Mechatronic treadmill for gait reeducation with control algorithm of treadmill speed adaptation

Different types of devices, from the simplest (medical walkers) to the most technologically advanced ones (mechatronic devices), are widely used to support the rehabilitation process for people who suffered strokes or have other disabilities—especially to enhance their mobility. This article presents a new mechatronic system for gait reeducation, which consists of two main components: training treadmill and body weight support system. The device is also equipped with sensors for measuring the rope inclination angle, rope tension and foot pressure on the ground. The transmission of measurement and control signals between the computer with control system and the electromechanical part of the device is realized by means of three real-time boards. This publication covers certain issues related to the device design process, integration of the main components, as well as the description of the developed treadmill speed adaptation algorithm and experimental verification of such control system. The speed of treadmill belt is adjusted by a feedback loop with a rope inclination angle measurement. Because of the kind of the connection of the treadmill (the control signals are sent to the buttons in the treadmill control panel) and related limitations, a proper conversion of the control signal was required, from a continuous one to a digital square wave signal with variable period. Developing an optimal treadmill speed control algorithm in this case was an interesting engineering challenge.

[1]  H. Barbeau,et al.  Body weight-supported treadmill training after stroke , 2001, Current atherosclerosis reports.

[2]  Jarosław Konieczny,et al.  Optimal control based on a modified quadratic performance index for systems disturbed by sinusoidal signals , 2015 .

[3]  Zahari Taha,et al.  The Control of a Lower Limb Exoskeleton for Gait Rehabilitation , 2017 .

[4]  Wei Meng,et al.  Recent development of mechanisms and control strategies for robot-assisted lower limb rehabilitation , 2015 .

[5]  Arkadiusz Mężyk,et al.  Mechatronic Device for Locomotor Training , 2016 .

[6]  Aleksander Gwiazda,et al.  Modelling of robotic work cells using agent based-approach , 2016 .

[7]  Tobias Nef,et al.  ZeroG: overground gait and balance training system. , 2011, Journal of rehabilitation research and development.

[8]  H. Barbeau,et al.  Optimal outcomes obtained with body-weight support combined with treadmill training in stroke subjects. , 2003, Archives of physical medicine and rehabilitation.

[9]  Karol Miadlicki,et al.  Ground plane estimation from sparse LIDAR data for loader crane sensor fusion system , 2017, 2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR).

[10]  Jaroslaw Smoczek,et al.  Fuzzy crane control with sensorless payload deflection feedback for vibration reduction , 2014 .

[11]  Jan Awrejcewicz,et al.  Analysis of stability of the human gait , 2015 .

[12]  Ming Cheng,et al.  Computational method for optimal control of switched systems with input and state constraints , 2017 .

[13]  A. Sherwood,et al.  Supported treadmill ambulation training after spinal cord injury: a pilot study. , 2001, Archives of physical medicine and rehabilitation.

[14]  J-Y Lee,et al.  A gait-assistive mobile robot based on a body weight support and autonomous path tracking system , 2012 .

[15]  R. Teasell,et al.  The Role of Task-Specific Training in Rehabilitation Therapies , 2005, Topics in stroke rehabilitation.

[16]  Thad W. Buster,et al.  Partial body weight support treadmill training speed influences paretic and non-paretic leg muscle activation, stride characteristics, and ratings of perceived exertion during acute stroke rehabilitation. , 2016, Human movement science.

[17]  J. Krakauer.  Motor learning: its relevance to stroke recovery and neurorehabilitation. , 2006, Current opinion in neurology.

[18]  Robert Michnik,et al.  The influence of frequency of visual disorders on stabilographic parameters. , 2016, Acta of bioengineering and biomechanics.

[19]  Candy Tefertiller,et al.  Efficacy of rehabilitation robotics for walking training in neurological disorders: a review. , 2011, Journal of rehabilitation research and development.

[20]  R. J. Gregor,et al.  Effects of training on the recovery of full-weight-bearing stepping in the adult spinal cat , 1986, Experimental Neurology.

[21]  Gabriel Mura,et al.  Numerical simulation of active track tensioning system for autonomous hybrid vehicle , 2017 .

[22]  S. Harkema,et al.  Locomotor training using body weight support on a treadmill improves mobility in persons with multiple sclerosis: a pilot study , 2007, Multiple sclerosis.

[23]  Matthew R. Scherer,et al.  Gait rehabilitation with body weight-supported treadmill training for a blast injury survivor with traumatic brain injury , 2007, Brain injury.

[24]  A. Wolf,et al.  Body weight unloading modifications on frontal plane joint moments, impulses and Center of Pressure during overground gait. , 2016, Clinical biomechanics.

[25]  Shin-ichiroh Yamamoto,et al.  Development of a body weight support system using pneumatic muscle actuators: Controlling and validation , 2016 .