A 6-DOF Gait Rehabilitation Robot With Upper and Lower Limb Connections That Allows Walking Velocity Updates on Various Terrains

This paper presents a 6-DOF gait rehabilitation robot that allows patients to update their walking velocity on various terrain types and navigate in virtual environments (VEs) through upper and lower limb connections. This robot is composed of an upper limb device, a sliding device, two footpad devices, and a body support system. The footpad device on the sliding device generates 3-DOF spatial motions on the sagittal plane for each foot. This allows the generation of various terrain types for diverse walking training. The upper limb device allows users to swing their arms naturally through the use of a simple pendulum link with a passive prismatic joint. Synchronized gait patterns for this robot are designed to represent a normal gait with upper and lower limb connections. To permit patients to walk at will, this robot allows walking velocity updates for various terrain types by estimating the interaction torques between the human and the upper limb device, and synchronizing the lower limb device with the upper limb device. In addition, the patient is able to navigate in VEs by generating turning commands with switches located in the handles of the upper limb device. Experimental results using a healthy subject show that the user can update the walking velocity on level ground, slopes, and stairs through upper and lower limb connections. In addition, the user could navigate in the VEs with walking velocity updates and turning input command allowing various rehabilitation training modes. During a pilot clinical test, a hemiplegic patient could use the suggested gait rehabilitation robot with a slow walking speed. The rehabilitation plan was also suggested for the patient and the possible therapeutic effects of the suggested rehabilitation robot system are discussed.

[1]  H Elftman,et al.  The function of the arms in walking , 1939 .

[2]  R. Stephenson.  A and V , 1962, The British journal of ophthalmology.

[3]  Dale A. Lawrence,et al.  Impedance control stability properties in common implementations , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[4]  R. Hinrichs.  Whole Body Movement: Coordination of Arms and Legs in Walking and Running , 1990 .

[5]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[6]  D. Winter.  Foot trajectory in human gait: a precise and multifactorial motor control task. , 1992, Physical therapy.

[7]  S. Simon.  Gait Analysis, Normal and Pathological Function. , 1993 .

[8]  P. Stratford,et al.  Measuring Physical Impairment and Disability With the Chedoke‐McMaster Stroke Assessment , 1993, Stroke.

[9]  M. Maležič,et al.  Restoration of gait in nonambulatory hemiparetic patients by treadmill training with partial body-weight support. , 1994, Archives of physical medicine and rehabilitation.

[10]  V. L. Nickel,et al.  Gait parameters following stroke: a practical assessment. , 1995, Journal of rehabilitation research and development.

[11]  E. Todorov,et al.  Virtual Environment Training Improves Motor Performance in Two Patients with Stroke: Case Report , 1999 .

[12]  B. Dobkin.  An Overview of Treadmill Locomotor Training with Partial Body Weight Support: A Neurophysiologically Sound Approach Whose Time Has Come for Randomized Clinical Trials , 1999 .

[13]  Hiroo Iwata,et al.  The Torus Treadmill: Realizing Locomotion in VEs , 1999, IEEE Computer Graphics and Applications.

[14]  S. Harkema,et al.  Locomotor training after human spinal cord injury: a series of case studies. , 2000, Physical therapy.

[15]  S. Hesse,et al.  A mechanized gait trainer for restoration of gait. , 2000, Journal of rehabilitation research and development.

[16]  R. van Emmerik,et al.  Resonant frequencies of arms and legs identify different walking patterns. , 2000, Journal of biomechanics.

[17]  S. Hesse,et al.  A mechanized gait trainer for restoring gait in nonambulatory subjects. , 2000, Archives of physical medicine and rehabilitation.

[18]  Grigore C. Burdea,et al.  A virtual-reality-based telerehabilitation system with force feedback , 2000, IEEE Transactions on Information Technology in Biomedicine.

[19]  C. M. Bastiaanse,et al.  Neuronal coordination of arm and leg movements during human locomotion , 2001, The European journal of neuroscience.

[20]  V. Dietz,et al.  Arm to leg coordination in humans during walking, creeping and swimming activities , 2001, Experimental Brain Research.

[21]  V. Dietz,et al.  Driven gait orthosis for improvement of locomotor training in paraplegic patients , 2001, Spinal Cord.

[22]  S. Hesse,et al.  Treadmill Training With Partial Body Weight Support and an Electromechanical Gait Trainer for Restoration of Gait in Subacute Stroke Patients: A Randomized Crossover Study , 2002, Stroke.

[23]  Jungwon Yoon,et al.  Design and analysis of a novel virtual walking machine , 2003, 11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2003. HAPTICS 2003. Proceedings..

[24]  Hiroo Iwata,et al.  Development of a gait rehabilitation system using a locomotion interface , 2003, Comput. Animat. Virtual Worlds.

[25]  E. Zehr,et al.  Regulation of Arm and Leg Movement during Human Locomotion , 2004, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[26]  Manfred Morari,et al.  Automatic gait-pattern adaptation algorithms for rehabilitation with a 4-DOF robotic orthosis , 2004, IEEE Transactions on Robotics and Automation.

[27]  J. Fung,et al.  Faster Is Better: Implications for Speed-Intensive Gait Training After Stroke , 2004, Stroke.

[28]  Masayoshi Kubo,et al.  Biomechanical mechanism for transitions in phase and frequency of arm and leg swing during walking , 2004, Biological Cybernetics.

[29]  Henry L. Lew,et al.  Stepping over obstacles to improve walking in individuals with poststroke hemiplegia. , 2004, Journal of rehabilitation research and development.

[30]  Daniel P. Ferris,et al.  Neural coupling between upper and lower limbs during recumbent stepping. , 2004, Journal of applied physiology.

[31]  Daniel P. Ferris,et al.  The effect of movement frequency on interlimb coupling during recumbent stepping. , 2005, Motor control.

[32]  Jörg Krüger,et al.  HapticWalker---a novel haptic foot device , 2005, TAP.

[33]  Grigore C. Burdea,et al.  Robotic mobility rehabilitation system using virtual reality , 2005 .

[34]  Maureen K. Holden,et al.  Virtual Environments for Motor Rehabilitation: Review , 2005, Cyberpsychology Behav. Soc. Netw..

[35]  M. Spong,et al.  Robot Modeling and Control , 2005 .

[36]  Roger Weber,et al.  Tools for understanding and optimizing robotic gait training. , 2006, Journal of rehabilitation research and development.

[37]  Daniel P. Ferris,et al.  Moving the Arms to Activate the Legs , 2006, Exercise and sport sciences reviews.

[38]  R. Riener,et al.  A Novel Mechatronic Body Weight Support System , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[39]  Sunil Kumar Agrawal,et al.  Gravity-Balancing Leg Orthosis and Its Performance Evaluation , 2006, IEEE Transactions on Robotics.

[40]  Jungwon Yoon,et al.  Reconfigurable ankle rehabilitation robot for various exercises , 2006 .

[41]  Jungwon Yoon,et al.  A Novel Locomotion Interface with Two 6-DOF Parallel Manipulators That Allows Human Walking on Various Virtual Terrains , 2006, Int. J. Robotics Res..

[42]  Jae-Hun Kim,et al.  Virtual Environment Training System for Rehabilitation of Stroke Patients with Unilateral Neglect: Crossing the Virtual Street , 2007, Cyberpsychology Behav. Soc. Netw..

[43]  R. Riener,et al.  A Novel Method for Automatic Treadmill Speed Adaptation , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[44]  Hector M. Garcia,et al.  Virtual Reality in Gait Rehabilitation , 2007 .

[45]  J.E. Deutsch,et al.  Technical and Patient Performance Using a Virtual Reality-Integrated Telerehabilitation System: Preliminary Finding , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[46]  H. van der Kooij,et al.  Design and Evaluation of the LOPES Exoskeleton Robot for Interactive Gait Rehabilitation , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[47]  Judith E. Deutsch,et al.  Robotics and Virtual Reality Applications in Mobility Rehabilitation , 2007 .

[48]  Robert Riener,et al.  Obstacle Crossing in a Virtual Environment with the Rehabilitation Gait Robot LOKOMAT , 2007, MMVR.

[49]  U. Croce,et al.  A kinematic and kinetic comparison of overground and treadmill walking in healthy subjects. , 2007, Gait & posture.

[50]  Yea-Ru Yang,et al.  Virtual reality-based training improves community ambulation in individuals with stroke: a randomized controlled trial. , 2008, Gait & posture.

[51]  J. Mehrholz,et al.  Gait training with the newly developed ‘LokoHelp’-system is feasible for non-ambulatory patients after stroke, spinal cord and brain injury. A feasibility study , 2008, Brain injury.

[52]  G. Burdea.  The role of haptics in physical rehabilitation , 2008 .

[53]  A. Mirelman,et al.  Effects of Training With a Robot-Virtual Reality System Compared With a Robot Alone on the Gait of Individuals After Stroke , 2009, Stroke.

[54]  S. Olney,et al.  A comparison of gait biomechanics and metabolic requirements of overground and treadmill walking in people with stroke. , 2009, Clinical biomechanics.

[55]  A. Schnider,et al.  Effect of different walking aids on walking capacity of patients with poststroke hemiparesis. , 2009, Archives of physical medicine and rehabilitation.

[56]  A. Lamontagne,et al.  The coordination of upper and lower limb movements during gait in healthy and stroke individuals. , 2009, Gait & posture.

[57]  Jungwon Yoon,et al.  A Planar Symmetric Walking Cancellation Algorithm for a Foot—Platform Locomotion Interface , 2010, Int. J. Robotics Res..

[58]  W. Marsden.  I and J , 2012 .