A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue

Muscle fatigue is an established area of research and various types of muscle fatigue have been investigated in order to fully understand the condition. This paper gives an overview of the various non-invasive techniques available for use in automated fatigue detection, such as mechanomyography, electromyography, near-infrared spectroscopy and ultrasound for both isometric and non-isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who wish to select the most appropriate methodology for research on muscle fatigue detection or prediction, or for the development of devices that can be used in, e.g., sports scenarios to improve performance or prevent injury. To date, research on localised muscle fatigue focuses mainly on the clinical side. There is very little research carried out on the implementation of detecting/predicting fatigue using an autonomous system, although recent research on automating the process of localised muscle fatigue detection/prediction shows promising results

Documenting and predicting topic changes in Computers in Biology and Medicine: A bibliometric keyword analysis from 1990 to 2017

The Computers in Biology and Medicine (CBM) journal promotes the use of com-puting machinery in the fields of bioscience and medicine. Since the first volume in 1970, the importance of computers in these fields has grown dramatically, this is evident in the diversification of topics and an increase in the publication rate. In this study, we quantify both change and diversification of topics covered in CBM. This is done by analysing the author supplied keywords, since they were electronically captured in 1990. The analysis starts by selecting 40 keywords, related to Medical (M) (7), Data (D)(10), Feature (F) (17) and Artificial Intelligence (AI) (6) methods. Automated keyword clustering shows the statistical connection between the selected keywords. We found that the three most popular topics in CBM are: Support Vector Machine (SVM), Elec-troencephalography (EEG) and IMAGE PROCESSING. In a separate analysis step, we bagged the selected keywords into sequential one year time slices and calculated the normalized appearance. The results were visualised with graphs that indicate the CBM topic changes. These graphs show that there was a transition from Artificial Neural Network (ANN) to SVM. In 2006 SVM replaced ANN as the most important AI algo-rithm. Our investigation helps the editorial board to manage and embrace topic change. Furthermore, our analysis is interesting for the general reader, as the results can help them to adjust their research directions

The Electroencephalogram as a Biomarker Based on Signal Processing Using Nonlinear Techniques to Detect Dementia

Dementia being a syndrome caused by a brain disease of a chronic or progressive nature, in which the irreversible loss of intellectual abilities, learning, expressions arises; including memory, thinking, orientation, understanding and adequate communication, of organizing daily life and of leading a family, work and autonomous social life; leads to a state of total dependence; therefore, its early detection and classification is of vital importance in order to serve as clinical support for physicians in the personalization of treatment programs. The use of the electroencephalogram as a tool for obtaining information on the detection of changes in brain activities. This article reviews the types of cognitive spectrum dementia, biomarkers for the detection of dementia, analysis of mental states based on electromagnetic oscillations, signal processing given by the electroencephalogram, review of processing techniques, results obtained where it is proposed the mathematical model about neural networks, discussion and finally the conclusions

Combining anti-cancer drugs with artificial sweeteners:Synthesis and anti-cancer activity of saccharinate (sac) and thiosaccharinate (tsac) complexes cis-[Pt(sac)2(NH3)2] and cis-[Pt(tsac)2(NH3)2]

WOS: 000343790700007PubMed ID: 25216367The new platinum(II) complexes cis-[Pt(sac)(2)(NH3)(2)] (sac = saccharinate) and cis-[Pt(tsac)(2)(NH3)(2)] (tsac = thiosaccharinate) have been prepared, the X-ray crystal structure of cis-[Pt(sac)(2)(NH3)(2)]center dot H2O reveals that both saccharinate anions are N-bound in a cis-arrangement being inequivalent in both the solid-state and in solution at room temperature. Preliminary anti-cancer activity has been assessed against A549 human alveolar type-II like cell lines with the thiosaccharinate complex showing good activity. (C) 2014 Elsevier Inc. All rights reserved.Tikrit University; Commonwealth Scholarship CommissionWe thank the Commonwealth Scholarship Commission for the award of a Commonwealth Scholarship to SG and Tikrit University for support

Combining anti-cancer drugs with artificial sweeteners: Synthesis and anti-cancer activity of saccharinate (sac) and thiosaccharinate (tsac) complexes cis-[Pt(sac)2(NH3)2] and cis-[Pt(tsac)2(NH3)2]

PubMed ID: 25216367The new platinum(II) complexes cis-[Pt(sac)2(NH3)2] (sac = saccharinate) and cis-[Pt(tsac)2(NH3)2] (tsac = thiosaccharinate) have been prepared, the X-ray crystal structure of cis-[Pt(sac)2(NH3)2].H2O reveals that both saccharinate anions are N-bound in a cis-arrangement being inequivalent in both the solid-state and in solution at room temperature. Preliminary anti-cancer activity has been assessed against A549 human alveolar type-II like cell lines with the thiosaccharinate complex showing good activity. © 2014 Elsevier B.V. All rights reserved