Article

Evaluating neuropsychological impairment in chronic fatigue syndrome.

Department of Medical Psychology, University Hospital Nijmegen, The Netherlands.
Journal of Clinical and Experimental Neuropsychology (Impact Factor: 2.16). 05/1998; 20(2):144-56. DOI: 10.1076/jcen.20.2.144.1160
Source: PubMed

ABSTRACT This study was designed to provide an estimate of the prevalence of neuropsychological impairment in chronic fatigue syndrome (CFS), to evaluate the concordance between impairment found on standardized tests and self-reported neuropsychological problems, and to study the relationship between neuropsychological functioning and fatigue severity and psychological processes. We adopted an individual approach to determine neuropsychological impairment as contrasted with the group-comparisons approach used in previous studies. Also, correction for premorbid functioning and confounders was done on an individual basis. The results show that a minority of participants were impaired in neuropsychological functioning. There was no relationship between neuropsychological impairment on standardized tests and self-reported memory and concentration problems. Neuropsychological functioning was not related to fatigue or depression. Slowed speed of information processing and motor speed were related to low levels of physical activity.

0 Bookmarks
 · 
80 Views
  • Journal of psychosomatic research 04/2014; 76(4):340. · 2.91 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Limited scientific evidence suggests that physical activity is directly related to cognitive performance in patients with chronic fatigue syndrome (CFS). To date, no other study has examined the direct relationship between cognitive performance and physical fitness in these patients. This study examined whether cognitive performance and physical fitness are associated in female patients with CFS and investigated the association between cognitive performance and physical activity level (PAL) in the same study sample. We hypothesized that patients who performed better on cognitive tasks would show increased PALs and better performance on physical tests. The study included 31 women with CFS and 13 healthy inactive women. Participants first completed three cognitive tests. Afterward, they undertook a test to determine their maximal handgrip strength, performed a bicycle ergometer test, and were provided with an activity monitor. In patients with CFS, lower peak oxygen uptake and peak heart rate were associated with slower psychomotor speed (p < 0.05). Maximal handgrip strength was correlated with working memory performance (p < 0.05). Both choice and simple reaction time were lower in patients with CFS relative to healthy controls (p < 0.05 and p < 0.001, respectively). In conclusion, physical fitness, but not PAL, is associated with cognitive performance in female patients with CFS.
    The Journal of Rehabilitation Research and Development 09/2013; 50(6):795-810. · 1.78 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Owing to providing a novel insight for the signal and image processing, compressed sensing (CS) is considered as a promising method for such fields. Successful applications of CS depend mainly on the accuracy and speed of the reconstruction algorithms. Essentially, CS reconstruction process belongs to a discrete inverse problem with finite unknown variables, methods that ensure the numerical stability while increasing the quality of a solution should be employed. In this paper, a new objective functional, which has been developed using a combinational estimation and a generalized stabilizing functional, is proposed. An efficient iterative scheme that integrates the beneficial advantages of the homotopy algorithm and the quantum particle swarm optimization (QPSO) algorithm is designed for searching a possible global optimal solution. Numerical simulations are implemented to test the validity of the proposed algorithm. Excellent numerical performances and encouraging results are observed. For the cases considered in this paper, the accuracy of the reconstructed objects is significantly improved, which indicates that the proposed algorithm is very successful in solving the CS inverse problem. As a result, a promising algorithm is introduced for CS reconstruction.
    Proceedings of the 2010 International Conference on Intelligent System Design and Engineering Application - Volume 01; 10/2010