Perceptual limits for a robotic rehabilitation environment using visual feedback distortion

Imperceptible visual distortion, in the form of a disguised progression of performance goals, may be a helpful addition to rehabilitation after stroke and other brain injuries. This paper describes work that has been done to lay the groundwork for testing this hypothesis. We have constructed and validated an experimental environment that provides controllable visual distortion and allows precise force and position measurements. To estimate the amount of visual distortion that should be imperceptible, we measured the limits for force and distance/position perception in our rehabilitation environment for young and elderly unimpaired subjects and for a single traumatic brain injury (TBI) patient. We found the Just Noticeable Difference (JND) for produced force to be 19.7% (0.296 N) and the JND for movement distance/finger position to be 13.0% (3.99 mm) for young subjects (ages 18-35). For elderly subjects (ages 61-80), the JND for force was measured to be 31.0% (0.619 N) and the JND for distance/position was 16.1% (5.01 mm). JNDs of 46.0% (0.920 N) and 45.0% (14.8 mm) were found for the motor-impaired individual. In addition, a subject's rating of effort was found to be profoundly influenced by visual feedback concerning the force magnitude. Even when this feedback was distorted, it accounted for 99% of the variance of the effort rating. These results indicate that substantial visual distortions should be imperceptible to the subject, and that visual feedback can be used to influence the subject's perceived experience in our robotic environment. This means that we should be able to use imperceptible visual distortion to alter a patient's perception of therapeutic exercise in a robotic environment.

[1]  John W. Atkinson,et al.  Introduction: Motivation , 1964 .

[2]  N. Durlach,et al.  Intensity perception. IV. Resolution in roving-level discrimination. , 1973, The Journal of the Acoustical Society of America.

[3]  J. Lackner.  Adaptation to Displaced Vision: Role of Proprioception , 1974, Perceptual and motor skills.

[4]  Edwin A. Fleishman,et al.  Reliability and validity of methods for evaluating perceived physical effort. , 1980 .

[5]  M A Heller,et al.  Haptic Dominance in Form Perception with Blurred Vision , 1983, Perception.

[6]  A. Bandura,et al.  Self-evaluative and self-efficacy mechanisms governing the motivational effects of goal systems. , 1983 .

[7]  E. A. Fleishman,et al.  The measurement of effort. , 1984, Ergonomics.

[8]  H. Ross,et al.  Sensorimotor mechanisms in weight discrimination , 1984, Perception & psychophysics.

[9]  M. S. Devanandan,et al.  Weight appreciation in the hand in normal subjects and in patients with leprous neuropathy. , 1985, Brain : a journal of neurology.

[10]  A. Bandura,et al.  Differential engagement of self-reactive influences in cognitive motivation , 1986, Organizational Behavior and Human Decision Processes.

[11]  H. Ross,et al.  Weber Fractions for Weight and Mass as a Function of Stimulus Intensity , 1987, The Quarterly journal of experimental psychology. A, Human experimental psychology.

[12]  C. Dweck,et al.  Goals: an approach to motivation and achievement. , 1988, Journal of personality and social psychology.

[13]  N I Durlach,et al.  Analysis of a synthetic Tadoma system as a multidimensional tactile display. , 1989, The Journal of the Acoustical Society of America.

[14]  N I Durlach,et al.  Notes and Comment Resolution in one dimension with random variations in background dimensions , 1989, Perception & psychophysics.

[15]  W. M. Rabinowitz,et al.  Manual discrimination and identification of length by the finger-span method , 1989, Perception & psychophysics.

[16]  L. A. Jones.  Matching Forces: Constant Errors and Differential Thresholds , 1989, Perception.

[17]  N. Durlach,et al.  Manual discrimination of force using active finger motion , 1991, Perception & psychophysics.

[18]  E. Taub.  Overcoming Learned Nonuse A New Approach to Treatment in Physical Medicine , 1994 .

[19]  M A Srinivasan,et al.  Manual discrimination of compliance using active pinch grasp: The roles of force and work cues , 1995, Perception & psychophysics.

[20]  S J Bolanowski,et al.  The effects of aging on information-processing channels in the sense of touch: III. Differential sensitivity to changes in stimulus intensity. , 1996, Somatosensory & motor research.

[21]  J. Liepert,et al.  Motor cortex plasticity during constraint-induced movement therapy in stroke patients , 1998, Neuroscience Letters.

[22]  W. Rymer,et al.  Understanding and treating arm movement impairment after chronic brain injury: progress with the ARM guide. , 2014, Journal of rehabilitation research and development.

[23]  N. Hogan,et al.  Is robot-aided sensorimotor training in stroke rehabilitation a realistic option? , 2001, Current opinion in neurology.

[24]  K Shinomori,et al.  Age-related changes in wavelength discrimination. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.

[25]  J G Williams,et al.  Development and initial validation of the Effort Sense Rating Scale (ESRS): a self-perceived index of physical fitness. , 2001, Preventive medicine.

[26]  S. Gordon-Salant,et al.  Aging and temporal discrimination in auditory sequences. , 2001, The Journal of the Acoustical Society of America.

[27]  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.

[28]  Roberta L. Klatzky,et al.  Measuring just noticeable differences for haptic force feedback: implications for rehabilitation , 2002, Proceedings 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. HAPTICS 2002.

[29]  M. Ernst,et al.  Humans integrate visual and haptic information in a statistically optimal fashion , 2002, Nature.

[30]  Jeffrey A. Lewis,et al.  Virtual Reality-based System for Ankle Rehabilitation Post Stroke , 2002 .

[31]  Roberta L. Klatzky,et al.  Feedback distortion for rehabilitation: gauging perceived physical effort , 2003, 11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2003. HAPTICS 2003. Proceedings..

[32]  Roberta L. Klatzky,et al.  Feedback distortion to overcome learned nonuse: a system overview , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[33]  Roberta L. Klatzky,et al.  Feedback Distortion to Increase Strength and Mobility , 2003 .

[34]  Slobodan Jaric,et al.  The effects of practice on movement distance and final position reproduction: implications for the equilibrium-point control of movements , 1994, Experimental Brain Research.

[35]  I. Hunter,et al.  A perceptual analysis of stiffness , 2004, Experimental Brain Research.

[36]  Functional assessment after stroke : examining outcome models using the international classification of functioning, disability and health , 2004 .

[37]  Roberta L. Klatzky,et al.  Effects of visual feedback distortion for the elderly and the motor-impaired in a robotic rehabilitation environment , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.