Advertisement

Experimental Validation of a Rapid, Adaptive Robotic Assessment of the MCP Joint Angle Difference Threshold

  • Mike D. RinderknechtEmail author
  • Werner L. Popp
  • Olivier Lambercy
  • Roger Gassert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8619)

Abstract

This paper presents an experimental evaluation of a rapid, adaptive assessment of the difference threshold (DL) of passive metacarpophalangeal index finger joint flexion using a robotic device. Parameter Estimation by Sequential Testing (PEST) is compared to the method of constant stimuli (MOCS) using a two-alternative forced-choice paradigm. The pilot study with \(13\) healthy subjects provided DLs within similar ranges for MOCS and PEST, averaging at \(2.15^{\circ }\pm 0.77^{\circ }\) and \(1.73^{\circ }\pm 0.78^{\circ }\), respectively, in accordance with the literature. However, no significant correlation was found between the two methods (\(r(11) = 0.09\), \(p = 0.762\)). The average number of trials required for PEST to converge was \(58.7\pm 17.6\), and significantly lower compared to \(120\) trials for MOCS (\(p < 0.001\)), leading to an assessment time of under \(15\) min. These results suggest that rapid, adaptive methods, such as PEST, could be successfully implemented in novel robotic tools for clinical assessment of sensory deficits.

Keywords

Robot-assisted assessment Sensory function Proprioception Difference threshold Psychophysics Hand function 

Notes

Acknowledgments

The authors would like to thank J.-C. Metzger for inspiring and profitable discussions, as well as J. Liepert, M. Kaiser and V. Raible for their help in defining the clinical requirements for stroke patients. This research was supported by the National Center of Competence in Research on Neural Plasticity and Repair of the Swiss National Science Foundation, the Janggen-Pöhn Foundation and ETH Zurich.

References

  1. 1.
    Bell-Krotoski, J., Weinstein, S., Weinstein, C.: Testing sensibility, including touch-pressure, two-point discrimination, point localization, and vibration. J. Hand Ther. 6(2), 114–123 (1993)CrossRefGoogle Scholar
  2. 2.
    Jerosch-Herold, C.: A study of the relative responsiveness of five sensibility tests for assessment of recovery after median nerve injury and repair. J. Hand Surg.-Brit. Eur. 28(3), 255–260 (2003)CrossRefGoogle Scholar
  3. 3.
    Lincoln, N.B., Crow, J.L., Jackson, J.M., Waters, G.R., Adams, S.A., Hodgson, P.: The unreliability of sensory assessments. Clin. Rehabil. 5(4), 273–282 (1991)CrossRefGoogle Scholar
  4. 4.
    Brewer, B.R., Fagan, M., Klatzky, R.L., Matsuoka, Y.: Perceptual limits for a robotic rehabilitation environment using visual feedback distortion. IEEE Trans. Neural Syst. Rehabil. Eng. 13(1), 1–11 (2005)CrossRefGoogle Scholar
  5. 5.
    Tan, H.Z., Srinivasan, M.A., Reed, C.M., Durlach, N.I.: Discrimination and identification of finger joint-angle position using active motion. ACM Trans. Appl. Percept. (TAP) 4(2), 10 (2007)CrossRefGoogle Scholar
  6. 6.
    Lambercy, O., Juárez Robles, A., Kim, Y., Gassert, R.: Design of a robotic device for assessment and rehabilitation of hand sensory function. In: 2011 IEEE International Conference on Rehabilitation Robotics (ICORR), pp. 1–6, June 2011Google Scholar
  7. 7.
    Gescheider, G.: Psychophysics: Method, Theory, and Applications. Lawrence Erlbaum Associates, New Jersey (1985)Google Scholar
  8. 8.
    Watson, A.B., Fitzhugh, A.: The method of constant stimuli is inefficient. Percept. Psychophysics 47(1), 87–91 (1990)CrossRefGoogle Scholar
  9. 9.
    Macmillan, N.A., Douglas Creelman, C.: Detection Theory: A User’s Guide. Lawrence Erlbaum Associates, New Jersey (2005)Google Scholar
  10. 10.
    Taylor, M.M., Douglas Creelman, C.: PEST: Efficient estimates on probability functions. J. Acoust. Soc. Am. 41, 782 (1967)CrossRefGoogle Scholar
  11. 11.
    Oldfield, R.C.: The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9(1), 97–113 (1971)CrossRefGoogle Scholar
  12. 12.
    Prins, N., Kingdom, F.A.A.: Palamedes: matlab routines for analyzing psychophysical data (2009). http://www.palamedestoolbox.org
  13. 13.
    Taylor, M.M., Forbes, S.M., Douglas Creelman, C.: PEST reduces bias in forced choice psychophysics. J. Acoust. Soc. Am. 74, 1367 (1983)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Mike D. Rinderknecht
    • 1
    Email author
  • Werner L. Popp
    • 1
  • Olivier Lambercy
    • 1
  • Roger Gassert
    • 1
  1. 1.Rehabilitation Engineering LabETH ZurichZurichSwitzerland

Personalised recommendations