Walk-IT: An Open-Source Modular Low-Cost Smart Rollator

被引:9
作者
Fernandez-Carmona, Manuel [1 ]
Ballesteros, Joaquin [2 ]
Diaz-Boladeras, Marta [3 ]
Parra-Llanas, Xavier [3 ]
Urdiales, Cristina [1 ]
Manuel Gomez-de-Gabriel, Jesus [4 ]
机构
[1] Univ Malaga, Elect Technol Dept, Complejo Tecnol, Ingn Sistemas Integrados Grp, Malaga 29071, Spain
[2] Univ Malaga, Dept Comp Sci & Programming Languages, Complejo Tecnol, ITIS Software, Malaga 29071, Spain
[3] Tech Univ Catalonia UPC, Tech Res Ctr Dependency Care & Autonomous Living, Barcelona 08800, Spain
[4] Univ Malaga UMA, Syst Engn & Automat Dept, Malaga 29071, Spain
关键词
rehabilitation robotics; assistive technology; smart rollator; gait analysis; PARTIAL WEIGHT-BEARING; GAIT DISTURBANCES; REHABILITATION; PARAMETERS; SYSTEM; AGE;
D O I
10.3390/s22062086
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Rollators are widely used in clinical rehabilitation for gait assessment, but gait analysis usually requires a great deal of expertise and focus from medical staff. Smart rollators can capture gait parameters autonomously while avoiding complex setups. However, commercial smart rollators, as closed systems, can not be modified; plus, they are often expensive and not widely available. This work presents a low cost open-source modular rollator for monitorization of gait parameters and support. The whole system is based on commercial components and its software architecture runs over ROS2 to allow further customization and expansion. This paper describes the overall software and hardware architecture and, as an example of extended capabilities, modules for monitoring dynamic partial weight bearing and for estimation of spatiotemporal gait parameters of clinical interest. All presented tests are coherent from a clinical point of view and consistent with input data.
引用
收藏
页数:16
相关论文
共 39 条
[31]   Neurological gait disorders in elderly people: clinical approach and classification [J].
Snijders, Anke H. ;
van de Warrenburg, Bart P. ;
Giladi, Nir ;
Bloem, Bastiaan R. .
LANCET NEUROLOGY, 2007, 6 (01) :63-74
[32]  
Thomas D., 2014, ROSCON CHICAGO 2014, DOI [10.36288/ROSCon2014-900183, DOI 10.36288/ROSCON2014-900183]
[34]  
Watanabe S, 2020, IEEE/SICE I S SYS IN, P1187, DOI [10.1109/SII46433.2020.9025977, 10.1109/sii46433.2020.9025977]
[35]   Validity of the GAITRite® walkway system for the measurement of averaged and individual step parameters of gait [J].
Webster, KE ;
Wittwer, JE ;
Feller, JA .
GAIT & POSTURE, 2005, 22 (04) :317-321
[36]   Detection of the onset of gait initiation using kinematic sensors and EMG in transfemoral amputees [J].
Wentink, E. C. ;
Schut, V. G. H. ;
Prinsen, E. C. ;
Rietman, J. S. ;
Veltink, P. H. .
GAIT & POSTURE, 2014, 39 (01) :391-396
[37]  
Woolley S M, 2001, Top Stroke Rehabil, V7, P1
[38]   Infrared gait recognition based on wavelet transform and support vector machine [J].
Xue, Zhaojun ;
Ming, Dong ;
Song, Wei ;
Wan, Baikun ;
Jin, Shijiu .
PATTERN RECOGNITION, 2010, 43 (08) :2904-2910
[39]   Two simple methods for determining gait events during treadmill and overground walking using kinematic data [J].
Zeni, J. A., Jr. ;
Richards, J. G. ;
Higginson, J. S. .
GAIT & POSTURE, 2008, 27 (04) :710-714