Kosuke Hirayama
ABSTRACT
We have been developing "Facial expression sensing service" for emotional analysis and quantitative evaluation of care based on subtle facial movements and conducted a preliminary experiment about its practicality. In this research, focusing both obtaining facial expression data and searching for an efficient care method, to elderly people can activate themselves and relieve their stress, we have developed "Video player service" that can easily play videos and automatically collect facial expression data. After developing the service, we have asked people who engage in elderly care to try it and obtained feedback. As a result, we received favorable comments for the usefulness of the service, and we were able to get facial expression data for four people.
- Elder Care Alliance. [n.d.]. Benefits of Reminiscence Therapy. https://eldercarealliance.org/blog/benefits-reminiscence-therapy/. accessed August 15, 2020.Google Scholar
- P. Ekman and W. V Friesen. 1975. Unmasking the Face. Malor Books.Google Scholar
- Headquarters for Japan's Economic Revitalization (No.26). [n.d.]. Future investment strategy (2017). http://www.kantei.go.jp/jp/singi/keizaisaisei/dai26/siryou.pdf.Google Scholar
- Kosuke Hirayama, Sachio Saiki, Masahide Nakamura, and Kiyoshi Yasuda. 2020. Capturing User-defined Facial Features for Scientific Evidence of Elderly Care. In The 2020 International Workshop on Pervasive Information Flow (PerFlow'20), Held in conjunction with the 18th Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2020). 35--40.Google ScholarCross Ref
- International Organization for Standardization. 2011. Systems and software Quality Requirements and Evaluation (SQuaRE). https://www.iso.org/standard/35733.html/.Google Scholar
- Davis E. King. 2009. Dlib-ml: A Machine Learning Toolkit. Journal of Machine Learning Research 10 (2009), 1755--1758. Google ScholarDigital Library
- A. Nakazawa and M. Honda. 2019. First-Person Camera System to Evaluate Tender Dementia-Care Skill. In 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW). 4435--4442.Google Scholar
- Julia O'Rourke, Fiona Tobin, Susan O'Callaghan, Rebecca Sowman, and DR Collins. 2011. 'YouTube': a useful tool for reminiscence therapy in dementia? Age and Ageing 40, 6 (08 2011), 742--744. https://doi.org/10.1093/ageing/afr100arXiv:https://academic.oup.com/ageing/article-pdf/40/6/742/98976/afr100.pdfGoogle Scholar
- Arashi Sako, Sachio Saiki, Masahide Nakamura, and Kiyoshi Yasuda. 2018. Developing Face Emotion Tracker for Quantitative Evaluation of Care Effects. In Digital Human Modeling 2018 (DHM 2018), Held as Part of HCI International 2018, Vol. LNCS 10917. 513--526. Las Vegas, USA.Google ScholarCross Ref
- Kazunori Sato, Kazuyuki Sugino, and Takashi Hayashi. 2010. Development of an objective evaluation method for the nursing-care education based on facial expression analysis. Medical and health science research: Bulletin of Tsukuba International University 1 (2010), 163--170.Google Scholar
- Seiki Tokunaga, Kazunari Tamamizu, Sachio Saiki, Masahide Nakamura, and Kiyoshi Yasuda. 2016. VirtualCareGiver: Personalized Smart Elderly Care. International Journal of Software Innovation (IJSI) 5, 1 (Oct 2016), 30--43. http://www.igi-global.com/journals/abstract-announcement/158780.Google Scholar
- Charles Tyack, Paul M. Camic, Michael James Heron, and Sabina Hulbert. 2017. Viewing Art on a Tablet Computer: A Well-Being Intervention for People With Dementia and Their Caregivers. Journal of Applied Gerontology 36, 7 (2017), 864--894. https://doi.org/10.1177/0733464815617287arXiv:https://doi.org/10.1177/0733464815617287 PMID: 26675353.Google ScholarCross Ref
- Bob Woods, Laura O'Philbin, Emma M Farrell, Aimee E Spector, and Martin Orrell. 2018. Reminiscence therapy for dementia. The Cochrane database of systematic reviews 3, 3 (2018).Google Scholar
Index Terms
- Evaluating Video Playing Application for Elderly People at Home by Facial Expression Sensing Service
Recommendations
Recognizing Action Units for Facial Expression Analysis
Most automatic expression analysis systems attempt to recognize a small set of prototypic expressions, such as happiness, anger, surprise, and fear. Such prototypic expressions, however, occur rather infrequently. Human emotions and intentions are more ...
Using Data Mining Techniques to Analyze Facial Expression Motion Vectors
Dynamics of Information SystemsAbstractAutomatic recognition of facial expressions is a common problem in human-computer interaction. While humans can recognize facial expressions very easily, machines cannot do it as easily as humans. Analyzing facial changes during facial expressions ...
Dynamics of facial expression: recognition of facial actions and their temporal segments from face profile image sequences
Automatic analysis of human facial expression is a challenging problem with many applications. Most of the existing automated systems for facial expression analysis attempt to recognize a few prototypic emotional expressions, such as anger and ...
Comments