New control strategies for neuroprosthetic systems

Patrick E. Crago, Ning Lan, Peter H. Veltink, James J. Abbas, Carole Kantor

Research output: Contribution to journalArticlepeer-review

89 Scopus citations


The availability of techniques to artificially excite paralyzed muscles opens enormous potential for restoring both upper and lower extremity movements with neuroprostheses. Neuroprostheses must stimulate muscle, and control and regulate the artificial movements produced. Control methods to accomplish these tasks include feedforward (open-loop), feedback, and adaptive control. Feedforward control requires a great deal of information about the biomechanical behavior of the limb. For the upper extremity, an artificial motor program was developed to provide such movement program input to a neuroprosthesis. In lower extremity control, one group achieved their best results by attempting to meet naturally perceived gait objectives rather than to follow an exact joint angle trajectory. Adaptive feedforward control, as implemented in the cycle-to-cycle controller, gave good compensation for the gradual decrease in performance observed with open-loop control. A neural network controller was able to control its system to customize stimulation parameters in order to generate a desired output trajectory in a given individual and to maintain tracking performance in the presence of muscle fatigue. The authors believe that practical FNS control systems must exhibit many of these features of neurophysiological systems.

Original languageEnglish (US)
Pages (from-to)158-172
Number of pages15
JournalJournal of Rehabilitation Research and Development
Issue number2
StatePublished - Apr 1996
Externally publishedYes


  • FES
  • FNS
  • adaptive control
  • closed-loop
  • feedback
  • feedforward
  • open-loop

ASJC Scopus subject areas

  • Rehabilitation


Dive into the research topics of 'New control strategies for neuroprosthetic systems'. Together they form a unique fingerprint.

Cite this