1. Learning to Control Opening and Closing a Myoelectric Hand
Hanneke Bouwsema, MSc, Corry K. van der Sluis, MD, PhD, Raoul M. Bongers, MSc, PhD 
Archives of Physical Medicine and Rehabilitation 
Volume 91, Issue 9, Pages (September 2010)
DOI: /j.apmr
Copyright © 2010 American Congress of Rehabilitation Medicine Terms and Conditions

2. Fig 1 The myoelectric simulator.
Archives of Physical Medicine and Rehabilitation  , DOI: ( /j.apmr )
Copyright © 2010 American Congress of Rehabilitation Medicine Terms and Conditions

3. Fig 2
Illustrative examples of myoelectric signals of 2 different participants on the posttest. (A) The 3 different velocity conditions can be clearly seen in the myoelectric signals. The slow conditions are characterized by a wide myoelectric signal, whereas the fast conditions show a very narrow but high myoelectric signal. (B) The velocity conditions are difficult to distinguish. Note the different time scales of the 2 figures.
Archives of Physical Medicine and Rehabilitation  , DOI: ( /j.apmr )
Copyright © 2010 American Congress of Rehabilitation Medicine Terms and Conditions

4. Fig 3
(A) Categorization of participants in high-capacity learners (HCL) and low-capacity learners (LCL), with the division based on the mean slope of the regression lines (81). (B and C) The regression lines of the (B) same HCL participant and (C) LCL participant as shown in Figure 2.
Archives of Physical Medicine and Rehabilitation  , DOI: ( /j.apmr )
Copyright © 2010 American Congress of Rehabilitation Medicine Terms and Conditions

5. Fig 4
Peak velocity reached in the pretest and the posttest for the high capacity learners (HCL) and low capacity learners (LCL) plotted for each of the velocity conditions.
Archives of Physical Medicine and Rehabilitation  , DOI: ( /j.apmr )
Copyright © 2010 American Congress of Rehabilitation Medicine Terms and Conditions