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Yardımlı Yaşlanma: Yaşlılık Bilimi, Nesnelerin İnterneti ve Psikolojik Yapay Zekanın Buluşması

Yıl 2019, Cilt: 1 Sayı: 1, 14 - 24, 30.06.2019

Öz

Bu makalede, yaşlanmakta olan nüfusların yardımlı yaşamaları konulu tartışmaların bir uzantısı olarak ‘yardımlı yaşlanma’ biçiminde yeni bir terim ileri sürüyoruz. Makale, 5 ana bölümden oluşuyor: Girişten sonraki ilk bölümde, nesnelerin internetinin sağlık uygulamalarının çoğunlukla teknik açıklamalarını gözden geçiriyoruz. İkinci bölümde, nesnelerin internetinin sağlık uygulamalarına ilişkin çoğunlukla toplum bilimleri yönelimli araştırmalara giriş yapıyoruz. Üçüncü bölümde, nesnelerin internetiyle ilgili yaşlılık bilimi araştırmalarını sunuyor ve tartışıyoruz. Dördüncü bölümde, bir diğer görece yeni terim olan ‘psikolojik Yapay Zeka’ terimine odaklanıyoruz. Bunun gelecekteki yaşlılık bilimi amaçlı nesnelerin interneti için ne kadar merkezi olacağını gösteriyoruz. Son olarak, yardımlı yaşlanma kavramsallaştırmamızı geliştirmek üzere yardımlı yaşama çalışmaları üstüne düşünüyoruz.

Kaynakça

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Assisted Aging: The Future Confluence of Gerontology, Internet of Things and Psychological AI

Yıl 2019, Cilt: 1 Sayı: 1, 14 - 24, 30.06.2019

Öz

In this article, we propose a new term, ‘assisted aging’ which is an offshoot of the discussions on assisted living of aging populations. The article consists of 5 major sections: In the first section after introduction, we review mostly technical accounts of health applications of IoT. In the second section, we introduce mostly social science-oriented research on health applications of IoT. In the third section, we present and discuss gerontological research on IoT. In the fourth section, we focus on yet another relatively new term which is ‘psychological AI’. We show how this will be central to future IoT for gerontological purposes. Finally, we reflect on assisted living studies to develop our notion of assisted aging.

Kaynakça

  • Anumala, H., & Busetty, S. M. (2015, December). Distributed device health platform using Internet of Things devices. In Data Science and Data Intensive Systems (DSDIS), 2015 IEEE International Conference on (pp. 525-531). IEEE. Accessed https://ieeexplore.ieee.org/abstract/document/7396553
  • Anzanpour, A., Rahmani, A. M., Liljeberg, P., & Tenhunen, H. (2015, December). Internet of things enabled in-home health monitoring system using early warning score. In Proceedings of the 5th EAI International Conference on Wireless Mobile Communication and Healthcare (pp. 174-177). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering).
  • Astington, J. W., & Jenkins, J. M. (1999). A longitudinal study of the relation between language and theory-of-mind development. Developmental Psychology, 35(5), 1311-1320.
  • Atee, M., Hoti, K., & Hughes, J. D. (2018). A technical note on the PainChek™ system: a web portal and mobile medical device for assessing pain in people with dementia. Frontiers in Aging Neuroscience, 10, 1-13.
  • Baldissera, T. A., & De Faveri, C. (2016). Emergent Technologies for Active Aging. Revista ComInG-Communications and Innovations Gazette, 1(1), 68-78.
  • Banerjee, T., Peterson, M., Oliver, Q., Froehle, A., & Lawhorne, L. (2018). Validating a commercial device for continuous activity measurement in the older adult population for dementia management. Smart Health, 5, 51-62.
  • Barrué, C., Cortés, A., Cortés, U., Tétard, F., & Gironès, X. (2017). CAREGIVERSPRO-MMD: community services, helping patients with dementia and caregivers connect with others for evaluation, support and to improve the care experience. Computación y Sistemas, 21(1), 23-33.
  • Baum, S. D. (2017). On the promotion of safe and socially beneficial artificial intelligence. AI & Society, 32(4), 543-551.
  • Baumgaertner, B., & Weiss, A. (2014). Do emotions matter in the ethics of human–robot interaction? Artificial empathy and companion robots. In International Symposium on New Frontiers in Human–Robot Interaction, London, UK. https://pdfs.semanticscholar.org/55e0/c6339f4b4541ea479160bcb7177cca93534c.pdf
  • Bengs, A., Hagglund, S., & Wiklund-Engblom, A. (2018). Applying experience design to facilitate wellbeing and social inclusion of older adults. Interaction Design & Architecture (s), 36, 11-30.
  • Boissy, P., Choquette, S., Hamel, M., & Noury, N. (2007). User-based motion sensing and fuzzy logic for automated fall detection in older adults. Telemedicine and e-Health, 13(6), 683-694.
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  • Mallat, H. K., Yared, R., & Abdulrazak, B. (2015, May). Assistive Technology for Risks Affecting Elderly People in Outdoor Environment. In ICT4AgeingWell (pp. 5-16). Accessed https://www.researchgate.net/profile/Rami_Yared/
  • Maresova, P., Tomsone, S., Lameski, P., Madureira, J., Mendes, A., Zdravevski, E., Chorbev, I., Trajkovik, V., Ellen, M. & Rodile, K. (2018). Technological Solutions for Older People with Alzheimer's Disease. Current Alzheimer Research, 15(10), 975-983.
  • Meacham, S., & Phalp, K. (2016). Requirements engineering methods for an Internet of Things application: fall-detection for ambient assisted living. BCS SQM/Inspire Conference. Accessed https://www. researchgate. net/publication/30938535
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  • Moore, P., Thomas, A., Tadros, G., Xhafa, F., & Barolli, L. (2013). Detection of the onset of agitation in patients with dementia: real-time monitoring and the application of big-data solutions. International Journal of Space-Based and Situated Computing, 3(3), 136-154.
  • Moosavi, S. R., Rahmani, A. M., Westerlund, T., Yang, G., Liljeberg, P., & Tenhunen, H. (2014, November). Pervasive health monitoring based on internet of things: Two case studies. In Wireless Mobile Communication and Healthcare (Mobihealth), 2014 EAI 4th International Conference on (pp. 275-278). IEEE.
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  • Nieto-Riveiro, L., Groba, B., Miranda, M. C., Concheiro, P., Pazos, A., Pousada, T., & Pereira, J. (2018). Technologies for participatory medicine and health promotion in the elderly population. Medicine, 97(20), 1-7.
  • Panicker, N. V., & Kumar, S. (2015, October). Design of a telemonitoring system for detecting falls of the elderly. In Green Computing and Internet of Things (ICGCIoT), 2015 International Conference on (pp. 800-803). IEEE. Accessed https://ieeexplore.ieee.org/abstract/document/7380572
  • Pantzar, M., & Ruckenstein, M. (2015). The heart of everyday analytics: emotional, material and practical extensions in self-tracking market. Consumption Markets & Culture, 18(1), 92-109.
  • Paré, G., Leaver, C., & Bourget, C. (2018). Diffusion of the Digital Health Self-Tracking Movement in Canada: Results of a National Survey. Journal of Medical Internet Research, 20(5), e177.
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Toplam 95 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Derleme Makaleler
Yazarlar

Ulaş Başar Gezgin 0000-0002-6075-3501

Alper Yaman Bu kişi benim 0000-0003-1767-4020

Yayımlanma Tarihi 30 Haziran 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 1 Sayı: 1

Kaynak Göster

APA Gezgin, U. B., & Yaman, A. (2019). Assisted Aging: The Future Confluence of Gerontology, Internet of Things and Psychological AI. İzmir Sosyal Bilimler Dergisi, 1(1), 14-24.
İzmir Sosyal Bilimler Dergisi © 2019
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tarafından taranmaktadır.

Yayıncı
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