D2.1 Requirements and Specification - CORBYS

D2.1 Requirements and Specification
function and improved gait (Barbeau and Rossignol, 1994; Dietz et al.,1994; Hesse et al., 1995). In addition,
there are several secondary positive effects on the physical and mental condition of these patients (Hidler et
al., 2008). Gait training prevents many of the secondary complications that often result from neurological
injury and gait impairment (e.g. joint stiffening, muscle atrophy, cardiovascular deterioration, pneumonia,
deep venous trombosis). Therefore, treadmill training is a well-established practice nowadays in rehabilitation
centres for the neurologically impaired.
The driving force behind neural recovery is neural plasticity, the ability of neural circuits, both in the brain
and the spinal cord, to reorganise or change function (Elbert et al., 1994). This process was clearly evidenced
in prior animal research, revealing the existence of so called “central pattern generators” at the level of the
spinal cord that allow to reinstill animal gait through training following spinal cord lesion. However, neural
recovery has proven to be much more complex in humans, as human walking involves both spinal control and
brain control (Yang and Gorassini, 2006). For rehabilitation to be successful neural plasticity should thus be
maximally promoted. Although the mechanisms underlying neural recovery are not yet fully understood,
there is a growing consensus about the major enabling principles. Sensory input from the muscles and joints
to the central nervous system (afferent input) is crucial (Ridding and Rothwell, 1999; Harkema, 2001). Also,
these sensory cues should match as closely as possible with those normally involved in the task to be
relearned. Some critical cues of human locomotion have been established, but are subject of ongoing research
(Behrman and Harkema, 2000). Another important requirement for recovery is that training should be
intensive and that it should be started as early as possible after the injury to maximise outcome (Sinkjaer and
Popovic, 2005). The need for intensive training and the aim of relieving therapists from the physical strain
induced by manually assisted gait training, triggered the application of robotic assistance to gait rehabilitation.
The development and use of gait rehabilitation robots both in rehabilitation practice and in research labs has
strengthened the validity of some concepts that are believed to underlie gait retraining in general and also to
increase the effectiveness of robot-assisted training itself. A key finding is that assisting movements (too
much) may result in reduced effort and decreased motor learning (Marchal-Crespo and Reinkensmeyer, 2008).
This is evidenced by motor learning studies in unimpaired subjects involving robotic assistance to learn a
movement task, and appears to apply to neural recovery as well. Some studies explored the benefits of
amplifying movement errors instead of correcting them, which was found to improve short term motor
learning, as reported for instance in Reisman et al., 2007. It was also shown that the training should be
adapted to the skills of the subject: similar to providing too much assistance, providing too little is
counterproductive (Emken et al., 2007). Another important aspect to training is active participation, which is
promoted by motivation. The robotic training environment should trigger the subject to self-initiate and
actively contribute to the movements and also to sustain efforts (Lotze et al., 2003). The suggestion that effort
may be more important than (robotic) assistance, questions the rationale behind the use of robots in movement
therapy (Reinkensmeyer et al., 2007). Nonetheless, many rationales for using robotic assistance in gait
rehabilitation can be found in literature (Guglielmelli et al. 2009; Marchal-Crespo and Reinkensmeyer, 2009).
Previously unexplored movements provide novel sensory information to the patient, assistance makes gait
training more safe and intense, and helping the patient accomplish desired movements is an important
motivating factor (an extensive overview can be found in Marchal-Crespo and Reinkensmeyer (2009)).
The aforementioned concepts are encompassed by a best practice in assistance-based robotic therapy
commonly referred to by “assistance-as-needed”, implying that the robot should assist only as much as needed
and only where needed. Hence, the level of assistance should be adaptable and task (or function) specific.
Newly developed robot technology for gait rehabilitation is increasingly focused on this paradigm. The
following section puts emphasis on general concepts and hardware.
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