Older adults display diminished error processing and response in a continuous tracking task

Colino, Francisco L.; Howse, Harvey; Norton, Angela; Trska, Robert; Pluta, Anthony; Luehr, Stephen J. C.; Handy, Todd C.; Krigolson, Olave E.

doi:10.1111/psyp.12907

Cited by 11 publications

(12 citation statements)

References 50 publications

(80 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Together these features play a key role in developing a reliable ErrP-BCI for rehabilitation and ADL assisted functions. Besides, ErrP has been observed in children as young as five years old [77], young and older adults [78], [79].…”

Section: Error-related Potentialsmentioning

confidence: 99%

“…It is interesting to note that the ErrP has been shown to be affected by fatigue [80], [81], motivation [82], [83], anxiety [84], [85], personality traits [86], [87], age [78], [79], [88], ethnicity [89] and even gender [89] that increases the intertrial and inter-subject variability. Remarkably, the variability of the ErrP signals due to the traits mentioned above has led to the use of ErrP signals in a variety of fields.…”

Section: Error-related Potentialsmentioning

confidence: 99%

See 1 more Smart Citation

A Review of Error-Related Potential-Based Brain–Computer Interfaces for Motor Impaired People

et al. 2019

View full text Add to dashboard Cite

Regaining the lost functionality of limbs is the top priority for people with motor skills impairment as it directly affects their ability to execute activities of daily living and hence, worsens their quality of life. In the last two decades, a great deal of research has focused on error-related potential (ErrP) based brain-computer interfaces (BCIs). Many applications have been developed to assist motor-impaired people in their rehabilitation and among these are robots, spellers, gesture recognition systems, and braincontrolled wheelchairs. In this paper, we present a review of various ErrP based BCI that can potentially aid motor-disabled people in their rehabilitation and execution of their daily activities. First, we describe the ErrP phenomenon and its characteristics followed by a comprehensive application-driven discussion on ErrP based rehabilitation and assistive strategies for motor-impaired people, including studies conducted since the inception of ErrP to the current state-of-the-art applications. Lastly, we discuss the potential issues and challenges being faced by current state-of-the-art applications as well as important future pathways and research directions that might be adopted for advanced ErrP-BCIs used in clinical settings.

show abstract

Section: Error-related Potentialsmentioning

confidence: 99%

Section: Error-related Potentialsmentioning

confidence: 99%

A Review of Error-Related Potential-Based Brain–Computer Interfaces for Motor Impaired People

et al. 2019

View full text Add to dashboard Cite

show abstract

“…In general, ErrP is a reliable feedback signal. However, ErrP amplitude and latency are also prone to inter-subject and inter-trial variability (Pailing and Segalowitz, 2004 ; Colino et al, 2017 ). Additionally, ErrP is best elicited by discrete events (Kumar et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

A Noninvasive BCI System for 2D Cursor Control Using a Spectral-Temporal Long Short-Term Memory Network

Peng

Zhang

et al. 2022

Front. Comput. Neurosci.

View full text Add to dashboard Cite

Two-dimensional cursor control is an important and challenging problem in the field of electroencephalography (EEG)-based brain computer interfaces (BCIs) applications. However, most BCIs based on categorical outputs are incapable of generating accurate and smooth control trajectories. In this article, a novel EEG decoding framework based on a spectral-temporal long short-term memory (stLSTM) network is proposed to generate control signals in the horizontal and vertical directions for accurate cursor control. Precisely, the spectral information is used to decode the subject's motor imagery intention, and the error-related P300 information is used to detect a deviation in the movement trajectory. The concatenated spectral and temporal features are fed into the stLSTM network and mapped to the velocities in vertical and horizontal directions of the 2D cursor under the velocity-constrained (VC) strategy, which enables the decoding network to fit the velocity in the imaginary direction and simultaneously suppress the velocity in the non-imaginary direction. This proposed framework was validated on a public real BCI control dataset. Results show that compared with the state-of-the-art method, the RMSE of the proposed method in the non-imaginary directions on the testing sets of 2D control tasks is reduced by an average of 63.45%. Besides, the visualization of the actual trajectories distribution of the cursor also demonstrates that the decoupling of velocity is capable of yielding accurate cursor control in complex path tracking tasks and significantly improves the control accuracy.

show abstract

“…However, its magnitude is diminished in subjects with spinal cord injury and schizophrenic disorders [24][25]. ErrP amplitude and latency also suffer from inter-subject and inter-trial variability [26][27]. Lastly, ErrP is best elicited with discrete events [28].…”

Section: Introductionmentioning

confidence: 99%

A hybrid brain-computer interface for closed-loop position control of a robot arm

Rakshit

Konar

Nagar

2020

IEEE/CAA J. Autom. Sinica

View full text Add to dashboard Cite

Brain-Computer Interfacing has currently added a new dimension in assistive robotics. Existing brain-computer interfaces designed for position control applications suffer from two fundamental limitations. First, most of the existing schemes employ open-loop control, and thus are unable to track the positional errors, resulting in failures in taking necessary online corrective actions. There are traces of one or fewer works dealing with closed-loop EEG-based position control. The existing closedloop brain-induced position control schemes employ a fixed order link selection rule, which often creates a bottleneck for timeefficient control. Second, the existing brain-induced position controllers are designed to generate the position response like a traditional first-order system, resulting in a large steady-state error. This paper overcomes the above two limitations by keeping provisions for (Steady-State Visual Evoked Potential induced) link-selection in an arbitrary order as required for efficient control and also to generate a second-order response of the position-control system with gradually diminishing overshoots/undershoots to reduce steady-state errors. Besides the above, the third novelty is to utilize motor imagery and P300 signals to design the hybrid brain-computer interfacing system for the said application with gradually diminishing error-margin by speed reversal at the zero-crossings of positional errors. Experiments undertaken reveal that the steady-state error is reduced to 0.2%. The paper also provides a thorough analysis of stability of the closed-loop system performance using Root Locus technique.

show abstract

Older adults display diminished error processing and response in a continuous tracking task

Cited by 11 publications

References 50 publications

A Review of Error-Related Potential-Based Brain–Computer Interfaces for Motor Impaired People

A Review of Error-Related Potential-Based Brain–Computer Interfaces for Motor Impaired People

A Noninvasive BCI System for 2D Cursor Control Using a Spectral-Temporal Long Short-Term Memory Network

A hybrid brain-computer interface for closed-loop position control of a robot arm

Contact Info

Product

Resources

About