Heart rate variability (HRV) has the potential to be a predicting factor of cognitive performance. The present research aimed to explore the differences in neurocognitive performance of workers with ...high HRV and low HRV. A total of 48 white-collar workers and 53 blue-collar workers were assessed. An electrocardiogram was used to obtain HRV data, whereby a 10 min baseline and an active (neuropsychological task) recording were taken. Median splits were performed on data to obtain high- and low-HRV groups. The Cambridge Neuropsychological Test Automated Battery, specifically, the spatial working memory, attention-switching task, rapid visual processing, and spatial span were used. Higher HRV (RMSSD and HF) was linked to better neurocognitive performance measures. Interestingly, the blue- and white-collar groups exhibited different correlations and, in some cases, showed an inverse relationship with the same variables. The differences observed in the present study demonstrate the importance of assessing task-dependent HRV parameters.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Fatigue and sleepiness are complex bodily states associated with monotony as well as physical and cognitive impairment, accidents, injury, and illness. Moreover, these states are often characteristic ...of professional driving. However, most existing work has focused on motor vehicle drivers, and research examining train drivers remains limited. As such, the present study psychophysiologically examined monotonous driving, fatigue, and sleepiness in a group of passenger train drivers and a group of non-professional drivers. Sixty-three train drivers and thirty non-professional drivers participated in the present study, which captured 32-lead electroencephalogram (EEG) data during a monotonous driving task. Fatigue and sleepiness were self-evaluated using the Pittsburgh Sleep Quality Index, the Epworth Sleepiness Scale, the Karolinksa Sleepiness Scale, and the Checklist of Individual Strength. Unexpectedly, fatigue and sleepiness scores did not significantly differ between the groups; however, train drivers generally scored lower than non-professional drivers, which may be indicative of individual and/or industry attempts to reduce fatigue. Across both groups, fatigue and sleepiness scores were negatively correlated with theta, alpha, and beta EEG variables clustered towards the fronto-central and temporal regions. Broadly, these associations may reflect a monotony-associated blunting of neural activity that is associated with a self-reported fatigue state.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Modern work environments have extensive interactions with technology and greater cognitive complexity of the tasks, which results in human operators experiencing increased mental workload. Air ...traffic control operators routinely work in such complex environments, and we designed tracking and collision prediction tasks to emulate their elementary tasks. The physiological response to the workload variations in these tasks was elucidated to untangle the impact of workload variations experienced by operators. Electroencephalogram (EEG), eye activity, and heart rate variability (HRV) data were recorded from 24 participants performing tracking and collision prediction tasks with three levels of difficulty. Our findings indicate that variations in task load in both these tasks are sensitively reflected in EEG, eye activity and HRV data. Multiple regression results also show that operators' performance in both tasks can be predicted using the corresponding EEG, eye activity and HRV data. The results also demonstrate that the brain dynamics during each of these tasks can be estimated from the corresponding eye activity, HRV and performance data. Furthermore, the markedly distinct neurometrics of workload variations in the tracking and collision prediction tasks indicate that neurometrics can provide insights on the type of mental workload. These findings have applicability to the design of future mental workload adaptive systems that integrate neurometrics in deciding not just "when" but also "what" to adapt. Our study provides compelling evidence in the viability of developing intelligent closed-loop mental workload adaptive systems that ensure efficiency and safety in complex work environments.
Title. Psychological, lifestyle and coping contributors to chronic fatigue in shift‐worker nurses
Aim. This paper is a report of a study to assess the following in shift‐worker nurses: (1) the ...relationships amongst chronic fatigue and psychological variables including anxiety, mood and locus of control; (2) the relationships amongst chronic fatigue and a number of lifestyle factors such as shiftwork, sleep and exercise; and (3) various coping behaviours that best predict chronic fatigue.
Background. In the shift‐working population, individual psychological, lifestyle and coping differences influence fatigue levels. However, some of these factors are somewhat unexplored and their relative contribution to fatigue remains poorly understood.
Methods. An exploratory design was adopted with 111 eldercare shift‐worker nurses. Data were collected during 2006. Nurses completed self‐administered questionnaires examining fatigue, anxiety, mood disturbance, locus of control, sleep, work, lifestyle and coping characteristics.
Findings. Multiple regressions showed that mood disturbance, locus of control and trait anxiety are statistically significant predictors of chronic fatigue. Poor sleep quality was the lifestyle factor which most strongly contributed to fatigue. Other lifestyle predictors included higher workload perception, lack of exercise and the non‐availability of support. Whilst problem‐focused coping behaviours were not associated with fatigue, coping by using alcohol, letting emotions out and avoiding the situation significantly predicted chronic fatigue.
Conclusion. The challenge for improving the fatigue outcomes requires further investigation of the profile of a nurse who is at a high risk of fatigue, and then integrating this profile into a fatigue management programme which considers relative contributions of the psychological, lifestyle and coping factors.
Cognitive impairment is traditionally identified via cognitive screening tools that have limited ability in detecting early or transitional stages of impairment. The dynamic nature of physiological ...variables such as the electroencephalogram (EEG) may provide alternate means for detecting these transitions. However, previous research examining EEG and cognitive performance is largely confined to samples with diagnosed cognitive impairments, and research examining non-impaired, and occupation specific samples, is limited. The present study aimed to investigate the associations between frontal pole and central EEG and cognitive performance in a sample of male and female nurses, and to determine the significance of these associations. Fifty seven nurses participated in the study, in which two lead bipolar EEG was recorded at positions Fp1 (frontal polar), Fp2, C3 (central) and C4 during a baseline and an active phase involving the common neuropsychological Stroop test. Participants' cognitive performance was assessed using the mini-mental state exam (MMSE) and Cognistat screening tools. Significant correlations between EEG beta activity and the outcome of MMSE and Cognistat were revealed, where an increased beta activity was associated to an increased global cognitive performance. Additionally, domain specific cognitive performance was also significantly associated to various EEG variables. The study identified potential EEG biomarkers for global and domain specific cognitive performance, and provides initial groundwork for the development of future EEG based biomarkers for detection of cognitive pathologies.
Objective: To investigate the relationship between EEG activity and the global and domain specific cognitive performance of healthy nurses, and determine the predictive capabilities of these ...relationships. Approach: Sixty-four nurses were recruited for the present study, and data from 61 were utilised in the present analysis. Global and domain specific cognitive performance of each participant was assessed psychometrically using the Mini-mental state exam and the Cognistat, and a 32-lead monopolar EEG was recorded during a resting baseline phase and an active phase in which participants completed the Stroop test. Main results: Global cognitive performance was successfully predicted (81%-85% of variance) by a combination of fast wave activity variables in the alpha, beta and theta frequency bands. Interestingly, predicting domain specific performance had varying degrees of success (42%-99% of the variance predicted) and relied on combinations of both slow and fast wave activity, with delta and gamma activity predicting attention performance; delta, theta, and gamma activity predicting memory performance; and delta and beta variables predicting judgement performance. Significance: Global and domain specific cognitive performance of Australian nurses may be predicted with varying degrees of success by a unique combination of EEG variables. These proposed models image transitory cognitive declines and as such may prove useful in the prediction of early cognitive impairment, and may enable better diagnosis, and management of cognitive impairment.
Objective: Mental stress is a major problem in our society and has become an area of interest for many psychiatric researchers. One primary research focus area is the identification of bio-markers ...that not only identify stress but also predict the conditions (or tasks) that cause stress. Electroencephalograms (EEGs) have been used for a long time to study and identify bio-markers. While these bio-markers have successfully predicted stress in EEG studies for binary conditions, their performance is suboptimal for multiple conditions of stress. Methods: To overcome this challenge, we propose using latent based representations of the bio-markers, which have been shown to significantly improve EEG performance compared to traditional bio-markers alone. We evaluated three commonly used EEG based bio-markers for stress, the brain load index (BLI), the spectral power values of EEG frequency bands (alpha, beta and theta), and the relative gamma (RG), with their respective latent representations using four commonly used classifiers. Results: The results show that spectral power value based bio-markers had a high performance with an accuracy of 83%, while the respective latent representations had an accuracy of 91%.
Chronic heart failure (CHF) is associated with a high comorbidity burden, adverse impact on quality of life and high health care utilisation. Peripheral arterial disease (PAD) and CHF share many ...risk, pathophysiological and prognostic features, and each has been associated with increased morbidity and mortality. PAD often goes undetected, and yet in spite of the availability of screening tools, this is not commonly considered in CHF care. A review of the electronic databases Medline, CINAHL and Cochrane CENTRAL was undertaken using the MeSH terms peripheral arterial disease, peripheral vascular disease, intermittent claudication and heart failure to identify studies examining the prevalence and clinical outcomes of coexisting PAD in patients with CHF. Five studies were identified. There are limited data describing the impact of PAD on CHF outcomes. As PAD may contribute to decreased capacity to exercise and other self-care behaviours, identifying those at risk and providing appropriate therapy are important. Based on this review, patients who are smokers and those with diagnosed coronary heart disease and diabetes should be targeted for the screening of PAD.
Assessment of heart rate variability (reflective of the cardiac autonomic nervous system) has shown some predictive power for stress. Further, the predictive power of the distinct patterns of ...cortical brain activity and - cardiac autonomic interactions are yet to be explored in the context of acute stress, as assessed by an electrocardiogram and electroencephalogram. The present study identified distinct patterns of neural-cardiac autonomic coupling during both resting and acute stress states. In particular, during the stress task, frontal delta waves activity was positively associated with low-frequency heart rate variability and negatively associated with high-frequency heart rate variability. Low high-frequency power is associated with stress and anxiety and reduced vagal control. A positive association between resting high-frequency heart rate variability and frontocentral gamma activity was found, with a direct inverse relationship of low-frequency heart rate variability and gamma wave coupling at rest. During the stress task, low-frequency heart rate variability was positively associated with frontal delta activity. That is, the parasympathetic nervous system is reduced during a stress task, whereas frontal delta wave activity is increased. Our findings suggest an association between cardiac parasympathetic nervous system activity and frontocentral gamma and delta activity at rest and during acute stress. This suggests that parasympathetic activity is decreased during acute stress, and this is coupled with neuronal cortical prefrontal activity. The distinct patterns of neural-cardiac coupling identified in this study provide a unique insight into the dynamic associations between brain and heart function during both resting and acute stress states.
Atherosclerosis is the underlying cause of most myocardial infarction (MI) and ischaemic stroke episodes. An early sign of atherosclerosis is hypertrophy of the arterial wall. It is known that ...increased intima media thickness (IMT) is a non-invasive marker of arterial wall alteration, which can easily be assessed in the carotid arteries by high-resolution B-mode ultrasound. Similarly, the other key element of MI and ischaemic strokes is the N-methyl-D-aspartate (NMDA) receptor which is an ionotropic glutamate receptor that mediates the vast majority of excitatory neurotransmission in the brain. NMDA activation requires the binding of both glutamate and a coagonist like D-serine to its glycine site. A special enzyme, serine racemase (SR), is required for the conversion of L-serine into D-serine, and alterations in SR activities lead to a variety of physiological and pathological conditions ranging from synaptic plasticity to ischemia, MI, and stroke. The amount of D-serine available for the activation of glutamatergic signalling is largely determined by SR and we have developed ways to estimate its levels in human blood samples and correlate it with the IMT. This research based short communication describes our pilot study, which clearly suggests that there is a direct relationship between the SR, D-serine, and IMT. In this article, we will discuss whether the activity of SR can determine the future consequences resulting from vascular pathologies such as MI and stroke.
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