Effects of architectural space design on predicting turning in daily life

Effects of architectural space design on predicting turning in daily life

Yurie Matsunami, Ryosuke Motoyama, Mikita Miyaguchi, Masayoshi Kondou, Ami Ogawa

download PDF

Abstract. In recent years, the diversification of lifestyles and the increase in the number of elderly single-person households have increased the need to introduce robots and sensors into living spaces to control living spaces appropriately for individuals. To realize these goals, it is necessary to predict people’s non-steady motions which is one of the challenges in introducing robots into living spaces. In response, we have conducted research on motion prediction systems using robots and sensors. These studies will contribute to the realization of safe and comfortable architectural spaces by introducing robots into living spaces and collaborating with various space controls such as automatic doors and lighting. In this study, we focused on turning related to walking, which is the most basic motion in activities of daily living. As turning is a non-steady motion greatly affected by aging and disease, it is difficult to predict while is highly useful as a health indicator. Previous studies have suggested that architectural space design can influence the prediction of turning, but the actual effects are not clear because these studies were conducted only under highly constrained conditions in a laboratory environment. Thus, existing systems for predicting turning have not been validated in daily living environments due to issues such as instructions of motions to participants, limitations of natural motions because of contact sensors, and validation in experimental environments that are specially prepared to ensure reproducibility. Therefore, the purpose of this study was to introduce our sensing systems into actual living spaces and to validate our turning prediction system using acquired data on participants’ natural motion. In addition, the influence of architectural space design on predicting turning was clarified by conducting an experiment at a T-junction with an open space and a crossroad with poor visibility. In this study, an office space was selected as the experimental field as a living space to verify the feasibility of our turning prediction system.

Keywords
Motion Prediction, Turning, Architectural Space Design, Motion Capture System, Azure Kinect DK

Published online 3/30/2023, 8 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA

Citation: Yurie Matsunami, Ryosuke Motoyama, Mikita Miyaguchi, Masayoshi Kondou, Ami Ogawa, Effects of architectural space design on predicting turning in daily life, Materials Research Proceedings, Vol. 27, pp 127-134, 2023

DOI: https://doi.org/10.21741/9781644902455-16

The article was published as article 16 of the book Structural Health Monitoring

Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

References
[1] Glaister, B.C., Bernatz, G.C., Klute, G.K., Orendurff, M.S.: Video task analysis of turning during activities of daily living, Gait & posture, 2007, 25.2: 289-294. https://doi.org/10.1016/j.gaitpost.2006.04.003
[2] AKRAM, Sakineh B.; FRANK, James S.; CHENOURI, Shojaeddin. Turning behavior in healthy older adults: is there a preference for step versus spin turns?. Gait & posture, 2010, 31.1: 23-26. https://doi.org/10.1016/j.gaitpost.2009.08.238
[3] Hase K, Stein RB.: Turning strategies during human walking, Journal of neurophysiology, 1999, 81.6: 2914-2922. https://doi.org/10.1152/jn.1999.81.6.2914
[4] Lamontagne, Anouk, Caroline Paquette, and Joyce Fung.: Stroke Affects the Coordination of Gaze and Posture During Preplanned Turns While Walking. Neurorehabil Neural Repair 2007; 21: 62-67. https://doi.org/10.1177/1545968306290822
[5] Silsupadol, P., Siu, K. C., Shumway-Cook, A., & Woollacott, M. H.: Training of balance under single-and dual-task conditions in older adults with balance impairment. Physical therapy, 2006, 86.2: 269-281. https://doi.org/10.1093/ptj/86.2.269
[6] IMAEDA, S., SON, B., UCHIYAMA, E., TANAKA, T., SUTHUTVORAVUT, U., SUMIKAWA, U., BABA, A., IIJIMA, K., and OTSUKI, T.: The Measures Against Fall Prevention at Home By Multidisciplinary Specialists For Elderly People Who experienced Fall And Femoral Fractures Based On Their Environmental Changes <Part 1>:To Clarify the Architectural Factors On Reasons Of Falls At Home, Journal of Architecture and Planning (Transactions of AIJ), 2020, 85.773: 1387-1395.(in Japanese). https://doi.org/10.3130/aija.85.1387
[7] CLARK, David J., Rose, D. K., Ring, S. A., & Porges, E. C.: Utilization of central nervous system resources for preparation and performance of complex walking tasks in older adults. Frontiers in aging neuroscience, 2014, 6: 217. https://doi.org/10.3389/fnagi.2014.00217
[8] J. Martinez, M.J. Black, J. Romero, On human motion prediction using recurrent neural networks, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 2891-2900. https://doi.org/10.1109/CVPR.2017.497
[9] Fragkiadaki, K., Levine, S., Felsen, P., Malik, J.: Recurrent network models for human dynamics, In: Proceedings of the IEEE international conference on computer vision, 2015. P. 4346-4354. https://doi.org/10.1109/ICCV.2015.494
[10] Motoyama, R., Matsunami, Y., Miyaguchi, M., Kondo, M., Ogawa, A., Mita, A.: Analysis and real-time prediction of turning movements during walking assuming activities of daily living, Summaries of Technical Papers of Annual Meeting, Architectural Institute of Japan, Information Systems Technology, 2022, 11111 (in Japanese)
[11] Sugimoto, N., Ogawa, A., Mita, A.: Prediction of walking turns focusing on the center of gravity, AIJ Journal of Technology and Design, 2022, 28.68: 510-514. (in Japanese). https://doi.org/10.3130/aijt.28.510
[12] Takeda, K., Ogawa, A., Mita, A.: Prediction of 90-degree turn using kinematic parameters for implementation of home robot, Journal of Environmental Engineering (Transactions of AIJ) , 2020, 85.778: 1027-1036. (in Japanese). https://doi.org/10.3130/aije.85.1027
[13] Ulrich, B., Santos, A. N., Jolles, B. M., Benninger, D. H., & Favre, J.: Gait events during turning can be detected using kinematic features originally proposed for the analysis of straight-line walking, Journal of biomechanics, 2019, 91: 69-78. https://doi.org/10.1016/j.jbiomech.2019.05.006