TY - GEN
T1 - Proto-chair
T2 - 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020
AU - Eguchi, Soya
AU - Yazaki, Yukako
AU - Kato, Riku
AU - Arita, Yusaku
AU - Moriya, Takumi
AU - Tanaka, Hiroya
N1 - Funding Information:
This research is partially supported by COI(Center of Innovation) project “Kansei-Based Digital Fabrication (2013-2021)” led by Keio University.
Publisher Copyright:
© 2020 Owner/Author.
PY - 2020/4/25
Y1 - 2020/4/25
N2 - Public space/furniture are amongst the new domains to apply a data-driven approach of design intervention and improvements. Open space is essentially dynamic, livable and interactive. Various types of people spend time for various purposes. Therefore, the "Measure-Test-Refine" loop is applicable for improving open spaces gradually. In this research, we developed our original smart chair called "Proto-Chair" that can contribute to the new design method of public space. Our chair is made with 3D-printed soft auxetic patterns. It is morphable allowing users to sit in various ways. Also, our chair is equipped with two sensors, which collect data stream to distinguish four different states of the chair. Long-term sensor stream can be stored and used to refine the furniture. In this paper, we propose our concept, prototypes, sensing methods and results of experiments. We also introduce our future vision of a sensor-based public design platform.
AB - Public space/furniture are amongst the new domains to apply a data-driven approach of design intervention and improvements. Open space is essentially dynamic, livable and interactive. Various types of people spend time for various purposes. Therefore, the "Measure-Test-Refine" loop is applicable for improving open spaces gradually. In this research, we developed our original smart chair called "Proto-Chair" that can contribute to the new design method of public space. Our chair is made with 3D-printed soft auxetic patterns. It is morphable allowing users to sit in various ways. Also, our chair is equipped with two sensors, which collect data stream to distinguish four different states of the chair. Long-term sensor stream can be stored and used to refine the furniture. In this paper, we propose our concept, prototypes, sensing methods and results of experiments. We also introduce our future vision of a sensor-based public design platform.
KW - 3D printing
KW - Auxetic pattern
KW - Implicit interaction
KW - Morphing design
KW - Public furniture
UR - http://www.scopus.com/inward/record.url?scp=85090183963&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85090183963&partnerID=8YFLogxK
U2 - 10.1145/3334480.3383036
DO - 10.1145/3334480.3383036
M3 - Conference contribution
AN - SCOPUS:85090183963
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 25 April 2020 through 30 April 2020
ER -