The “Beam-Me-In Strategy” – remote haptic therapist-patient interaction with two exoskeletons for stroke therapy

BackgroundWe present a robot-assisted telerehabilitation system that allows for haptic interaction between therapist and patient over distance. It consists of two arm therapy robots. Attached to one robot the therapists can feel on their own arm the limitations of the patient’s arm which is attached to the other robot. Due to the exoskeleton structure of the robot, movements can be performed in the three-dimensional space.MethodsFifteen physical and occupational therapists tested this strategy, named “Beam-Me-In”, while using an exoskeleton robot connected to a second exoskeleton robot in the same room used by the study experimenter. Furthermore, the therapists assessed the level of impairment of recorded and simulated arm movements. They quantified four typical impairments of stroke patients: reduced range of motion (active and passive), resistance to passive movement, a lack of ability to fractionate a movement, and disturbed quality of movement.ResultsOn a Likert Scale (0 to 5 points) therapists rated the “Beam-Me-In” strategy as a very useful medium (mode: 4 points) to evaluate a patient’s progress over time. The passive range of motion of the elbow joint was assessed with a mean absolute error of 4.9∘ (absolute precision error: 6.4∘). The active range of motion of the elbow was assessed with a mean absolute error of 4.9∘ (absolute precision error: 6.5∘). The resistance to passive movement (i.e. modified Tardieu Scale) and the lack of ability to fractionate a movement (i.e. quantification of pathological muscle synergies) was assessed with an inter-rater reliability of 0.930 and 0.948, respectively.ConclusionsThe “Beam-Me-In” strategy is a promising approach to complement robot-assisted movement training. It can serve as a platform to assess and identify abnormal movement patterns in patients. This is the first application of remote three-dimensional haptic assessmen t applied to telerehabilitation. Furthermore, the “Beam-Me-In” strategy has a potential to overcome barriers for therapists regarding robot-assisted telerehabilitation.

[1]  Marc Bolliger,et al.  Robots for Measurement/Clinical Assessment , 2012 .

[2]  C. Burgar,et al.  Evidence for strength imbalances as a significant contributor to abnormal synergies in hemiparetic subjects , 2003, Muscle & nerve.

[3]  Robert Riener,et al.  A robotic system to train activities of daily living in a virtual environment , 2011, Medical & Biological Engineering & Computing.

[4]  S. Hasson,et al.  The Modified Tardieu Scale for the measurement of elbow flexor spasticity in adult patients with hemiplegia , 2008, Brain injury.

[5]  A. Armstrong,et al.  Reliability of range-of-motion measurement in the elbow and forearm. , 1998, Journal of shoulder and elbow surgery.

[6]  Hao Chen,et al.  Components of information for multiple resolution comparison between maps that share a real variable , 2008, Environmental and Ecological Statistics.

[7]  G. Mead,et al.  Interventions for improving upper limb function after stroke. , 2014, The Cochrane database of systematic reviews.

[8]  Simona Crea,et al.  Technologically-advanced assessment of upper-limb spasticity: a pilot study. , 2018, European journal of physical and rehabilitation medicine.

[9]  Graham W. Taylor,et al.  Robotic pilot study for analysing spasticity: clinical data versus healthy controls , 2015, Journal of NeuroEngineering and Rehabilitation.

[10]  G. Johnson,et al.  A systematic review of the Tardieu Scale for the measurement of spasticity , 2006, Disability and rehabilitation.

[11]  J. Dewald,et al.  Abnormal joint torque patterns in the paretic upper limb of subjects with hemiparesis , 2001, Muscle & nerve.

[12]  Richard W. Bohannon.  Muscle strength and muscle training after stroke. , 2007, Journal of rehabilitation medicine.

[13]  Massimo Midiri,et al.  Comparison of US Strain Elastography and Entero-MRI to Typify the Mesenteric and Bowel Wall Changes during Crohn's Disease: A Pilot Study , 2017, BioMed research international.

[14]  Robert Riener,et al.  Robot-Assisted Arm Assessments in Spinal Cord Injured Patients: A Consideration of Concept Study , 2015, PloS one.

[15]  Maria Sandgren,et al.  Test-retest and inter-rater reliability of a method to measure wrist and finger spasticity. , 2013, Journal of rehabilitation medicine.

[16]  Hermano I Krebs,et al.  Rehabilitation robotics: pilot trial of a spatial extension for MIT-Manus , 2004, Journal of NeuroEngineering and Rehabilitation.

[17]  Julius P. A. Dewald,et al.  Involuntary paretic wrist/finger flexion forces and EMG increase with shoulder abduction load in individuals with chronic stroke , 2012, Clinical Neurophysiology.

[18]  Etienne Burdet,et al.  On the analysis of movement smoothness , 2015, Journal of NeuroEngineering and Rehabilitation.

[19]  Etienne Burdet,et al.  Robotic assessment of hand function with the HapticKnob , 2010 .

[20]  Peter Wolf,et al.  Teleoperation of two six-degree-of-freedom arm rehabilitation exoskeletons , 2015, 2015 IEEE International Conference on Rehabilitation Robotics (ICORR).

[21]  Mario Cortese,et al.  A Mechatronic System for Robot-Mediated Hand Telerehabilitation , 2015, IEEE/ASME Transactions on Mechatronics.

[22]  Yvan Petit,et al.  Validity of Goniometric Elbow Measurements: Comparative Study with a Radiographic Method , 2011, Clinical orthopaedics and related research.

[23]  Hans Forssberg,et al.  Sensitivity of the NeuroFlexor method to measure change in spasticity after treatment with botulinum toxin A in wrist and finger muscles. , 2014, Journal of rehabilitation medicine.

[24]  Alex Mihailidis,et al.  The development of an upper limb stroke rehabilitation robot: identification of clinical practices and design requirements through a survey of therapists , 2011, Disability and rehabilitation. Assistive technology.

[25]  Bernhard Elsner,et al.  Electromechanical and robot-assisted arm training for improving activities of daily living, arm function, and arm muscle strength after stroke. , 2018, The Cochrane database of systematic reviews.

[26]  Maurizio Corbetta,et al.  Neurological Principles and Rehabilitation of Action Disorders , 2011, Neurorehabilitation and neural repair.

[27]  Robert Riener,et al.  Control strategies for active lower extremity prosthetics and orthotics: a review , 2015, Journal of NeuroEngineering and Rehabilitation.

[28]  Janne M. Veerbeek,et al.  Effects of Robot-Assisted Therapy for the Upper Limb After Stroke , 2017, Neurorehabilitation and neural repair.

[29]  Peter Wolf,et al.  Making neurorehabilitation fun: Multiplayer training via damping forces balancing differences in skill levels , 2017, 2017 International Conference on Rehabilitation Robotics (ICORR).

[30]  Saleh M. Aloraini,et al.  Assessment of spasticity after stroke using clinical measures: a systematic review , 2015, Disability and rehabilitation.

[31]  Rita K Bode,et al.  Factors Influencing Therapists' Decision-Making in the Acceptance of New Technology Devices in Stroke Rehabilitation , 2011, American journal of physical medicine & rehabilitation.

[32]  Stefano Negrini,et al.  Hand Passive Mobilization Performed with Robotic Assistance: Acute Effects on Upper Limb Perfusion and Spasticity in Stroke Survivors , 2017, BioMed research international.

[33]  Robert Riener,et al.  ARMin III --arm therapy exoskeleton with an ergonomic shoulder actuation , 2009 .

[34]  T. Twitchell.  The restoration of motor function following hemiplegia in man. , 1951, Brain : a journal of neurology.

[35]  D. Cicchetti.  Guidelines, Criteria, and Rules of Thumb for Evaluating Normed and Standardized Assessment Instruments in Psychology. , 1994 .

[36]  G. Gard,et al.  An eye for movement quality: A phenomenological study of movement quality reflecting a group of physiotherapists' understanding of the phenomenon , 2008, Physiotherapy theory and practice.