Postural Control as a Probe for Cognitive State: Exploiting Human Information Processing to Enhance Performance

Cognitive workload assessment plays an important role to examine the mental status of brain for emergency situations faced by air traffic controllers, military personals and many more. It is also significant for brain disorder diagnosis and psychological health monitoring. Mental workload induced by various factors needs to be critically examined for better decisions. This paper presents an automated model for cognitive workload assessment to provide accurate categorization on intensity of workload induced by multitasking situations. Statistical wavelets corresponding to brain frequencies act as features for categorization task. The brain analysis needs technical expertise to identify the relevant information but, due to lack of sufficient number of experts, feature selection model helps to identify the relevant features responsible to categorize cognitive workload. Teaching Learning based Optimization (TLBO) method has been modified using `Logical Operators' for binary feature selection problem in the current study and evaluated based on different parameters. Results on Logical TLBO reached upto 100% for binary and multiclass classification of cognitive workload. The results also show the proposed method is converging in minimum iteration for multiclass cognitive workload. PROMETHEE based multi-criteria decision-making approach has adopted for ranking of algorithm to select the best algorithm when multiple alternatives are available. Based on study of current literature, this approach appears to be first time implemented to provide ranking of optimization algorithms. The PROMETHEE method also suggests that the Logical TLBO is best among all the other compared approaches.

The topic of brain-computer interface is gaining increasing attention annually, yet there is limited research on confirming the reliability of Chinese indigenous chips in EEG signal acquisition. To demonstrate the progressiveness of Chinese indigenous chips, this article compares the performance of two ADC, ADS1299 and LHE7909, in EEG applications, with ADS1299 already proven reliable in multiple studies. Both chips demonstrate reliability in capturing high-quality EEG signals with the measured amplitude error below 2%. They show remarkably similar characteristics in the performance of SSVEP, oddball experiments and cognitive workload assessments on five participants from both genders and various age groups. LHE7909 even excels in capturing subtle EEG features such as the third harmonic components evoked in SSVEP in response to 13Hz stimulation, particularly in cognitive workload assessment, though tending to generate slightly more low-frequency noise. When it comes to P300 detection, LHE7909 shows a positive wave at approximately 340ms after the stimuli, in contrast to the ADS1299 which has a 360ms latency. These findings underscore the potential advantages of Chinese indigenous chips in EEG research.

Cognitive and emotional factors influence specific domains of postural control in individuals with moderate-to-severe Parkinson’s disease

In the field of neuroeconomics, the assessment of cognitive workload is a crucial issue with significant implications for real-world applications. Previous research has made progress in task-based germane cognitive load classification, but decentralized studies focusing on task-independent assessment have often produced less than optimal results. In this study, we present a stacked graph attention convolutional networks (SGATCNs) model to tackle the challenges related to task-independent cognitive workload assessment using EEG spatial information. The model employs the differential entropy (DE) and power spectral density (PSD) features of each EEG channel across four frequency bands (delta, theta, alpha, and beta) as node information. For the construction of the network structure, phase-locked values (PLVs), phase-lag indices (PLIs), Pearson correlation coefficients (PCCs), and mutual information (MI) are utilized and evaluated to generate a functional brain network. Specifically, the model aggregates spatial information on the dynamic map by stacking the graph attention layers and utilizes the convolution module to extract the frequency domain information from between the networks under each frequency band. We conducted a cognitive workload experiment with 15 subjects and selected three representative psychological experimental task paradigms (N-back, mental arithmetic, and Sternberg) to induce different levels of cognitive workload (low, medium, and high). Our framework achieved an average accuracy of 65.11% in recognizing the task-independent cognitive workload across the three scenarios.

Effects of assistive devices on postural control following a balance disturbance along the anterior-posterior direction.

Mental workload during high-effort tasks is a crucial measure of effective task performance. Maintaining cognitive demands within an individual's capacity enables the effective performance of complex multi-tasking. Conversely, surpassing this margin may lead to unpredictable and suboptimal performance. This review explores human mental workload assessment across real-world tasks like aircraft piloting, vehicle driving under challenging conditions, and automated power plant monitoring. Both subjective and objective monitoring methods are examined: subjective methods include the widely used NASA-TLX, while objective methods cover EEG and eye-tracking measures during task execution. Findings from these methods are correlated with overall task performance outcomes. Real-time workload monitoring provides distinct advantages in critical settings; for instance, if an operator’s cognitive capacity is reached, alerts could be triggered, or task demands adjusted to alleviate overload. Finally, a multi-modal analysis of the literature is presented, comparing the effectiveness of various monitoring technologies across different task domains to guide future research directions.

Is there an association between variables of postural control and strength in adolescents? The risk of sustaining sport injuries is particularly high in adolescents. Deficits in postural control and muscle strength represent 2 important intrinsic injury risk factors. Therefore, the purpose of this study was to investigate the relationship between variables of static and dynamic postural control and isometric and dynamic muscle strength and to find out whether there is an association between measures of postural control and muscle strength. Twenty-eight adolescents participated in this study (age 16.8 ± 0.6 years; body mass index 20.5 ± 1.8 kg · m(-2)). Biomechanic tests included the measurements of maximal isometric leg extension force (MIF) and rate of force development (RFDmax) of the leg extensors on a leg press with the feet resting on a force platform, vertical jumping force, and height (countermovement jump [CMJ]) on a force plate and the assessment of static (1-legged stance on a balance platform) and dynamic (mediolateral perturbation impulse on a balance platform) postural control. The significance level was set at p < 0.05. No significant associations were observed between measures of static and dynamic postural control. Significant positive correlations were detected between variables of isometric and dynamic muscle strength with r-values ranging from 0.441 to 0.779 (p < 0.05). Based on these models, a 100-N increase in MIF of the leg extensors was associated with 3.9, 4.2, and 6.5% better maximal CMJ force, CMJ height, and RFDmax, respectively. No significant correlations were observed between variables of postural control and muscle strength. The nonsignificant correlation between static/dynamic postural control and muscle strength implies that primarily dynamic measures of postural control should be incorporated in injury risk assessment and that postural control and muscle strength are independent of each other and may have to be trained complementary for lower extremity injury prevention and rehabilitation purposes.

With age, a decline in motor and cognitive functionality is inevitable, and it greatly affects the quality of life of the elderly and their ability to live independently. Early detection of these types of decline can enable timely interventions and support for maintaining functional independence and improving overall well-being. This paper explores the potential of the GAME2AWE platform in assessing the motor and cognitive condition of seniors based on their in-game performance data. The proposed methodology involves developing machine learning models to explore the predictive power of features that are derived from the data collected during gameplay on the GAME2AWE platform. Through a study involving fifteen elderly participants, we demonstrate that utilizing in-game data can achieve a high classification performance when predicting the motor and cognitive states. Various machine learning techniques were used but Random Forest outperformed the other models, achieving a classification accuracy ranging from 93.6% for cognitive screening to 95.6% for motor assessment. These results highlight the potential of using exergames within a technology-rich environment as an effective means of capturing the health status of seniors. This approach opens up new possibilities for objective and non-invasive health assessment, facilitating early detections and interventions to improve the well-being of seniors.

In the future, cognitive activity will be tracked in the same way how physical activity is tracked today. Eye-tracking technology is a promising off-body technology that provides access to relevant data for cognitive activity tracking. For building cognitive state models, continuous and longitudinal collection of eye-tracking and self-reported cognitive state label data is critical. In a field study with 11 students, we use experience sampling and our data collection system esmLoop to collect both cognitive state labels and eye-tracking data. We report descriptive results of the field study and develop supervised machine learning models for the detection of two eye-based cognitive states: cognitive load and flow. In addition, we articulate the lessons learned encountered during data collection and cognitive state model development to address the challenges of building generalizable and robust user models in the future. With this study, we contribute knowledge to bring eye-based cognitive state detection closer to real-world applications.

The current study aimed to investigate the dynamic changes in brain glymphatic function during chemotherapy in breast cancer patients (BCP) and their correlation with cognitive function. A total of 40 healthy female participants (control group) and 80 female BCP were included. Various cognitive assessment tools were used to evaluate cognitive function. Diffusion tensor imaging along the perivascular space was employed to measure brain glymphatic function. Following chemotherapy, BCP exhibited a significant decline in various cognitive scores. After chemotherapy, the along the perivascular space index, a parameter indicating brain glymphatic function, was slightly higher than that at baseline and the control group levels and was correlated with cognitive scores. This study unveiled a close relationship between the dynamic changes in brain glymphatic function after chemotherapy and cognitive function in BCP. Our findings contribute to a deeper understanding of the brain mechanisms underlying chemotherapy-related cognitive impairment and provide a theoretical basis for future interventions and treatments. In addition, they offer a new perspective for exploring the relationship between brain function and cognitive states.

Psychological factors may be important in the assessment and management of ankylosing spondylitis (AS). Our primary objective was to describe associations between disease and psychological status in AS, using AS-specific assessment tools and questionnaires. Our secondary objectives were to identify patient subgroups based on such associations and to determine the stability of the measures over time. A total of 110 patients were assessed at 6-monthly intervals up to four times using tools to measure disease [Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI) and the Bath Ankylosing Spondylitis Metrology Index (BASMI)], psychological [Hospital Anxiety and Depression Questionnaire (HADS), Health Locus of Control-Form C Questionnaire (HLC-C)] and generic health [Short form (SF)-36] status. Eighty-nine participants completed all four assessments. Throughout the study, BASDAI, BASFI and BASMI scores correlated significantly with anxiety, depression, internality and health status, but not with levels of belief in chance or powerful others. Clinically anxious or depressed subgroups had significantly worse BASDAI and BASFI, but not BASMI, scores. BASMI scores were the least closely linked to psychological status. Mean scores for disease, psychological and health status were clinically stable over the 18 months period. Disease status scores in AS correlated significantly with anxiety, depression, internality and health status. Interpretation of AS disease scores should take an account of psychological status and the choice of measures used. These findings have important potential applications in AS management and monitoring, including the identification of patients for biological therapies.

Objective This study aimed to assess the validity and reliability of the Turkish version of the Brief Cognitive Assessment Tool (BCAT) in differentiating between older adults with major Neurocognitive Disorder (MNCD) and mild neurocognitive disorder (MiNCD), and cognitively normal (CN) individuals. Method Participants were categorized into MNCD (n = 152), MiNCD (n = 73), and CN (n = 53) groups by Diagnostic and Statistical Manual of Mental Disorders-5 criteria. The BCAT was translated and culturally adapted into Turkish. All participants completed the BCAT, Mini Mental State Examination, Montreal Cognitive Assessment (MoCA), Clock Drawing Test, and Öktem’s Auditory Verbal Learning Test. Internal consistency, test–retest reliability, and concurrent validity with MoCA were assessed. Receiver operating characteristic analysis was employed to determine a cutoff point for BCAT. Results BCAT scores showed high internal consistency and test–retest reliability. BCAT and MoCA scores correlated strongly, confirming convergent validity. MNCD group had lower BCAT scores than MiNCD and CN across multiple cognitive domains. At a cutoff score of 33, BCAT distinguished MNCD from MiNCD and CN. Conclusions Our findings suggest that the Turkish version of the BCAT is a valid and reliable screening tool for cognitive impairment in older adults. It effectively differentiates between MNCD, MiNCD, and CN individuals, supporting its clinical utility for early detection of neurocognitive disorders.

I call illocutionary externalism (IE) the approach to the study of illocutionary force that I favor. IE is inspired by Austin's seminal ideas on performatives and speech acts. According to IE, in the analysis of a paradigmatic illocutionary force we must essentially mention some aspects of the social and natural environment that cannot be reduced to the (de dicto) speakers' mental states, no matter how these are individuated. A difficult problem for IE derives from the possibility of making explicit the force of an utterance. This fact invites us to focus our attention on the utterer (the person who makes the force explicit) and his mental states (illocutionary intentions), and to support a mentalist approach in the study of forces. In this article I shall argue for the compatibility of IE with the phenomenon of the explicitability of illocutionary force.

In pregnant women, the standing posture changes as the fetus develops. Increased loading on the lumbar spine and abdominal muscles causes a shift of the head position in the posterior direction and increases the lumbar lordosis and anterior pelvic tilt. These changes in body alignment will influence the control of standing posture. Also, mental states including anxiety also influence the sensory organization and motor control for postural balance. PURPOSE: The present study investigated the influences of walking exercise on postural control and mental condition during pregnancy. METHODS: Control group (n=6, age 28.5±5.4yrs, 21-26 weeks) and walking group (n=9, age 31.7±5.6yrs, 18-26 weeks) pregnant women subjects participated in this study. Body composition of the subjects was measured by bio-impedance method. After that, the grip strength, aerobic capacity test (3 minutes walking test) of all subjects were measured. The displacement of the center of pressure (COP) of ground reaction forces were recorded at a frequency of 50 Hz while the subjects were standing still on a portable gravicorder for 30 seconds, and the total length of COP displacements (LNG) was calculated. The walking group pregnant women subjects were performed four or five times a week for 12 weeks to walking 20 to 30 minutes once. Before and after 12 weeks, the psychological state was investigated by the Profile of Mood States (POMS) questionnaire RESULTS: Body weight was significantly increased in both control (8.5%) and walking group (12.5%) after 12 weeks. Estimated skeletal muscle mass has increased significantly in the walking group (pre; 35.0±1.9kg, post; 36.8±1.6kg, p<0.01), however, the control group did not change. In comparison with the control group, the walking group were significantly decreased in LNG (33.9±7.6 vs. 24.9±6.6cm, p<0.05). Of the POMS scores, that for Anger decreased after the 12 weeks in walking group (44.4±4.56 vs. 40.1±2.7cm, p<0.05), however, the control group did not change. There was a significant negative correlation between LNG and Anger score of POMS (r=-0.787, p<0.05). CONCLUSIONS: The results showed that walking improves posture control and mental condition during pregnancy. The present study suggest that regular aerobic exercise during pregnancy appears to improve (or maintain) physical and mental fitness.

Assessment has the purpose to determine the attainment of educational objectives. There are three domains of assessment: cognitive, affective, and psychomotor. The cognitive domain focuses on assessing knowledge, comprehension, and intellectual thinking. Cognitive assessment tools can be designed through the utilization of authentic assessments, which replicate real-world situations or contexts. Authentic assessment methodologies offer a more precise means of evaluating a student's capacity to apply acquired concepts. This research had the purpose to investigate the development of cognitive assessment instruments within the independent curriculum at MTs Negeri 1 East Lombok. This qualitative research utilized a field-based approach, collecting data through teacher observations and interviews conducted at MTs Negeri 1 East Lombok. The data analysis process included data reduction, presentation, and inference. The outcomes suggested that cognitive domain assessment instruments in the independent curriculum should be in alignment with the learning objectives, integrate various question types, involve students in their development, and provide constructive feedback.