1,720,962 research outputs found
A combination of template matching and Bayesian estimation to detect and classify activities of daily living
No full textClassifying among motor activities executed at different speeds: SVM vs MAP applied to accelerometric features
No full textDistinguishing among different lower limb physical activities through a Bayes' classifier applied on features extracted from single-axis accelerometer data
No full textMinimizing the Set Up for ADL Monitoring through DTW Hierarchical Classification on Accelerometer Data
No full textSystems for remote monitoring of motor activities in the elderly are becoming very popular in developed countries. In this context, recognition and classification of Activities of Daily Living (ADL) is a very important step that can open intriguing scenarios, especially if real-time techniques become available. The present work proposes a hierarchical classifier based on the Dynamic Time Warping (DTW) technique, applied on data recorded from a tri-axial accelerometer placed on the shin, to classify among different motor activities. The classifier was applied to the recognition of walking, climbing and descending stairs of five different subjects. After the calibration phase needed to extract the templates, the technique makes it possible to recognize activities by determining the distance between the signal input and a set of the previously defined templates. Signals coming from the three different channels are used in a hierarchical way, with three layers. The hierarchy has been set based on sorting channels by signal to noise ratio in descending order. The results show a classification with overall percentage of error less than 5%
A hierarchical classifier to monitor ADL through dynamic programming on dual-axis accelerometer data
No full textThe new focus on active ageing in developed countries renders more urgent the availability of
remote monitoring for motor activities in the elderly. Recognition and classification of Activities of Daily
Living in this context open intriguing scenarios especially if real-time techniques are available. The present
work proposes a hierarchical classifier for activity recognition that uses only a dual axis accelerometer placed
on the shin, and the Dynamic Time Warping (DTW) algorithm. The classifier was applied to the recognition
of walking, climbing and descending stairs of five different subjects. The first part is a calibration phase, to
obtain the template signals, and the second part recognizes activities by determining the distance between the
signal input and a set of previously defined templates. The signals of the two channels will be used in a
hierarchical way. The results show a classification with overall percentage of error less than 5%
Classification of Motor Activities through Derivative Dynamic Time Warping applied on Accelerometer Data
No full textIn the context of tele-monitoring, great interest is presently devoted to physical activity, mainly of elderly or people with disabilities. In this context, many researchers studied the recognition of activities of daily living by using accelerometers. The present work proposes a novel algorithm for activity recognition that considers the variability in movement speed, by using dynamic programming. This objective is realized by means of a matching and recognition technique that determines the distance between the signal input and a set of previously defined templates. Two different approaches are here presented, one based on Dynamic Time Warping (DTW) and the other based on the Derivative Dynamic Time Warping (DDTW). The algorithm was applied to the recognition of gait, climbing and descending stairs, using a biaxial accelerometer placed on the shin. The results on DDTW, obtained by using only one sensor channel on the shin showed an average recognition score of 95%, higher than the values obtained with DTW (around 85%). Both DTW and DDTW consistently show higher classification rate than classical Linear Time Warping (LTW).In the context of tele-monitoring, great interest is presently devoted to physical activity, mainly of elderly or people with disabilities. In this context, many researchers studied the recognition of activities of daily living by using accelerometers. The present work proposes a novel algorithm for activity recognition that considers the variability in movement speed, by using dynamic programming. This objective is realized by means of a matching and recognition technique that determines the distance between the signal input and a set of previously defined templates. Two different approaches are here presented, one based on Dynamic Time Warping (DTW) and the other based on the Derivative Dynamic Time Warping (DDTW). The algorithm was applied to the recognition of gait, climbing and descending stairs, using a biaxial accelerometer placed on the shin. The results on DDTW, obtained by using only one sensor channel on the shin showed an average recognition score of 95%, higher than the values obtained with DTW (around 85%). Both DTW and DDTW consistently show higher classification rate than classical Linear Time Warping (LTW)
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
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