Design and Preliminary Evaluation of a Perturbation-based Robot-assisted Assessment of Hand Sensorimotor Impairments

Neurological injuries often lead to hand sensorimotor deficits, such as impaired corrective responses to mechanical disturbances. That is frequently caused by difficulties in integrating sensory feedback when executing motor responses and affects the general ability to interact with the external environment. It is challenging to quantitatively assess such impairments using clinical measures, whereas the existing robotic approaches mainly target shoulder joints. This work presents design and preliminary evaluation of a robot-assisted assessment of hand sensorimotor function, in which subjects need to rely on proprioceptive feedback to actively correct for load perturbations. The task is implemented on a one degree-of-freedom robotic platform focused on the index finger metacarpophalangeal joint, which can apply a precise stimuli and measure kinematic responses. In a study with six healthy young subjects we investigated four different load perturbations parameters (1.5N step-, 3N step-, 2.5N ramp and 5N ramp, each on top of a 2.5N load) to find the most promising perturbation scenario for future studies with neurological subjects. We found that a ramp perturbation applied over 1 second with 2.5 N amplitude is least prone to confounds such as involuntary responses or high intra-subject variability, hence it is expected to be the most accurate in distinguishing between impairments. Overall, the presented perturbation-based assessment provides insights into sensorimotor system integrity in a quantitative and reproducible way and hence has the potential to add value to the battery of existing clinical methods.

[1]  J. Gordon,et al.  Impairments of reaching movements in patients without proprioception. II. Effects of visual information on accuracy. , 1995, Journal of neurophysiology.

[2]  Stephen H Scott,et al.  Impaired corrective responses to postural perturbations of the arm in individuals with subacute stroke , 2015, Journal of NeuroEngineering and Rehabilitation.

[3]  Stephen H Scott,et al.  A postural unloading task to assess fast corrective responses in the upper limb following stroke , 2019, Journal of NeuroEngineering and Rehabilitation.

[4]  S. Scott The computational and neural basis of voluntary motor control and planning , 2012, Trends in Cognitive Sciences.

[5]  Olivier Lambercy,et al.  Design and Characterization of a Robotic Device for the Assessment of Hand Proprioceptive, Motor, and Sensorimotor Impairments , 2019, 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR).

[6]  Benjamin K. Barry,et al.  Reflex responsiveness of a human hand muscle when controlling isometric force and joint position , 2007, Clinical Neurophysiology.

[7]  Marten Munneke,et al.  Clinimetric properties of instruments to assess activities in patients with hand injury: a systematic review of the literature. , 2009, Archives of physical medicine and rehabilitation.

[8]  Joachim Hermsdörfer,et al.  Evaluation of precision grip using pneumatically controlled loads , 1992, Journal of Neuroscience Methods.

[9]  James M. Goodman,et al.  Finger Posture and Finger Load are Perceived Independently , 2019, Scientific Reports.

[10]  S. Rathore,et al.  Characterization of Incident Stroke Signs and Symptoms: Findings From the Atherosclerosis Risk in Communities Study , 2002, Stroke.

[11]  D. Nowak,et al.  Grip force control during object manipulation in cerebral stroke , 2003, Clinical Neurophysiology.

[12]  J. A. Pruszynski,et al.  The long-latency reflex is composed of at least two functionally independent processes. , 2011, Journal of neurophysiology.

[13]  J Hermsdörfer,et al.  Effects of baroreceptor stimulation on sensorimotor control of the hand. , 1993, Somatosensory & motor research.

[14]  O. Lippold,et al.  Long-latency component of the stretch reflex in human muscle is not mediated by intramuscular stretch receptors. , 2000, Journal of neurophysiology.

[15]  Philippe Lefèvre,et al.  Long-Latency Feedback Coordinates Upper-Limb and Hand Muscles during Object Manipulation Tasks123 , 2016, eNeuro.

[16]  C Ghez,et al.  Roles of proprioceptive input in the programming of arm trajectories. , 1990, Cold Spring Harbor symposia on quantitative biology.

[17]  L. Carey,et al.  Somatosensory assessment and treatment after stroke: An evidence-practice gap. , 2015, Australian occupational therapy journal.

[18]  Olivier Lambercy,et al.  Systematic Review on Kinematic Assessments of Upper Limb Movements After Stroke , 2019, Stroke.

[19]  S. Scott Optimal feedback control and the neural basis of volitional motor control , 2004, Nature Reviews Neuroscience.

[20]  Leeanne M. Carey,et al.  Somatosensory Loss after Stroke , 1995 .

[21]  Nadina B. Lincoln,et al.  The unreliability of sensory assessments , 1991 .

[22]  Olivier Lambercy,et al.  Reliability, validity, and clinical feasibility of a rapid and objective assessment of post-stroke deficits in hand proprioception , 2018, Journal of NeuroEngineering and Rehabilitation.

[23]  Frédéric Crevecoeur,et al.  A perspective on multisensory integration and rapid perturbation responses , 2015, Vision Research.

[24]  J. Noth,et al.  Long latency EMG responses in hand and leg muscles: cerebellar disorders. , 1987, Journal of neurology, neurosurgery, and psychiatry.

[25]  Olivier Lambercy,et al.  A data-driven framework for the selection and validation of digital health metrics: use-case in neurological sensorimotor impairments , 2019 .

[26]  S. Scott,et al.  Potential of robots as next-generation technology for clinical assessment of neurological disorders and upper-limb therapy. , 2011, Journal of rehabilitation research and development.

[27]  Nadina B. Lincoln,et al.  Reliability and Revision of the Nottingham Sensory Assessment for Stroke Patients , 1998 .

[28]  S. Chieffi,et al.  The role of proprioception in the control of prehension movements: a kinematic study in a peripherally deafferented patient and in normal subjects , 2004, Experimental Brain Research.

[29]  E. Burdet,et al.  Robot-assisted rehabilitation of hand function. , 2010, Current opinion in neurology.

[30]  Michael I. Jordan,et al.  Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.

[31]  Stephen H Scott,et al.  A robotic object hitting task to quantify sensorimotor impairments in participants with stroke , 2014, Journal of NeuroEngineering and Rehabilitation.

[32]  J. A. Pruszynski,et al.  Optimal feedback control and the long-latency stretch response , 2012, Experimental Brain Research.

[33]  R. Lyle A performance test for assessment of upper limb function in physical rehabilitation treatment and research , 1981, International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation.

[34]  L. Connell,et al.  Somatosensory impairment after stroke: frequency of different deficits and their recovery , 2008, Clinical rehabilitation.

[35]  Post-Stroke Rehabilitation Guidelin Post-Stroke Rehabilitation: Assessment, Referral, and Patient Management: Quick Reference Guide for Clinicians , 1996 .