Review article
Stroke Patients’ Psychophysiological responses to Robot Training
Nika GOLJAR
; University Rehabilitation Institute of Republic of Slovenia – Soča, Linhartova 51, 1000 Ljubljana, Slovenia
Abstract
Robotic interfaces are becoming increasingly common in motor rehabilitation,
for they enable more intensive therapy. As the patient’s cognitive intent further
enhances motor relearning, the robots have been usually combined with virtual
reality (VR). In clinical environment the difficulty level of the training has to be
ensured in a way to meet a particular patient’s performance capabilities, inducing
appropriate motivation and arousal. While rehabilitation robots can provide
objective information about the patient’s motor performance and VR-based
game systems include real-time feedback, such systems do not offer insight into
the patient’s psychological state (mood, motivation, engagement). Emotions
experienced while playing computer games are reflected in physiological
responses, which could be used to determine a patient’s level of enjoyment
or frustration while training. The most commonly used psychophysiological
responses are those of the autonomic nervous system: heart rate, skin
conductance, respiration and skin temperature. Though autonomic nervous
system responses are also influenced by any physical activity, their usefulness
up to a certain level of physical load was confirmed.
Stroke survivors seem to have weaker psychophysiological responses than
healthy subjects. The disease itself can change the activity of the autonomic
nervous system and other factors such as comorbidity and medication should
be taken in consideration to influence psychophysiological measurements.
Only skin conductance and skin temperature have been proven to be useful for
psychological state estimation in stroke patients during robot-aided training in
VR. Changes in heart rate primarily reflect physical activity while changes in
respiration rate are small and unreliable.
The psychophysiological measurements seem to be unreliable for assessing
stroke patients’ psychological state during robot training in VR. Further studies
are needed in this aspect of rehabilitation robotics.
Keywords
Hrčak ID:
163347
URI
Publication date:
3.4.2016.
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