Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics 2014
DOI: 10.5220/0005058001270135
|View full text |Cite
|
Sign up to set email alerts
|

Development of Gait Measurement Robot for Prevention of Falls in the Elderly

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
3
0

Year Published

2015
2015
2024
2024

Publication Types

Select...
3
1
1

Relationship

1
4

Authors

Journals

citations
Cited by 6 publications
(3 citation statements)
references
References 14 publications
0
3
0
Order By: Relevance
“…A comprehensive review of the applications of stationary depth imaging sensors in elderly care, including movement analysis and balance training, can be found in Webster and Celik ( 2014 ). RGB-D cameras (Stone and Skubic, 2011 ; Gabel et al, 2012 ; Clark et al, 2013 ) and laser range sensors (LRS) (Pallejà et al, 2009 ; Yorozu et al, 2014 ) can estimate a basic set of gait parameters, but they share some of the drawbacks of optical motion capture systems, for example, constrained workspaces and occlusions. Stationary cameras also require costly modifications to an individual’s home, and their acceptance is hampered by users’ privacy concerns.…”
Section: Introductionmentioning
confidence: 99%
“…A comprehensive review of the applications of stationary depth imaging sensors in elderly care, including movement analysis and balance training, can be found in Webster and Celik ( 2014 ). RGB-D cameras (Stone and Skubic, 2011 ; Gabel et al, 2012 ; Clark et al, 2013 ) and laser range sensors (LRS) (Pallejà et al, 2009 ; Yorozu et al, 2014 ) can estimate a basic set of gait parameters, but they share some of the drawbacks of optical motion capture systems, for example, constrained workspaces and occlusions. Stationary cameras also require costly modifications to an individual’s home, and their acceptance is hampered by users’ privacy concerns.…”
Section: Introductionmentioning
confidence: 99%
“…In the real-world, the robot has to estimate the human's position and velocity when applying the proposed method. Therefore, the robot equips with leg detection using an LRF and estimates of the human's position and velocity by the Kalman filter [27,28].…”
Section: Methodsmentioning
confidence: 99%
“…(1) First, the positions of the obstacles and personal space [22] are calculated by human's position and velocity [27,28], and these areas are set as G occupied as shown in Fig. 2(b).…”
Section: Calculation Of Distance Values Considering Personal Spacementioning
confidence: 99%