Error-Related Neural Responses Recorded by Electroencephalography During Post-stroke Rehabilitation Movements

Ohhh, lots of big new words, must be important. But no, nothing about actual recovery, just potential, so useless.  Even worse they used Bobath, already proven not to help. 

• Bobath (31)

Error-Related Neural Responses Recorded by Electroencephalography During Post-stroke Rehabilitation Movements

Akshay Kumar², Qiang Fang^1*, Jianming Fu³, Elena Pirogova² and Xudong Gu³

• ¹College of Engineering, Shantou University, Shantou, China
• ²School of Engineering, RMIT University, Melbourne, VIC, Australia
• ³2nd Hospital of Jiaxing, Jiaxing, China

Error-related potential (ErrP) based assist-as-needed robot-therapy can be an effective rehabilitation method. To date, several studies have shown the presence of ErrP under various task situations. However, in the context of assist-as-needed methods, the existence of ErrP is unexplored. Therefore, the principal objective of this study is to determine if an ErrP can be evoked when a subject is unable to complete a physical exercise in a given time. Fifteen stroke patients participated in an experiment that involved performing a physical rehabilitation exercise. Results showed that the electroencephalographic (EEG) response of the trials, where patients failed to complete the exercise, against the trials, where patients successfully completed the exercise, significantly differ from each other, and the resulting difference of event-related potentials resembles the previously reported ErrP signals as well as has some unique features. Along with the highly statistically significant difference, the trials differ in time-frequency patterns and scalp distribution maps. In summary, the results of the study provide a novel basis for the detection of the failure against the success events while executing rehabilitation exercises that can be used to improve the state-of-the-art robot-assisted rehabilitation methods.

Introduction

Stroke is the second leading cause of death and the third leading cause of disability in the world (Johnson et al., 2016). Depending on the extent and the location of damage due to stroke, stroke survivors suffer from a various degree of body functionality impairment (Kalaria et al., 2016). The most notable impairments include cognitive impairment, dementia, and limb movement impairment (Kalaria et al., 2016). Nevertheless, recovery from the disability due to stroke is possible through neuroplasticity (Basteris et al., 2014). Neuroplasticity is brain’s natural process aimed to reorganize itself by forming new neural connections, especially in response to learning or experiences that result in partial recovery from the disability. Post-stroke rehabilitation accelerates this process of neurological changes and ultimately helps in attaining a higher rate of recovery (Liu et al., 2017).

Motor function impairment affects the patient’s activities of daily living (ADLs) (Basteris et al., 2014). Therefore, recovery from motor disabilities is one of the primary objectives of the post-stroke rehabilitation program. Historically, in post-stroke rehabilitation, the patients are asked to perform certain physical exercises using their affected limb (Liu et al., 2017). Previous studies have described the role of intensive and repetitive rehabilitation exercises in promoting the rate of recovery from motor disabilities (Grosmaire and Duret, 2017; Liu et al., 2017; Tacchino et al., 2017). In addition, several studies have highlighted the significance of the active participation of the patient in performing rehabilitation exercises to promote motor recovery (Grosmaire and Duret, 2017; Tacchino et al., 2017). However, the key issue is that stroke patients cannot perform the rehabilitation exercises repetitively and actively due to their motor impairment (Basteris et al., 2014; Yue et al., 2017).

Assist-as-needed (AAN) robot therapy-based rehabilitation program helps in eliminating the issues mentioned above and allows the patients to perform exercises repetitively and actively (Basteris et al., 2014; Grosmaire and Duret, 2017). In AAN based robot therapies, assistance is provided to the patient in performing the rehabilitation exercise when he/she is unable to perform it on his/her own and vice versa. A few well-known EEG based BCI approaches, including movement-related cortical potentials (MRCP) (Liu et al., 2017), event-related synchronization/desynchronization (ERS/ERD) (Liu et al., 2017) and surface-electromyographic (sEMG) signals (Basteris et al., 2014), are most popular in developing assistive exoskeletons that assist stroke survivors in performing physical exercises. Error-related potential (ErrP) is another event-related potential (ERP) signal which is gaining popularity recently in BCI research due to its inherent intrinsic human feedback mechanism (Chavarriaga et al., 2014). It is an ERP that is elicited when a human perceives an error (Chavarriaga et al., 2014).

The existing body of research on ErrP suggests that ErrP signal is elicited under certain task situations. Response ErrP occurs when the subject is asked to respond as quickly as possible (e.g., choice reaction task) (Olvet and Hajcak, 2009). Feedback ErrP occurs when the subject realizes an error upon given feedback of the task (Lopez-Larraz et al., 2010). Interaction ErrP occurs when the subject is interacting with a machine, and the machine misinterpreted an instruction given (Ferrez and Del R. Millán, 2008). Observation ErrP occurs when the subject recognizes an error made by a machine or external system (Roset et al., 2014). Recently, three new types of errors, namely target, outcome, and execution ErrPs have been reported (Milekovic et al., 2013). To date, a number of studies have investigated the ErrP signal and its applicability in the EEG-based BCIs (Olvet and Hajcak, 2008; Chavarriaga et al., 2014; Weinberg et al., 2015; Kim et al., 2017). In Omedes et al. (2018), authors developed a 3D virtual interface that simulated participants’ hand to reach and grasp different virtual objects and found that an ErrP evokes in erroneous commands. In Kim et al. (2017), ErrP was employed to detect if a robot has made an error in recognizing the gesture made by the participant. In Yazmir and Reiner (2017), authors developed a virtual tennis game in which a difference in EEG response was observed when the participant successfully hit to that of miss the target.

Although significant research has been carried out on ErrP, there is no single study which discusses the feasibility of ErrP in implementing assist-as-needed robot therapy approach. With the aim of filling the gap mentioned above in BCI based methods, in this study we investigated if an ErrP signal is evoked when a participant is unable to perform a physical exercise. Fifteen stroke patients participated in this EEG experiment in which they performed a standard rehabilitation exercise. We hypothesized that a difference similar to error-related potentials will exist when the stroke patients are unable to perform a rehabilitation exercise (failure trial) to that of when they complete the same rehabilitation exercise (success trial) in a given time. Results of this study will provide a novel basis for the BCI based methods to be implement in the AAN based robot therapy, hence forming a foundation of a new type of task situation in which the ErrP brain signal can be elicited. This will assist in differentiating a failure trial against a success trial in performing a rehabilitation exercise. The developed ErrP based brain-in-the-loop approach is expected to enhance the efficiency of robot-based stroke rehabilitation programs.

Task Description

Participants sat on a comfortable chair facing the LCD monitor (resolution of 1280 × 720 and refresh rate of 100 Hz) that delivered task instructions to the participants.

The experiment required participants to perform a standard Bobath’s rehabilitation exercise: shoulder flexion-extension while adjoining both hands.

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