dc.contributor.advisor Yuan, Soe Tysren_US
dc.contributor.author (Authors) 魏曉晨zh_TW
dc.contributor.author (Authors) Wei, Xiao Chenen_US
dc.creator (作者) 魏曉晨zh_TW
dc.creator (作者) Wei, Xiao Chenen_US
dc.date (日期) 2016en_US
dc.date.accessioned 9-Aug-2016 10:46:00 (UTC+8)-
dc.date.available 9-Aug-2016 10:46:00 (UTC+8)-
dc.date.issued (上傳時間) 9-Aug-2016 10:46:00 (UTC+8)-
dc.identifier (Other Identifiers) G0103356044en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/99773-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 103356044zh_TW
dc.description.abstract (摘要) 現在,資訊技術為了通過實時、交互、有效的方式解決多樣但是具體的問題依然在發展變化著。然而幸運的是,以手機為代表的智慧產品已經發展到一定的階段,因此給了我們服務於不同的使用者提供了更多的機會。大約出生在第二次戰之後二十年的嬰兒潮一代,到現在處在50-65歲這一年齡階段。但是,相當數量的他們在經過幾十年的喧囂忙碌之後並沒有找尋到自己的生活意義。目前市場上的可穿戴裝置並不能滿足嬰兒潮人群的真正需求。在本研究中,我們想開發一個通過可穿戴設備架構起來的服務交互平臺。此研究分為四個階段,分別是感應期,監測期,優化期和自主期。之後資源將通過提供者和受益者之間的互動,達到“價值最大化”的最終目的。我們將要提供的服務,不僅部分預防了某些嚴重疾病的發生,同時也通過可穿戴裝置為嬰兒潮人群提供幫助,以實現有意義地生活。zh_TW
dc.description.abstract (摘要) Information technology nowadays is evolving and changing to solve various but specific human-needs problems through a real-time, interactive, effective way. Smart products exemplified by mobile phones have developed to reach a certain stage that gives us more chances to serve different users. Baby boomers, who were born in about twenty years after the second war, are now about 50-65 years old. A certain number of them confuse leisure in meaning of life after decades of bustle. However, current wearable devices still cannot fulfill the real demands of baby boomers. In this paper, we would like to develop interactive service system of wearable devices in four phases, respectively sensing, monitoring, optimization and autonomy, and then resources are integrated through the interaction among providers and beneficiaries in order to reach the result of “value maximization” from each baby boomer`s perspective. This study aims to design services that not only prevent partly from serious diseases but also offer useful help to have a meaningful life through wearable devices.en_US
dc.description.tableofcontents CHAPTER 1. INTRODUCTION 1
1.1 Background and Motivation 2
1.2 Research Question 3
1.3 Research Methods 6
1.4 Propose and contribution 9
1.5 Content Organization 9
CHAPTER 2. LITERATURE REVIEW 12
2.1 Wearable Devices 12
2.1.1 The wearable devices - “Fitbit” and “Spire” 14
2.1.2 The Sensors of Physical Data in Wearable Devices 15
2.1.3 The Sensors of Emotional Data in Wearable Devices 16
2.2 The Service Design in Wearable Devices 16
CHAPTER 3. iEnjOrange PROJECT 19
3.1 The Conceptual Framework of iEnjOrange 19
3.2 The Ecosystem of iEnjOrange 21
3.3 The System Architecture of iEnjOrange 23
3.4 The System Flow 25
CHAPTER 4. THE ACTIVITY-BASED ENGAGEMENT OF BABYBOOMERS MECHANISM THROUGH WEARABLE DEVICES 29
4.1 Conceptual Framework 29
4.2 Design logic and research approach 31
4.3 Activity-based Sensing Module 33
4.4 Activity-based Monitor Module 35
4.4.1 Activity 35
4.4.2 Emotion 38
4.4.3 Others 39
4.5 Activity-based Optimization Module 40
4.6Activity-based Autonomy Module 43
CHAPTER 5. APPLICATION SCENARIO 46
CHAPTER 6 EVALUATION 50
6.1 Propositions 50
6.1.1 Assumptions 50
6.2 Controlled Experiment and Interview for Baby Boomers 51
6.2.2 Subjects of Controlled Experiment with Baby Boomers 53
6.2.3 Results of Controlled Experiment with Baby Boomers 54
6.3 Discussion of Findings 72
6.3.1 Propositions 73
CHAPTER 7. CONCLUSIONS 76
7.1 Contribution 76
7.2 Managerial Implications 77
7.3 Limitations and Future Works 77
REFERENCES 79
zh_TW
dc.format.extent 3990331 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0103356044en_US
dc.subject (關鍵詞) 可穿戴裝置zh_TW
dc.subject (關鍵詞) 嬰兒潮人群zh_TW
dc.subject (關鍵詞) 行為識別zh_TW
dc.subject (關鍵詞) 情緒識別zh_TW
dc.subject (關鍵詞) 積極情緒zh_TW
dc.subject (關鍵詞) 投入度zh_TW
dc.subject (關鍵詞) 優化zh_TW
dc.subject (關鍵詞) 介入zh_TW
dc.subject (關鍵詞) wearable deviceen_US
dc.subject (關鍵詞) baby boomeren_US
dc.subject (關鍵詞) activity recognitionen_US
dc.subject (關鍵詞) emotion recognitionen_US
dc.subject (關鍵詞) positive emotionen_US
dc.subject (關鍵詞) engagementen_US
dc.subject (關鍵詞) optimizationen_US
dc.subject (關鍵詞) interventionen_US
dc.title (題名) 通過可穿戴裝置最佳化以活動為基礎的嬰兒潮顾客參與度研究zh_TW
dc.title (題名) Optimizing Activity-Based Engagement of Baby Boomers through Wearable Devicesen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 1. Anderson, L., & Heyne, L. A. (2012). Therapeutic recreation practice: A strengths approach. Venture Pub.
2. Antheunis, M. L., Vanden Abeele, M. M., & Kanters, S. (2015). The Impact of Facebook Use on Micro-Level Social Capital: A Synthesis. Societies, 5(2), 399-419.
3. Bloch, S., Lemeignan, M., & Aguilera-T, N. (1991). Specific respiratory patterns distinguish among human basic emotions. International Journal of Psychophysiology, 11(2), 141-154.
4. De Deugd, S., Carroll, R., Kelly, K., Millett, B., & Ricker, J. (2006). SODA: service oriented device architecture. IEEE Pervasive Computing, (3), 94-96.
5. Eakman, A. M., Carlson, M. E., & Clark, F. A. (2010). The meaningful activity participation assessment: A measure of engagement in personally valued activities. The International Journal of Aging and Human Development, 70(4), 299-317.
6. Ghosh, R., Ratan, S., Lindeman, D., & Steinmetz, V. (2013). The new era of connected aging: A framework for understanding technologies that support older adults in aging in place. Oakland, CA: Center for Technology and Aging.
7. Gilleard, C., & Higgs, P. (2008). The third age and the baby boomers: Two approaches to the social structuring of later life. International journal of ageing and later life, 2(2), 13-30
8. Grootaert, C., Narayan, D., Jones, V. N., & Woolcock, M. (2003). Integrated questionnaire for the measurement of social capital. The World Bank Social Capital Thematic Group.
9. Jerritta, S., Murugappan, M., Nagarajan, R., & Wan, K. (2011, March). Physiological signals based human emotion recognition: a review. In Signal Processing and its Applications (CSPA), 2011 IEEE 7th International Colloquium on (pp. 410-415). IEEE.
10. Lusardi, A., & Mitchell, O. S. (2007). Baby boomer retirement security: The roles of planning, financial literacy, and housing wealth. Journal of monetary Economics, 54(1), 205-224.
11. MacInnes, J. (2006). Work–life balance in Europe: a response to the baby bust or reward for the baby boomers? European Societies, 8(2), 223-249.
12. Martin, L. G., Freedman, V. A., Schoeni, R. F., & Andreski, P. M. (2009). Health and functioning among baby boomers approaching 60. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, gbn040.
13. Mathie, M. J., Coster, A. C., Lovell, N. H., & Celler, B. G. (2004). Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiological measurement, 25(2), R1.
14. Moraveji, N., Olson, B., Nguyen, T., Saadat, M., Khalighi, Y., Pea, R., & Heer, J. (2011, October). Peripheral paced respiration: influencing user physiology during information work. In Proceedings of the 24th annual ACM symposium on User interface software and technology (pp. 423-428). ACM.
15. Nyan, M. N., Tay, F. E., Manimaran, M., & Seah, K. H. W. (2006, April). Garment-based detection of falls and activities of daily living using 3-axis MEMS accelerometer. In Journal of Physics: Conference Series (Vol. 34, No. 1, p. 1059). IOP Publishing.
16. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. the Journal of Marketing, 41-50.
17. Park, N., Peterson, C., & Seligman, M. E. (2004). Strengths of character and well-being. Journal of social and Clinical Psychology, 23(5), 603-619.
18. Philippot, P., Chapelle, G., & Blairy, S. (2002). Respiratory feedback in the generation of emotion. Cognition & Emotion, 16(5), 605-627.
19. Porter, M. E., & Heppelmann, J. E. (2015). How Smart, Connected Products Are Transforming Companies. HARVARD BUSINESS REVIEW, 93(10), 96-+
20. Prochaska, J. O. (2008). Multiple health behavior research represents the future of preventive medicine. Preventive medicine, 46(3), 281-285.
21. Quine, S., & Carter, S. (2006). Australian baby boomers’ expectations and plans for their old age. Australasian Journal on Ageing, 25(1), 3-8.
22. Sazonov, E., & Neuman, M. R. (Eds.). (2014). Wearable Sensors: Fundamentals, implementation and applications. Elsevier
23. Segerstrom, S. C. (2001). Optimism and attentional bias for negative and positive stimuli. Personality and Social Psychology Bulletin, 27(10), 1334-1343.
24. Seligman, M. E. (2012). Flourish: A visionary new understanding of happiness and well-being. Simon and Schuster.
25. Steger, M. F., Bundick, M. J., & Yeager, D. (2012). Meaning in life. In Encyclopedia of Adolescence (pp. 1666-1677). Springer US.
26. Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of marketing, 68(1), 1-17.
27. Vargo, S. L., Maglio, P. P., & Akaka, M. A. (2008). On value and value co-creation: A service systems and service logic perspective. European management journal, 26(3), 145-152
28. Vargo, S. L., & Morgan, F. W. (2005). Services in society and academic thought: an historical analysis. Journal of Macromarketing, 25(1), 42-53.
29. Yang, C. C., & Hsu, Y. L. (2010). A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors, 10(8), 7772-7788.
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