https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-018-0408-5
Journal of NeuroEngineering and Rehabilitation201815:65
© The Author(s). 2018
Received: 18 October 2017
Accepted: 19 June 2018
Published: 4 July 2018
Abstract
Despite upper extremity function playing a crucial role in maintaining one’s independence in activities of daily living, upper extremity impairments remain one of the most prevalent post-stroke deficits. To enhance the upper extremity motor recovery and performance among stroke survivors, two training paradigms in the fields of robotics therapy involving modifying haptic feedback were proposed: the error-augmentation (EA) and error-reduction (ER) paradigms. There is a lack of consensus, however, as to which of the two paradigms yields superior training effects. This systematic review aimed to determine (i) whether EA is more effective than conventional repetitive practice; (ii) whether ER is more effective than conventional repetitive practice and; (iii) whether EA is more effective than ER in improving post-stroke upper extremity motor recovery and performance. The study search and selection process as well as the ratings of methodological quality of the articles were conducted by two authors separately, and the results were then compared and discussed among the two reviewers. Findings were analyzed and synthesized using the level of evidence. By August 1st 2017, 269 articles were found after searching 6 databases, and 13 were selected based on criteria such as sample size, type of participants recruited, type of interventions used, etc. Results suggest, with a moderate level of evidence, that EA is overall more effective than conventional repetitive practice (motor recovery and performance) and ER (motor performance only), while ER appears to be no more effective than conventional repetitive practice. However, intervention effects as measured using clinical outcomes were under most instance not ‘clinically meaningful’ and effect sizes were modest. While stronger evidence is required to further support the efficacy of error modification therapies, the influence of factors related to the delivery of the intervention (such as intensity, duration) and personal factors (such as stroke severity and time of stroke onset) deserves further investigations as well.
Background
Stroke, also referred to as cerebrovascular accident (CVA), is one of the leading causes of disablement among adults [1, 2]. It is estimated that stroke costs the Canadian, United States and United Kingdom economy around $3.6 billion [3], $34 billion [4] and £9 billion [5]
a year respectively in medical services, personal care and lost
productivity. The disabilities resulting from stroke can affect all
aspects of life including gross and fine motor ability, walking,
activities of daily living (ADLs), speech and cognition [6].
Motor impairments are some of the most prevalent issues post stroke and
restoring upper extremity function is one of the top priorities of
people with stroke [7].
Compared to the lower extremity impairments, the upper extremity
impairments are more likely to result in activities limitations (see
International Classification of Functioning, Disability and Health (ICF)
in Appendix 1) because tasks that involve the arm and hand often require a high level of fine motor control [8]. In fact, severe upper extremity impairments post-stroke often hinder the ability to take care for oneself and perform ADLs [9].
Although restoration of upper extremity motor functions is crucial for
stroke patients to regain their independence, studies have shown that
only 35 to 70% of people with stroke recover to the level of arm ability
that is considered functional [10, 11, 12] while more than 50% have persistent upper extremity impairments [13].
Studies
in both human and animal models demonstrate the importance of motor
learning in the process of motor recovery following an acquired brain
lesion as both learning and recovery processes can induce cortical
changes and reorganization [14].
Motor learning, which is “a set of processes associated with practice
or experience that leads to relatively permanent changes in the ability
to produce skilled action” [15],
relies on an experience-dependent neural plasticity that is modulated
by various factors such as task specificity, repetition, intensity,
timing, salience, etc. [16]. Amongst different factors influencing the acquisition of motor skills, feedback is believed to be one of the key factors [15]. Feedback is the information that an individual receives as a result of his or her performance [17].
It can be either intrinsic or extrinsic, where intrinsic feedback is
that experienced by the performer (e.g. sensory, visual feedback, etc.)
and extrinsic (augmented) feedback is that provided by an external
source, such as a therapist providing verbal or physical guidance [18, 19].
Extrinsic feedback can inform the performer about a success or failure
on a task (knowledge of results) or about the quality of movement or
task performance (knowledge of performance) [15].
Robotics is one of the advanced technologies that is increasingly used in post-stroke upper extremity rehabilitation [20].
Compared to conventional approaches, it offers the advantages of high
convenience when providing task-oriented practice, as well as high
accuracy in measuring outcomes of motor performance (e.g. trajectory
straightness, movement speed, range of joint movement [21]). The latter outcomes can in turn be used to provide knowledge of performance as a source of feedback [22].
Two main paradigms of training on the use of feedback, arising from the
literature on robotics, were proposed and tested as means to facilitate
motor learning and improve motor performance: the error reduction (ER)
paradigm and error augmentation (EA) paradigm. The ER paradigm, also
known as haptic guidance, is to reduce the performance errors of a
subject during a motor task [23],
namely via the assistance provided by a robot so that the performer can
stay within the optimal movement trajectory determined by the
non-paretic arm or by the therapist [24].
This approach is based on the hypothesis that by demonstrating the
correct movement trajectory to a person, he/she will be able to learn it
by imitation [25].
The discovery of “mirror neurons” that were first identified using
microelectrode recordings of single neurons in area F5 of monkey
premotor cortex [26]
prompted the researchers to believe that a similar mirror neuron system
exists in humans, and that this mirror neuron system could play an
important role in learning through imitation [27].
Furthermore, the theory of reinforcement-based learning suggests that
positive/successful feedback is essential for motor learning to occur [28].
The ER paradigm also assumes that there is a unique optimal movement
trajectory and any deviation from it is considered to be an error.
According to the principle of abundance and the theory of use-dependent
learning, however, having variance in how a motor action is performed
does not necessarily impede the overall motor performance [29, 30].
A
whole body of literature also suggests that motor learning can be an
error driven process, a postulate that can be explained and supported by
motor control theories such as the internal model theory [31] and the equilibrium point hypothesis [32].
In the internal model theory, it is hypothesized that subjects form an
‘internal model’ based on their anticipation of the effects of the
environment on their motor actions, therefore the internal model acts as
a feed-forward component of the motor control [31].
The detection of errors that occur during the motor performance play
the role of a feedback component, as errors prompt the existing internal
model to adapt in order to reduce errors [33, 34, 35, 36].
In the equilibrium point hypothesis, the errors occur in the subsequent
movements following a change in the environment, but the motor system
is able to correct these errors by adjusting the control variables based
on information about the current motor system, joint positioning of the
limbs, etc., thus resetting the activation thresholds (λ) of muscle and
forming a new equilibrium point [32, 37].
Given the role of errors in motor learning, it was hypothesized that
artificially increasing the performance error would cause learning to
occur more quickly [25],
an idea that is the foundation of the EA paradigm. In robotics, one of
the commonly used technique to artificially increase performance error
is to create a force-field that disturbs the limb motion during the
movement [38].
While
the theories and ideas that support ER vs. EA paradigms are distinct,
both are currently being used, primarily in the form of haptic feedback,
as part of clinical intervention studies for populations with deficits
in motor recovery. Until this day, there is no consensus as to which of
the two paradigms provides superior treatment effects in upper extremity
motor recovery and performance among stroke survivors. Furthermore,
while systematic reviews on the use of error modification in upper
extremity rehabilitation after stroke were published in the recent years
[39, 40],
these exclusively focused on the EA paradigm and did not allow for a
comparison between the two approaches. In this study, we conducted a
systematic review on the use of EA and ER paradigms in the form of
haptic feedback to enhance upper extremity motor recovery and
performance in stroke survivors. The main research questions that were
addressed are listed in PICO format (Population, Intervention,
Comparison, and Outcome) and read as follows:
- 1.Among stroke survivors (P), to which extent do interventions involving EA paradigm (I1) or ER paradigm (I2) compared to interventions without error modification (C) enhance the upper extremity motor recovery and performance respectively (O).
- 2.Among stroke survivors (P), to which extent does the EA paradigm (I) compared to ER paradigm (C) enhance the upper extremity motor recovery and performance (O).
For
the purpose of clarification, the comparison component of the first
research question, “training without error modification,” refers to
standard repetitive practice that does not involve any external force
(reducing or amplifying errors) that provides feedback on the
performance. The outcomes of both research questions, “upper extremity
motor recovery and performance,” can include clinical measures of both
upper extremity impairment and disability and kinematic measures of
motor performance (for more details, refer to the section of inclusion
and exclusion criteria).
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