![](bg6.png)
analyze the muscles synchronization issues. Two sen-
sors located over 2 antagonistic muscles can discover
their synchronization during contractions. Moreover,
the information from these sensors can be used in con-
trol algorithms.
System Identification. The estimation of the sys-
tem state only from physiological sensors or the de-
termination of fuzzy sets must be adjusted to the in-
dividual subject. Moreover, the optimal control algo-
rithm for the FES controller must be selected. The
system is capable to perform tests enabling to work
out the force-EMG relationship for each subject. It is
possible to prepare a set of tests which enable semi-
automatic calibration of the sensors system.
The Stimuli Optimization. The stimulation exper-
iments revealed the variability of the excitability level
for the same stimulation procedure. The variability is
dependent on the pathology but also on the individ-
ual features of the subject. Therefore, the stimulation
waveforms and stimulus shapes should be selected in-
dividually. It was observed, that the stimulation let to
divide the subjects into few groups. The system let to
perform tests enabling classification of the subject to
the particular group.
3.3 Rehabilitation Tasks
Repetitive Exercises with or without Stimulation
Support. The aim of such a treatment is to increase
the maximum contraction force, or to increase a range
of motion. A subject can observe the actual force
level, the EMG amplitude, or the joint angle on the
screen, and to try to follow the reference trajectory as
set by the therapist. Moreover it is possible to use the
stimulation in order to compensate partially for the
error between the reference and the actual trajectory.
Restoration of Movement Functions for the Phys-
ically Disabled Subject. The main aim of the pre-
sented system is to develop a daily-use FES system
for the restoration of movement functions with a min-
imal number of sensors. The system is potentially ca-
pable to operate in closed feedback loop mode with
sensors and stimulation sequences configured indi-
vidually by therapist on the basis of the identifica-
tion tests results. However, to obtain satisfying results
with this application further investigations and devel-
opment of control algorithm is necessary.
ACKNOWLEDGEMENTS
The work was partially supported by the Polish
Ministry of Education and Science, project no.
1445/T11/2004/27.
REFERENCES
Bennie, S. D., Petrofsky, J. S., Nisperos, J., Tsurudome, M.,
and Laymon, M. (2002). Toward the optimal wave-
form for electrical stimulation of human muscle. Eur
J Appl Physiol, 88(1-2):13 – 19.
Breen, P. P., O’Keeffe, D. T., Conway, R., and Lyons, G. M.
(2006). A system for the delivery of programmable,
adaptive stimulation intensity envelopes for drop foot
correction applications. Med Eng Phys, 28(2):177 –
186.
Chizeck, H. J., Chang, S., Stein, R. B., Scheiner, A., and
Ferencz, D. C. (1999). Identification of electrically
stimulated quadriceps muscles in paraplegic subjects.
IEEE Trans Biomed Eng, 46(1):51 – 61.
Chou, L.-W., Ding, J., Wexler, A. S., and Binder-Macleod,
S. A. (2005). Predicting optimal electrical stimulation
for repetitive human muscle activation. J Electromyo-
graphy Kinesiology, 15:300–309.
Kaczmarek, P., Celichowski, J., and Kasi
´
nski, A. (2005).
Experimentally verified model of mechanomyograms
recorded during single motor unit contractions. J
Electromyogr Kinesiol, 15(6):617 – 630.
Keller, T., Popovic, M., Pappas, I., and Müller, P. (2002).
Transcutaneous functional electrical stimulator "com-
pex motion". Artificial Organs, 26(3):219–223.
Kutch, J. J. and Buchanan, T. S. (2001). Human elbow joint
torque is linearly encoded in electromyographic sig-
nals from multiple muscles. Neurosci Lett, 311(2):97
– 100.
Orizio, C., Gobbo, M., Veicsteinas, A., Baratta, R. V., Zhou,
B. H., and Solomonow, M. (2003). Transients of the
force and surface mechanomyogram during cat gas-
trocnemius tetanic stimulation. Eur J Appl Physiol,
88(6):601–606.
Sinkjaer, T., Haugland, M., Inmann, A., Hansen, M., and
Nielsen, K. D. (2003). Biopotentials as command
and feedback signals in functional electrical stim-
ulation systems. Medical Engineering & Physics,
25(2003):45 – 96.
Taylor, P. N., Burridge, J. H., Wood, D. E., Norton, J.,
Dunkerly, A., Singleton, C, and Swain, I. D. (1999).
Clinical use of the odstock drop foot stimulator - its
effect on the speed and effort of walking. Arch Phys
Med Rehabil, 80:1577 – 1583.
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