Design strategies to improve patient motivation during robot-aided rehabilitation

BackgroundMotivation is an important factor in rehabilitation and frequently used as a determinant of rehabilitation outcome. Several factors can influence patient motivation and so improve exercise adherence. This paper presents the design of two robot devices for use in the rehabilitation of upper limb movements, that can motivate patients during the execution of the assigned motor tasks by enhancing the gaming aspects of rehabilitation. In addition, a regular review of the obtained performance can reinforce in patients' minds the importance of exercising and encourage them to continue, so improving their motivation and consequently adherence to the program. In view of this, we also developed an evaluation metric that could characterize the rate of improvement and quantify the changes in the obtained performance.MethodsTwo groups (G1, n = 8 and G2, n = 12) of patients with chronic stroke were enrolled in a 3-week rehabilitation program including standard physical therapy (45 min. daily) plus treatment by means of robot devices (40 min., twice daily) respectively for wrist (G1) and elbow-shoulder movements (G2). Both groups were evaluated by means of standard clinical assessment scales and the new robot measured evaluation metric. Patients' motivation was assessed in 9/12 G2 patients by means of the Intrinsic Motivation Inventory (IMI) questionnaire.ResultsBoth groups reduced their motor deficit and showed a significant improvement in clinical scales and the robot measured parameters. The IMI assessed in G2 patients showed high scores for interest, usefulness and importance subscales and low values for tension and pain subscales.ConclusionThanks to the design features of the two robot devices the therapist could easily adapt training to the individual by selecting different difficulty levels of the motor task tailored to each patient's disability. The gaming aspects incorporated in the two rehabilitation robots helped maintain patients' interest high during execution of the assigned tasks by providing feedback on performance. The evaluation metric gave a precise measure of patients' performance and thus provides a tool to help therapists promote patient motivation and hence adherence to the training program.

[1]  A. Fugl-Meyer,et al.  The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. , 1975, Scandinavian journal of rehabilitation medicine.

[2]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[3]  N. Mayo Patient compliance: practical implications for physical therapists. A review of the literature. , 1978, Physical therapy.

[4]  N. Oldridge Compliance and exercise in primary and secondary prevention of coronary heart disease: a review. , 1982, Preventive medicine.

[5]  R. Ryan,et al.  Control and information in the intrapersonal sphere: An extension of cognitive evaluation theory. , 1982 .

[6]  M. Becker Patient adherence to prescribed therapies. , 1985, Medical care.

[7]  R. Ryan,et al.  Intrinsic motivation and the effects of self-consciousness, self-awareness, and ego-involvement: An investigation of internally controlling styles , 1985 .

[8]  E. Hamrin,et al.  Evaluation of functional capacity after stroke as a basis for active intervention. Validation of a modified chart for motor capacity assessment. , 1988, Scandinavian journal of rehabilitation medicine.

[9]  Terry E. Duncan,et al.  Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: a confirmatory factor analysis. , 1989, Research quarterly for exercise and sport.

[10]  Ellen L. Lewis,et al.  Facilitating Treatment Adherence: A Practitioner’s Guidebook , 1989 .

[11]  E. Deci,et al.  Ego-involved persistence: When free-choice behavior is not intrinsically motivated , 1991 .

[12]  J. Sabari,et al.  Motor learning concepts applied to activity-based intervention with adults with hemiplegia. , 1991, The American journal of occupational therapy : official publication of the American Occupational Therapy Association.

[13]  E. Deci,et al.  Facilitating internalization: the self-determination theory perspective. , 1994, Journal of personality.

[14]  N. Hogan,et al.  Robot-aided neurorehabilitation. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[15]  M. Friedrich,et al.  Combined exercise and motivation program: effect on the compliance and level of disability of patients with chronic low back pain: a randomized controlled trial. , 1998, Archives of physical medicine and rehabilitation.

[16]  C. Skinner,et al.  Factors influencing compliance with home exercise programs among patients with upper-extremity impairment. , 1999, The American journal of occupational therapy : official publication of the American Occupational Therapy Association.

[17]  N. Hogan,et al.  A novel approach to stroke rehabilitation , 2000, Neurology.

[18]  C. Wolfe,et al.  Qualitative analysis of stroke patients' motivation for rehabilitation , 2000, BMJ : British Medical Journal.

[19]  H. F. Machiel van der Loos,et al.  Development of robots for rehabilitation therapy: the Palo Alto VA/Stanford experience. , 2000, Journal of rehabilitation research and development.

[20]  K.,et al.  Reliability of measurements of muscle tone and muscle power in stroke patients. , 2000, Age and ageing.

[21]  J. Donovan,et al.  Why don't patients do their exercises? Understanding non-compliance with physiotherapy in patients with osteoarthritis of the knee , 2001, Journal of epidemiology and community health.

[22]  C. Burgar,et al.  Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. , 2002, Archives of physical medicine and rehabilitation.

[23]  C. Wolfe,et al.  The Concept of Patient Motivation: A Qualitative Analysis of Stroke Professionals’ Attitudes , 2002, Stroke.

[24]  M.Q.-H. Meng,et al.  Development of a robotic device for facilitating learning by children who have severe disabilities , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[25]  N. Hogan,et al.  Movement Smoothness Changes during Stroke Recovery , 2002, The Journal of Neuroscience.

[26]  William S. Harwin,et al.  Upper Limb Robot Mediated Stroke Therapy—GENTLE/s Approach , 2003, Auton. Robots.

[27]  S. Hesse,et al.  Robot-assisted arm trainer for the passive and active practice of bilateral forearm and wrist movements in hemiparetic subjects. , 2003, Archives of physical medicine and rehabilitation.

[28]  P. Morasso,et al.  Trajectory formation and handwriting: A computational model , 1982, Biological Cybernetics.

[29]  W. Rymer,et al.  Assessment of Active and Passive Restraint During Guided Reaching After Chronic Brain Injury , 1999, Annals of Biomedical Engineering.

[30]  N. Hogan,et al.  Robotic therapy for chronic motor impairments after stroke: Follow-up results. , 2004, Archives of physical medicine and rehabilitation.

[31]  Ferdinando A. Mussa-Ivaldi,et al.  Robot-assisted adaptive training: custom force fields for teaching movement patterns , 2004, IEEE Transactions on Biomedical Engineering.

[32]  Silvestro Micera,et al.  A Simple Robotic System for Neurorehabilitation , 2005, Auton. Robots.

[33]  S. Micera,et al.  Robotic techniques for upper limb evaluation and rehabilitation of stroke patients , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[34]  Maarten J. IJzerman,et al.  Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. , 2006, Journal of rehabilitation research and development.

[35]  M.J. Johnson,et al.  Collaborative Tele-rehabilitation: A Strategy for Increasing Engagement , 2006, The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006. BioRob 2006..