The effects of error-augmentation versus error-reduction paradigms in robotic therapy to enhance upper extremity performance and recovery post-stroke: a systematic review

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.

Learning and transfer of complex motor skills in virtual reality: a perspective review

“…One such example is error amplification [41–43]. While physical or haptic error amplification (and reduction) requires the use of robotic interfaces [44–46], visual error amplification or distortion can be presented in a VE without the use of a robot. For example, Hasson et al [43] used the virtual throwing task earlier described to explore the effect of visual error amplification after participants had reached a performance plateau following 3 days of practice.…”

Experimental Study on Upper-Limb Rehabilitation Training of Stroke Patients Based on Adaptive Task Level: A Preliminary Study

“…The disabilities usually affect the activities of daily living, such as motion ability, walking, speech, and cognition [10, 11]. In clinics, motor deficits are some of the most prevalent symptoms, and 69% of stroke patients have some degree of motion disability of the upper extremity [12]. Fortunately, clinic investigations in both human and animal models demonstrate that massive and intensive motion training can induce cortical changes and reorganization, which construct a relative ability to produce skilled action [4].…”

The Untapped Potential of Virtual Reality in Rehabilitation of Balance and Gait in Neurological Disorders

“…The evidence supports the use of multimodal feedback to modulate or train functional locomotion from a rehabilitation perspective. In upper extremity rehabilitation research, a well-studied approach consists of artificially increasing the perceived performance error through visual or haptic feedback (i.e., error augmentation paradigm) ( Israely and Carmeli, 2016 ; Liu et al, 2018 ). Similarly, manipulating avatar-based feedback offers an opportunity to modify the locomotor behavior.…”