1,720,982 research outputs found
Muscle Co-Contraction Detection in the Time–Frequency Domain
Full text linkBackground: Muscle co-contraction plays a significant role in motion control. Available detection methods typically only provide information in the time domain. The current investigation proposed a novel approach for muscle co-contraction detection in the time–frequency domain, based on continuous wavelet transform (CWT). Methods: In the current study, the CWT-based crossenergy localization of two surface electromyographic (sEMG) signals in the time–frequency domain, i.e., the CWT coscalogram, was adopted for the first time to characterize muscular co-contraction activity. A CWT-based denoising procedure was applied for removing noise from the sEMG signals. Algorithm performances were checked on synthetic and real sEMG signals, stratified for signalto-noise ratio (SNR), and then validated against an approach based on the acknowledged doublethreshold statistical algorithm (DT). Results: The CWT approach provided an accurate prediction of co-contraction timing in simulated and real datasets, minimally affected by SNR variability. The novel contribution consisted of providing the frequency values of each muscle co-contraction detected in the time domain, allowing us to reveal a wide variability in the frequency content between subjects and within stride. Conclusions: The CWT approach represents a relevant improvement over state-of-theart approaches that provide only a numerical co-contraction index or, at best, dynamic information in the time domain. The robustness of the methodology and the physiological reliability of the experimental results support the suitability of this approach for clinical applications
ADLs Detection with a Wrist-Worn Accelerometer in Uncontrolled Conditions
No full textIn 2017, the European Commission estimated that 29% of European population will be aged 65 and over, by 2070. The capability of tracking and recognizing people’s daily activities may promote and support an active and independent lifestyle. In this regard, Human Activity Recognition allows to obtain meaningful information by monitoring daily activities using wearable devices, that are small, easy to use, and minimally invasive. In this paper, we discuss the recognition performance of six machine learning classifiers applied to accelerometer data only. Data was collected by 36 individuals, wearing a single wrist-worn sensor to monitor six daily activities pertaining to Hygiene and House Cleaning scenarios. Following a pre-processing phase, both temporal and frequency features were computed to classify and recognize the collected real-world data. The study presents some statistical results obtained from each classifier in order to compare their performance. The findings of experiments are promising for the adoption of the Random Forest classifier in Human Activity Recognition with acceleration data from a single wrist-worn device
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
A time-frequency approach for the assessment of dynamic muscle co-contractions
No full textCo-contraction is defined as the activity of agonist and antagonist muscles around a joint, enhancing stability and balance. The quantitative assessment of muscle co-contractions would be meaningful for deepening the comprehension of this physiological mechanism. Thus, the purpose of this work is to quantify muscle co-contraction using energy localization in time-frequency domain of sEMG signal during straight walking. To this purpose, sEMG from tibialis anterior (TA) and gastrocnemius lateralis (GL) and basographic signals were acquired in five healthy subjects during walking. Basographic signals were analyzed to quantify foot-floor contact. sEMG signals were processed using Wavelet Transform (WT) to identify muscular co-contractions, according to the following steps. Daubechies (order 4 with 6 levels of decomposition) was chosen as mother wavelet. A denoising algorithm based on Daubechies mother wavelet was applied for removing noise from raw signals. Denoised signals were decomposed into WT coefficients with different frequency content, and then recombined to achieve the co-scalogram function, a localized statistical assessment of cross-energy density between signals. The localization of regions with maximum cross-energy density provided the assessment of co-contractions in time-frequency domain. This methodology applied to TA and GL signals was able to detect GL/TA co-contractions during mid-stance (30–34% of GC) phase, matching with literature. Moreover, WT approach was able to provide also the frequency band of information content for muscle co-contractions: 65–164 Hz. In conclusion, this study proposed WT cross-energy density as a reliable estimation of muscle co-contraction in time-frequency domain
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