Dual-task performance assessment robot

Ayanori Yorozu, Ayumi Tanigawa, Masaki Takahashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, dual-task performance assessment robot (DAR) using projection is developed. Falling is a common problem in the growing elderly population. Fall-risk assessment systems have proven to be helpful in community-based fall prevention programs. One of the risk factors of falling is the deterioration of a person's dual-task performance. For example, gait training, which enhances both motor and cognitive functions, is a multi-target stepping task (MTST), in which participants step on assigned colored targets. To evaluate the dual-task performance during MTST in human living space, projection mapping and robot navigation to maintain a safe distance from the participant are key technologies. Projection mapping is used to evaluate the long-distance dual-task performance, where MTST images are displayed on the floor by the moving DAR. To evaluate the accuracy of the projected target position, experiments for MTST projection using the moving DAR and video analysis are carried out. Additionally, to verify the validity of the MTST by the moving DAR at a constant speed, experiments with several young participants are carried out.

Original languageEnglish
Title of host publicationIROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6929-6934
Number of pages6
Volume2017-September
ISBN (Electronic)9781538626825
DOIs
Publication statusPublished - 2017 Dec 13
Event2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017 - Vancouver, Canada
Duration: 2017 Sep 242017 Sep 28

Other

Other2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017
CountryCanada
CityVancouver
Period17/9/2417/9/28

Fingerprint

Robots
Risk assessment
Deterioration
Navigation
Experiments

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Cite this

Yorozu, A., Tanigawa, A., & Takahashi, M. (2017). Dual-task performance assessment robot. In IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems (Vol. 2017-September, pp. 6929-6934). [8206617] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS.2017.8206617

Dual-task performance assessment robot. / Yorozu, Ayanori; Tanigawa, Ayumi; Takahashi, Masaki.

IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems. Vol. 2017-September Institute of Electrical and Electronics Engineers Inc., 2017. p. 6929-6934 8206617.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Yorozu, A, Tanigawa, A & Takahashi, M 2017, Dual-task performance assessment robot. in IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems. vol. 2017-September, 8206617, Institute of Electrical and Electronics Engineers Inc., pp. 6929-6934, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017, Vancouver, Canada, 17/9/24. https://doi.org/10.1109/IROS.2017.8206617
Yorozu A, Tanigawa A, Takahashi M. Dual-task performance assessment robot. In IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems. Vol. 2017-September. Institute of Electrical and Electronics Engineers Inc. 2017. p. 6929-6934. 8206617 https://doi.org/10.1109/IROS.2017.8206617
Yorozu, Ayanori ; Tanigawa, Ayumi ; Takahashi, Masaki. / Dual-task performance assessment robot. IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems. Vol. 2017-September Institute of Electrical and Electronics Engineers Inc., 2017. pp. 6929-6934
@inproceedings{8ebd97ea49f14d098b5a4c02798e2327,
title = "Dual-task performance assessment robot",
abstract = "In this paper, dual-task performance assessment robot (DAR) using projection is developed. Falling is a common problem in the growing elderly population. Fall-risk assessment systems have proven to be helpful in community-based fall prevention programs. One of the risk factors of falling is the deterioration of a person's dual-task performance. For example, gait training, which enhances both motor and cognitive functions, is a multi-target stepping task (MTST), in which participants step on assigned colored targets. To evaluate the dual-task performance during MTST in human living space, projection mapping and robot navigation to maintain a safe distance from the participant are key technologies. Projection mapping is used to evaluate the long-distance dual-task performance, where MTST images are displayed on the floor by the moving DAR. To evaluate the accuracy of the projected target position, experiments for MTST projection using the moving DAR and video analysis are carried out. Additionally, to verify the validity of the MTST by the moving DAR at a constant speed, experiments with several young participants are carried out.",
author = "Ayanori Yorozu and Ayumi Tanigawa and Masaki Takahashi",
year = "2017",
month = "12",
day = "13",
doi = "10.1109/IROS.2017.8206617",
language = "English",
volume = "2017-September",
pages = "6929--6934",
booktitle = "IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Dual-task performance assessment robot

AU - Yorozu, Ayanori

AU - Tanigawa, Ayumi

AU - Takahashi, Masaki

PY - 2017/12/13

Y1 - 2017/12/13

N2 - In this paper, dual-task performance assessment robot (DAR) using projection is developed. Falling is a common problem in the growing elderly population. Fall-risk assessment systems have proven to be helpful in community-based fall prevention programs. One of the risk factors of falling is the deterioration of a person's dual-task performance. For example, gait training, which enhances both motor and cognitive functions, is a multi-target stepping task (MTST), in which participants step on assigned colored targets. To evaluate the dual-task performance during MTST in human living space, projection mapping and robot navigation to maintain a safe distance from the participant are key technologies. Projection mapping is used to evaluate the long-distance dual-task performance, where MTST images are displayed on the floor by the moving DAR. To evaluate the accuracy of the projected target position, experiments for MTST projection using the moving DAR and video analysis are carried out. Additionally, to verify the validity of the MTST by the moving DAR at a constant speed, experiments with several young participants are carried out.

AB - In this paper, dual-task performance assessment robot (DAR) using projection is developed. Falling is a common problem in the growing elderly population. Fall-risk assessment systems have proven to be helpful in community-based fall prevention programs. One of the risk factors of falling is the deterioration of a person's dual-task performance. For example, gait training, which enhances both motor and cognitive functions, is a multi-target stepping task (MTST), in which participants step on assigned colored targets. To evaluate the dual-task performance during MTST in human living space, projection mapping and robot navigation to maintain a safe distance from the participant are key technologies. Projection mapping is used to evaluate the long-distance dual-task performance, where MTST images are displayed on the floor by the moving DAR. To evaluate the accuracy of the projected target position, experiments for MTST projection using the moving DAR and video analysis are carried out. Additionally, to verify the validity of the MTST by the moving DAR at a constant speed, experiments with several young participants are carried out.

UR - http://www.scopus.com/inward/record.url?scp=85041943608&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85041943608&partnerID=8YFLogxK

U2 - 10.1109/IROS.2017.8206617

DO - 10.1109/IROS.2017.8206617

M3 - Conference contribution

AN - SCOPUS:85041943608

VL - 2017-September

SP - 6929

EP - 6934

BT - IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems

PB - Institute of Electrical and Electronics Engineers Inc.

ER -