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Augmented Feedback on Motor Functions

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Several studies have addressed the use of augmented feedback, such as biofeedback, with spinal cord injured populations. Van Dijik et al. (2005) conducted a systematic review of RCTs on the effect of augmented feedback on motor function of the affected upper extremity in rehabilitation patients. Much of the information about augmented feedback comes from the motor learning literature where it has been noted that feedback combined with practice is a potent variable for affecting motor skill learning (Newell 1991; Schmidt & Lee 1999). There are two types of performance-related information or feedback. The first type of feedback, task intrinsic or inherent feedback, is sensory-perceptual information and is a natural part of performing a skill. The second type of feedback is augmented feedback or information-based extrinsic or artificial feedback. Augmented feedback refers to enhancing task intrinsic feedback with an external source (Magill 2001; Schmidt & Lee 1999), such as a therapist or device (biofeedback or timer) (van Dijik et al., 2005). It has been suggested that augmented feedback may have practical implications for rehabilitation therapy since re-acquisition of motor skills is an important part of functional motor recovery (Jarus 1994; Jarus & Ratzon 2005; Kilduski & Rice 2003; Winstein 1991).

The ability to use intrinsic feedback to guide performance is impaired in patients with cognitive and perceptual deficits (Flinn & Radomski 2002). In persons who are compromised by neurological sensory impairments, augmented feedback is important (Sabari 2001).

Table 3: Augmented Feedback on Motor Functions

Discussion

Four of the six included studies concluded that there was no evidence for the effectiveness of augmented feedback to improve arm function in rehabilitation. These four studies are the only RCTs to date that have test augmented feedback for arm rehabilitation post SCI.

One study by Brucker et al. (1996) tested biofeedback treatment among 100 participants and found an increase in normal EMG scores in the right and left triceps, however, this sample did not include a control group. A more recent study with just three participants applied magnetoencephalography based neurofeedback and authors concluded that neurofeedback training may have the potential to be used for motor rehabilitation (Foldes et al., 2015). Given the small sample sizes within each of the six included studies, conducting additional RCTs with larger samples is necessary to gain a more conclusive understanding of the impact of augmented feedback in upper limb rehabilitation.

In a systematic review, van Dijik et al. (2005) recommended the following be considered in future research in this area:

  • future studies should focus on content, form, and timing of the augmented feedback to clarify its importance in rehabilitation.
  • studies should recognize the difference between performance and learning effects concerning reacquisition of motor skills by re-examining the study population after a follow up period.

Conclusion

There is level 1a evidence (from two randomized controlled trials; Kohlmeyer et al., 1996; Popovic et al., 2006) that augmented feedback is not effective in improving upper limb function in tetraplegia.

There is level 2 evidence (from two randomized control trials; Klose et al., 1990; Klose et al., 1993) that the addition of biofeedback does not improve patient scores in rehabilitation more than physical exercise alone.

There is level 4 evidence (from one pre-post test; Bruker and Bulaeva, 1996) that EMG biofeedback sessions can significantly improve normal EMG muscle test scores of both triceps.

There is level 4 evidence (from one post-test; Foldes et al., 2015) that patients with complete hand paralysis can learn to significantly modulate their sensory motor rythyms using a virtual hand task over time.   

  • Augmented feedback does not improve motor function of the upper extremity
    in SCI rehabilitation patients. However, biofeedback has been shown to positively effect normal EMG muscle scores in both triceps.

    Patients may be ale to learn to regulate their sensory motor rhythms in their upper extremities using virtual tasks like hand-grasping.