Biomedical Engineering Reference
In-Depth Information
The main function of our planar robot is for rehabilitating the elbow and
shoulder joints. However, in stroke patients, motor impairments of the wrist and
hand usually accompany those of elbow and shoulder joints. For the upper limbs,
the function of hands is the main focus, and the function of the proximal parts is
supportive. After completing the planar robot for elbow-shoulder rehabilitation,
we modify the wrist fixation part so that the pronation-supination movement of
the forearm can also be controlled and rehabilitated (Kung
et al.
, 2005). Two types
of movements are designed, i.e., passive and active movements. The passive
movement means that the subject is asked to relax his forearm and the robot
guides the forearm to complete the movement. The main function of the passive
movements is to reduce the muscle tone of the forearm and to increase the ROM.
In the active mode, subjects have to move actively along a planned trajectory and
the robot applies either a resistant or an assistant torque. Active movements are
designed to help patients to increase muscle power. Two treatment trajectories, i.e.,
seesaw-like and ramp-and-hold trajectories, are designed to mimic the facilitation
techniques of the physical therapists. In the seesaw-like trajectory the robot can
cyclically stretch the forearm of the subject. Hogan's group also has developed a
wrist rehabilitation robot, which can be combined with the original MIT-MANUS
(Krebs
et al.
, 2007).
The next step is for rehabilitation of the hand. In terms of the joint number,
hand is the most complicated part of the upper limb and the design of robots
for hand rehabilitation is the most difficult part. Hogan's group developed two
generations of robots for hand rehabilitation (Masia
et al.
, 2006) and is still on the
way of improving the system. We also developed several prototypes, but none
is satisfactory (Hong
et al.
, 2006; Shih
et al.
, 2007). More studies to gain insight
into what is essential for hand rehabilitation may be needed before a practical
rehabilitation robot for hands can be designed.
Currently, the rehabilitation robots are controlled by pre-written programs
and subjects interact with the robots through parameters, such as force, position
and compliance. The subjects can not control the behavior of the robots. Allow-
ing subjects to have control over the robots may have the benefits of tailoring
the treatment individually. EEG is a commonly used control source for brain-
computer interface (BCI) (Wolpaw
et al.
, 2000) , which is defined as an artificially
reconstructed connection between a subject's brain and the environment. BCI
is developed to help subjects with motor impairments to regain environmental
control or communication with others. Using the subjects' own EEG as the control
source may have the benefits of training the brain and promoting plasticity of the
cortex. If the required imagery attempts correspond to the natural control for the
rehabilitating movements, it is also possible that the setup may promote the repair
of the corrupted efferent connection. We implemented the idea in a rehabilitation
device of fingers. The results (Chen
et al.
, 2009) indicate that the idea is plausible.
Yet, the benefits for fingers and for the brain need to be validated.
The individual difference among subjects are huge, because variation in the
pre-morbid capability, the size and the location of stroke lesions and the intensity
of rehabilitation.
It is more logical to design and implement a custom-tailored
