Translation, cultural adaptation, and validation of the Spanish version of the Movement Imagery Questionnaire-3 (MIQ-3)

Acute Stress Does Not Affect Motor Imagery Ability in Young, Healthy Participants: A Randomized Trial

Motor imagery (MI) is the mental representation of a movement without its execution. It activates internal representations of the movement without external stimulus through different memory-related processes. Although acute stress is frequent in the population and affects supraspinal structures essential for memory functionality, it is still unknown how that stress affects MI capacity and temporal congruence (TC) between execution and movement imagination. This study aimed to discover how acute stress may influence MI capacity and TC in the subscales of internal and external visual imagery and kinesthetic imagery. A double-blind, randomized trial was conducted. Sixty-two young, healthy subjects (mean age = 20.65 [2.54]; 39 females and 23 males) unfamiliar with the assessment and uses of MI were recruited. Participants were assigned by stratified randomization to the stress group or the control group. Stress was induced by the Maastricht Acute Stress Test (MAST), while the control group performed the MAST control protocol. MI capacity and TC were assessed before (t1) and after (t2) MAST stress or control using the Movement Imagery Questionnaire-3 (MIQ-3). Electrodermal activity and heart rate variability were further recorded as control variables to assess stress induction. Thirty subjects in the stress group and 26 subjects in the control group were analyzed. No significant group differences were observed when comparing MI capacity or TC in any subscales. These findings suggest that acute stress does not significantly affect MI capacity or TC in young, healthy, non-experienced MI subjects. MI could thus be a relevant helpful technique in stressful situations.

The Development and Evaluation of the Kinesthetic Motor Imagery of Pelvic Floor Muscle Contraction Questionnaire (KMI-PFQ) in Spanish Women

Practitioners have begun using motor imagery (MI) for preventing and treating some pelvic floor disorders. Due to requirements for imagining before performing a MI intervention and because there are few instruments available for assessing this specific ability in the pelvic floor musculature, we sought to develop and test a new MI questionnaire, the Kinesthetic Motor Imagery of Pelvic Floor Muscle Contraction Questionnaire (KMI-PFQ). We focused in this study on the development and analysis of the instrument's factorial structure and internal reliability in a participant sample of 162 healthy Spanish women (M age = 20.1, SD = 2.2 years). We developed and evaluated the KMI-PFQ's psychometric properties, finding it to have good internal consistency, with Cronbach's α = .838, ω coefficient = .839, and an intraclass correlation coefficient = .809, with two factors ("ability" and "mental effort") explaining 58.36% of response variance. The standard error of measurement was 3.58, and the minimal detectable change was 9.92. No floor or ceiling effects were identified. There was also good convergent validity as seen by statistically significant positive correlations between KMI-PFQ scores and the revised-Movement Image Questionnaire and Vividness of Visual Imagery Questionnaire. There were no statistically significant correlations between KMI-PFQ scores and the Orientation to Life Questionnaire. The KMI-PFQ is a valid and reliable instrument for measuring kinesthetic ability to feel/imagine pelvic floor muscle contractions in healthy Spanish women.

Development and Validation of the Combined Action Observation and Motor Imagery Ability Questionnaire

Combined use of action observation and motor imagery (AOMI) is an increasingly popular motor-simulation intervention, which involves observing movements on video while simultaneously imagining the feeling of movement execution. Measuring and reporting participant imagery-ability characteristics are essential in motor-simulation research, but no measure of AOMI ability currently exists. Accordingly, the AOMI Ability Questionnaire (AOMI-AQ) was developed to address this gap in the literature. In Study 1, two hundred eleven participants completed the AOMI-AQ and the kinesthetic imagery subscales of the Movement Imagery Questionnaire-3 and Vividness of Motor Imagery Questionnaire-2. Following exploratory factor analysis, an 8-item AOMI-AQ was found to correlate positively with existing motor-imagery measures. In Study 2, one hundred seventy-four participants completed the AOMI-AQ for a second time after a period of 7-10 days. Results indicate a good test-retest reliability for the AOMI-AQ. The new AOMI-AQ measure provides a valid and reliable tool for researchers and practitioners wishing to assess AOMI ability.

Brain-machine interface based on deep learning to control asynchronously a lower-limb robotic exoskeleton: a case-of-study

BACKGROUND

This research focused on the development of a motor imagery (MI) based brain-machine interface (BMI) using deep learning algorithms to control a lower-limb robotic exoskeleton. The study aimed to overcome the limitations of traditional BMI approaches by leveraging the advantages of deep learning, such as automated feature extraction and transfer learning. The experimental protocol to evaluate the BMI was designed as asynchronous, allowing subjects to perform mental tasks at their own will.

METHODS

A total of five healthy able-bodied subjects were enrolled in this study to participate in a series of experimental sessions. The brain signals from two of these sessions were used to develop a generic deep learning model through transfer learning. Subsequently, this model was fine-tuned during the remaining sessions and subjected to evaluation. Three distinct deep learning approaches were compared: one that did not undergo fine-tuning, another that fine-tuned all layers of the model, and a third one that fine-tuned only the last three layers. The evaluation phase involved the exclusive closed-loop control of the exoskeleton device by the participants' neural activity using the second deep learning approach for the decoding.

RESULTS

The three deep learning approaches were assessed in comparison to an approach based on spatial features that was trained for each subject and experimental session, demonstrating their superior performance. Interestingly, the deep learning approach without fine-tuning achieved comparable performance to the features-based approach, indicating that a generic model trained on data from different individuals and previous sessions can yield similar efficacy. Among the three deep learning approaches compared, fine-tuning all layer weights demonstrated the highest performance.

CONCLUSION

This research represents an initial stride toward future calibration-free methods. Despite the efforts to diminish calibration time by leveraging data from other subjects, complete elimination proved unattainable. The study's discoveries hold notable significance for advancing calibration-free approaches, offering the promise of minimizing the need for training trials. Furthermore, the experimental evaluation protocol employed in this study aimed to replicate real-life scenarios, granting participants a higher degree of autonomy in decision-making regarding actions such as walking or stopping gait.

Exploring EEG-based motor imagery decoding: a dual approach using spatial features and spectro-spatial Deep Learning model IFNet

Introduction

In recent years, the decoding of motor imagery (MI) from electroencephalography (EEG) signals has become a focus of research for brain-machine interfaces (BMIs) and neurorehabilitation. However, EEG signals present challenges due to their non-stationarity and the substantial presence of noise commonly found in recordings, making it difficult to design highly effective decoding algorithms. These algorithms are vital for controlling devices in neurorehabilitation tasks, as they activate the patient's motor cortex and contribute to their recovery.

Methods

This study proposes a novel approach for decoding MI during pedalling tasks using EEG signals. A widespread approach is based on feature extraction using Common Spatial Patterns (CSP) followed by a linear discriminant analysis (LDA) as a classifier. The first approach covered in this work aims to investigate the efficacy of a task-discriminative feature extraction method based on CSP filter and LDA classifier. Additionally, the second alternative hypothesis explores the potential of a spectro-spatial Convolutional Neural Network (CNN) to further enhance the performance of the first approach. The proposed CNN architecture combines a preprocessing pipeline based on filter banks in the frequency domain with a convolutional neural network for spectro-temporal and spectro-spatial feature extraction.

Results and discussion

To evaluate the approaches and their advantages and disadvantages, EEG data has been recorded from several able-bodied users while pedalling in a cycle ergometer in order to train motor imagery decoding models. The results show levels of accuracy up to 80% in some cases. The CNN approach shows greater accuracy despite higher instability.

Reliability of the Spanish Version of the Movement Imagery Questionnaire-3 (MIQ-3) and Characteristics of Motor Imagery in Institutionalized Elderly People

Motor imagery (MI) training is increasingly used to improve the performance of specific motor skills. The Movement Imagery Questionnaire-3 (MIQ-3) is an instrument for assessing MI ability validated in Spanish although its reliability has not yet been studied in the elderly population. The main objective of this study was to test its reliability in institutionalized elderly people. Secondarily, we studied whether there are differences according to gender and age in MI ability (measured by the MIQ-3) and in temporal congruency (measured by mental chronometry of elbow and knee flexion-extension and getting up and sitting down from chair movements). The subjects were 60 elderly, institutionalized, Spanish-speaking individuals without cognitive impairment or dementia, and aged between 70 and 100 years. Cronbach's alpha showed high internal consistency in the internal visual and external visual subscales and moderate in the kinesthetic subscale. The intraclass correlation coefficient showed good test-retest reliability for all three subscales. Mixed factorial analysis of variances (ANOVAs) showed that MI ability decreased with increasing age range, the imagery time decreased concerning the execution of the same movement, and there were no gender differences in either IM ability or temporal congruence. The Spanish version of the MIQ-3 is a reliable instrument for measuring MI ability in institutionalized elderly.

Convergent validity and sex invariant factor structure of the Movement Imagery Questionnaire-3 - Second version (MIQ-3S): Healthy, young adult reference data

Aligned with the approach that established the factor structure of the Movement Imagery Questionnaire-3 (MIQ-3), this study extended the two-factor structure of the Movement Imagery Questionnaire - Revised Second version (MIQ-RS). The extension involves assessment of both internal and external visual imagery abilities along with kinesthetic imagery ability. Participants (N = 396) completed the new Movement Imagery Questionnaire - 3 Second Version (MIQ-3S) along with the Vividness of Movement Imagery Questionnaire-2 (VMIQ-2) which measure the same three imagery abilities. Alpha coefficients and between scale Spearman correlations for internal, external, and kinesthetic abilities indicated items were internally consistent (α > 0.87) and established convergent validity (r > 0.69), respectively. MIQ-3S scale means ranged from 5.56 (SD = 1.10) to 5.98 (SD = 0.84), with no differences by sex. The three scales were not multicolinear as intra-scale correlations ranged from 0.47 to 0.61, supporting the three abilities were related, but separate constructs. A multi-trait multimethod confirmatory factor analysis (MTMM CFA), with sex invariance, was conducted to confirm the 3-factor structure of the MIQ-3S. Results from 396 healthy male (n = 200) and female (n = 196) adult college-aged students (M = 21.91, SD = 2.37) indicated a correlated-traits correlated-uniqueness model provided the best fit to the data (CFI = 0.99; SRMR = 0.05; RMSEA = 0.03), while displaying sex invariance. These findings provide baseline data on college-aged, healthy adult participants providing reference data to those investigating imagery abilities among injured populations and practitioners interested in tracking individuals in rehabilitation.

Imagery ability assessments: a cross-disciplinary systematic review and quality evaluation of psychometric properties

BACKGROUND

Over the last two centuries, researchers developed several assessments to evaluate the multidimensional construct of imagery. However, no comprehensive systematic review (SR) exists for imagery ability evaluation methods and an in-depth quality evaluation of their psychometric properties.

METHODS

We performed a comprehensive systematic search in six databases in the disciplines of sport, psychology, medicine, education: SPORTDiscus, PsycINFO, Cochrane Library, Scopus, Web of Science, and ERIC. Two reviewers independently identified and screened articles for selection. COSMIN checklist was used to evaluate the methodological quality of the studies. All included assessments were evaluated for quality using criteria for good measurement properties. The evidence synthesis was summarised by using the GRADE approach.

RESULTS

In total, 121 articles reporting 155 studies and describing 65 assessments were included. We categorised assessments based on their construct on: (1) motor imagery (n = 15), (2) mental imagery (n = 48) and (3) mental chronometry (n = 2). Methodological quality of studies was mainly doubtful or inadequate. The psychometric properties of most assessments were insufficient or indeterminate. The best rated assessments with sufficient psychometric properties were MIQ, MIQ-R, MIQ-3, and VMIQ-2 for evaluation of motor imagery ability. Regarding mental imagery evaluation, only SIAQ and VVIQ showed sufficient psychometric properties.

CONCLUSION

Various assessments exist to evaluate an individual's imagery ability within different dimensions or modalities of imagery in different disciplines. However, the psychometric properties of most assessments are insufficient or indeterminate. Several assessments should be revised and further validated. Moreover, most studies were only evaluated with students. Further cross-disciplinary validation studies are needed including older populations with a larger age range. Our findings allow clinicians, coaches, teachers, and researchers to select a suitable imagery ability assessment for their setting and goals based on information about the focus and quality of the assessments.

SYSTEMATIC REVIEWS REGISTER

PROSPERO CRD42017077004 .