A novel human-machine interface for guiding: The NeoASAS smart walker

In an aging society it is extremely important to develop devices, which can support and aid the elderly in their daily life. This demands tools that extend independent living and promote improved health. In this work it is proposed a new interface approach integrated into a walker. This interface is based on a force sensor and it is intended to extract the user's movement intentions. The interface is designed to be user-friendly, simple and intuitive, efficient and economic, meeting usability aspects and focused on a commercial implementation, but not being demanding at the user cognitive level. Preliminary sets of experiments were performed which showed the sensibility of the force sensor extract navigation commands from the user. These signals presented a higher frequency component that was attenuated by a Benedict-Bordner g-h filter. The presented methodology offers an effective cancelation of the undesired components from force sensor data, allowing the system to extract in real-time voluntary user's navigation commands. Based on this real-time identification of voluntary user's commands, an approach to the control architecture of the robotic walker is being developed, in order to obtain stable and safe user assisted locomotion.

[1]  T. Benedict,et al.  Synthesis of an optimal set of radar track-while-scan smoothing equations , 1962 .

[2]  Alan V. Oppenheim,et al.  Discrete-Time Signal Pro-cessing , 1989 .

[3]  Sebastian Thrun,et al.  A robotic walker that provides guidance , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[4]  E. Brookner.  Tracking and Kalman Filtering Made Easy , 1998 .

[5]  Nak Young Chong,et al.  Design and control of JAIST active robotic walker , 2010, Intell. Serv. Robotics.

[6]  Shane MacNamara,et al.  Personal Adaptive Mobility Aid for the Infirm and Elderly Blind , 1995, Assistive Technology and Artificial Intelligence.

[7]  Kenji Ishida,et al.  Adaptive controller for motion control of an omni-directional walker , 2010, 2010 IEEE International Conference on Mechatronics and Automation.

[8]  Makoto Shimojo,et al.  The Development of the Plantar Pressure Sensor Shoes for Gait Analysis , 2008, J. Robotics Mechatronics.

[9]  Kazuhiro Kosuge,et al.  Active type robotic mobility aid control based on passive behavior , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  José Luis Pons Rovira,et al.  Tremor Characterization - Algorithms for the Study of Tremor Time Series , 2008, BIOSIGNALS.

[11]  Kenneth M. Dawson-Howe,et al.  Evaluation of Robot Mobility Aid for the Elderly Blind , 1997 .

[12]  Robert Riener,et al.  Rehabilitation Robotics , 2013, Found. Trends Robotics.

[13]  Michael J. McDonald.  Active Research Topics in Human Machine Interfaces , 2000 .

[14]  W. Gharieb,et al.  Intelligent Robotic Walker Design , 2006 .

[15]  H. Hashimoto,et al.  Walker with hand haptic interface for spatial recognition , 2006, 9th IEEE International Workshop on Advanced Motion Control, 2006..

[16]  M. Hirvensalo,et al.  Mobility Difficulties and Physical Activity as Predictors of Mortality and Loss of Independence in the Community‐Living Older Population , 2000, Journal of the American Geriatrics Society.

[17]  Eduardo Rocon,et al.  Human–Robot Cognitive Interaction , 2008 .

[18]  J.V. Miro,et al.  A multi-stage shared control method for an intelligent mobility assistant , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..

[19]  Sean Graves,et al.  Effective Shared Control in Cooperative Mobility Aids , 2001, FLAIRS.

[20]  M. Boninger,et al.  Clinical evaluation of Guido robotic walker. , 2008, Journal of rehabilitation research and development.

[21]  Qixin Cao,et al.  Based on force sensing-controlled human-machine interaction system for walking assistant robot , 2010, 2010 8th World Congress on Intelligent Control and Automation.