84 research outputs found

    fNIRS complexity analysis for the assessment of motor imagery and mental arithmetic tasks

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    Conventional methods for analyzing functional near-infrared spectroscopy (fNIRS) signals primarily focus on characterizing linear dynamics of the underlying metabolic processes. Nevertheless, linear analysis may underrepresent the true physiological processes that fully characterizes the complex and nonlinear metabolic activity sustaining brain function. Although there have been recent attempts to characterize nonlinearities in fNIRS signals in various experimental protocols, to our knowledge there has yet to be a study that evaluates the utility of complex characterizations of fNIRS in comparison to standard methods, such as the mean value of hemoglobin. Thus, the aim of this study was to investigate the entropy of hemoglobin concentration time series obtained from fNIRS signals and perform a comparitive analysis with standard mean hemoglobin analysis of functional activation. Publicly available data from 29 subjects performing motor imagery and mental arithmetics tasks were exploited for the purpose of this study. The experimental results show that entropy analysis on fNIRS signals may potentially uncover meaningful activation areas that enrich and complement the set identified through a traditional linear analysis

    Multivariate Pattern Analysis of Entropy estimates in Fast- and Slow-Wave Functional Near Infrared Spectroscopy: A Preliminary Cognitive Stress study

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    Functional near infrared spectroscopy (fNIRS) is a modality that can measure shallow cortical brain signals and also contains pulsatile oscillations that originate from heartbeat dynamics. In particular, while fNIRS slow waves (0 Hz to 0.6 Hz) refer to the standard hemodynamic signal, fast-wave (0.8 Hz to 3 Hz) fNIRS signals refer to cardiac oscillations. Using a cognitive stress experiment paradigm with mental arithmetic, the aim of this study was to assess differences in cortical activity when using slow-wave or fast-wave fNIRS signals. Furthermore, we aimed to see whether fNIRS fast and slow waves provide different information to discriminate mental arithmetic tasks from baseline. We used data from 10 healthy subjects from an open dataset performing mental arithmetic tasks and assessed fNIRS signals using mean values in the time domain, as well as complexity estimates including sample, fuzzy, and distribution entropy. A searchlight representational similarity analysis with pairwise t-test group analysis was performed to compare the representational dissimilarity matrices of each searchlight center. We found significant representational differences between fNIRS fast and slow waves for all complexity estimates, at different brain regions. On the other hand, no statistical differences were observed for mean values. We conclude that entropy analysis of fNIRS data may be more sensitive than traditional methods like mean analysis at detecting the additional information provided by fast-wave signals for discriminating mental arithmetic tasks and warrants further research

    Complexity Analysis on Functional-Near Infrared Spectroscopy Time Series: A Preliminary Study on Mental Arithmetic

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    It is well known that physiological systems show complex and nonlinear behaviours. In spite of that, functional near-infrared spectroscopy (fNIRS) is usually analyzed in the time and frequency domains with the assumption that metabolic activity is generated from a linear system. To leverage the full information provided by fNIRS signals, in this study we investigate topological entropy in fNIRS series collected from 10 healthy subjects during mental mental arithmetic task. While sample entropy and fuzzy entropy were used to estimate time series irregularity, distribution entropy was used to estimate time series complexity. Our findings show that entropy estimates may provide complementary characterization of fNIRS dynamics with respect to reference time domain measurements. This finding paves the way to further investigate functional activation in fNIRS in different case studies using nonlinear and complexity system theory

    The design and in vivo testing of a locally stiffness-matched porous scaffold

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    An increasing volume of work supports utilising the mechanobiology of bone for bone ingrowth into a porous scaffold. However, typically during in vivo testing of implants, the mechanical properties of the bone being replaced are not quantified. Consequently there remains inconsistencies in the literature regarding ‘optimum’ pore size and porosity for bone ingrowth. It is also difficult to compare ingrowth results between studies and to translate in vivo animal testing to human subjects without understanding the mechanical environment. This study presents a clinically applicable approach to determining local bone mechanical properties and design of a scaffold with similar properties. The performance of the scaffold was investigated in vivo in an ovine model. The density, modulus and strength of trabecular bone from the medial femoral condyle from ovine bones was characterised and power-law relationships were established. A porous titanium scaffold, intended to maintain bone mechanical homeostasis, was additively manufactured and implanted into the medial femoral condyle of 6 ewes. The stiffness of the scaffold varied throughout the heterogeneous structure and matched the stiffness variation of bone at the surgical site. Bone ingrowth into the scaffold was 10.73 ± 2.97% after 6 weeks. Fine woven bone, in the interior of the scaffold, and intense formations of more developed woven bone overlaid with lamellar bone at the implant periphery were observed. The workflow presented will allow future in vivo testing to test specific bone strains on bone ingrowth in response to a scaffold and allow for better translation from in vivo testing to commercial implants

    Statistical shape modelling of the thoracic spine for the development of pedicle screw insertion guides

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    Spinal fixation and fusion are surgical procedures undertaken to restore stability in the spine and restrict painful or degenerative motion. Malpositioning of pedicle screws during these procedures can result in major neurological and vascular damage. Patient-specific surgical guides offer clear benefits, reducing malposition rates by up to 25%. However, they suffer from long lead times and the manufacturing process is dependent on third-party specialists. The development of a standard set of surgical guides may eliminate the issues with the manufacturing process. To evaluate the feasibility of this option, a statistical shape model (SSM) was created and used to analyse the morphological variations of the T4–T6 vertebrae in a population of 90 specimens from the Visible Korean Human dataset (50 females and 40 males). The first three principal components, representing 39.7% of the variance within the population, were analysed. The model showed high variability in the transverse process (~ 4 mm) and spinous process (~ 4 mm) and relatively low variation (< 1 mm) in the vertebral lamina. For a Korean population, a standardised set of surgical guides would likely need to align with the lamina where the variance in the population is lower. It is recommended that this standard set of surgical guides should accommodate pedicle screw diameters of 3.5–6 mm and transverse pedicle screw angles of 3.5°–12.4°

    Characterization of ICRISAT-bred Pearl Millet Restorer Parents

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    Pearl millet [Pennisetum glaucum (L) R. Br.], primarily grown for grain production on more than 26 m ha in the arid and semi-arid tropical (SAT) regions of Asia and Africa, is a highly nutritious cereal crop with wide agro- ecological adaptation. India, the largest producer of this crop at the global level, cultivates pearl millet on about >9 million ha contributing to more than 90% area of the crop in the Asian region. It is a highly cross pollinated crop, and single-cross hybrids generally give 20-30% more yield than open pollinated varieties (Rai et al. 2006). With the availability of commercially exploitable cytoplasmic-nuclear male sterility (CMS) systems in pearl millet, the national agricultural research system (NARS) and the private seed sector in India focused their breeding programs on hybrid development. This led to the development and adoption of a diverse range and large number of hybrids (> 80 in 2011) and now occupying > 4.5 m ha area, which is about half the total pearl millet area being cultivated in India (Rai et al. 2006). ICRISAT also aligned its breeding program to developing promising hybrid parental lines in order to support the Asian pearl millet hybrid program..

    Brugada Syndrome-Associated Genetic Loci Are Associated With J-Point Elevation and an Increased Risk of Cardiac Arrest

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    Introduction: A previous genome-wide association study found three genetic loci, rs9388451, rs10428132, and rs11708996, to increase the risk of Brugada Syndrome (BrS). Since the effect of these loci in the general population is unknown, we aimed to investigate the effect on electrocardiogram (ECG) parameters and outcomes in the general population.Materials and Methods: A cohort of 6,161 individuals (median age 45 [interquartile range (IQR) 40–50] years, 49% males), with available digital ECGs, was genotyped and subsequently followed for a median period of 13 [IQR 12.6–13.4] years. Data on outcomes were collected from Danish administrative healthcare registries. Furthermore, ~400,000 persons from UK Biobank were investigated for associations between the three loci and cardiac arrest/ventricular fibrillation (VF).Results: Homozygote carriers of the C allele in rs6800541 intronic to SCN10A had a significantly larger J-point elevation (JPE) compared with wildtype carriers (11 vs. 6 μV, P &lt; 0.001). There was an additive effect of carrying multiple BrS-associated risk alleles with an increased JPE in lead V1. None of the BrS-associated genetic loci predisposed to syncope, atrial fibrillation, or total mortality in the general Danish population. The rs9388451 genetic locus adjacent to the HEY2 gene was associated with cardiac arrest/VF in an analysis using the UK Biobank study (odds ratio = 1.13 (95% confidence interval: 1.08–1.18), P = 0.006).Conclusions: BrS-associated risk alleles increase the JPE in lead V1 in an additive manner, but was not associated with increased mortality or syncope in the general population of Denmark. However, the HEY2 risk allele increased the risk of cardiac arrest/VF in the larger population study of UK Biobank indicating an important role of this common genetic locus
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