Computational Intelligence in Analysis of Electromyography Signals - Computational Intelligence in Biomedical Engineering - page 258

Extension

90 °

Adduction 90 °

Motors

Abduction

Flexion

Extension

90 °

Flexion

Flexion

120 °

Motors

Extension

Motors

FIGURE 5.24
The exoskeleton developed by Kiguchi et al. (2004) and the neurofuzzy
controller system implemented for control of the mechanical actuators.
( Continued )

Mulas et al. (2005) explored a device for partial hand musculature loss due
to stroke or spinal cord injury. Their exoskeleton (Figure 5.25) has been used
primarily to detect finger motion and can be easily connected to a laptop with
a graphical user interface for monitoring the patient's therapy. Initial inves-
tigation has shown the ability to detect and actuate based on the intention
of a healthy volunteer to move his fingers. Andreasen et al. (2005) examined
prototype development of a robotic system for upper extremity (UE) reha-
bilitation in individuals with neurological impairments such as cervical level
spinal cord injuries (SCI), brain injuries, or stroke. Their system included
programmable mechanical impedance for load variations, adjustable thresh-
olds, and control gains and offered some user adaptability. The device was
designed to provide automated rehabilitation via repeated motor practice so
that neurological recovery in the UEs could be facilitated without requir-
ing a physiotherapist. A wearable power-assisted device was developed by
Naruse et al. (2005) to enable a person to lift heavier than normal objects
(Figure 5.26) and was designed to support the upper body weight. This