64,068 research outputs found
Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury
Background: Recent studies show that spatial distribution of High Density surface EMG maps (HD-EMG) improves the identification of tasks and their corresponding contraction levels. However, in patients with incomplete spinal cord injury (iSCI), some nerves that control muscles are damaged, leaving some muscle parts without an innervation. Therefore, HD-EMG maps in patients with iSCI are affected by the injury and they can be different for every patient. The objective of this study is to investigate the spatial distribution of intensity in HD-EMG recordings to distinguish co-activation patterns for different tasks and effort levels in patients with iSCI. These patterns are evaluated to be used for extraction of motion intention.; Method: HD-EMG was recorded in patients during four isometric tasks of the forearm at three different effort levels. A linear discriminant classifier based on intensity and spatial features of HD-EMG maps of five upper-limb muscles was used to identify the attempted tasks. Task and force identification were evaluated for each patient individually, and the reliability of the identification was tested with respect to muscle fatigue and time interval between training and identification. Results: Three feature sets were analyzed in the identification: 1) intensity of the HD-EMG map, 2) intensity and center of gravity of HD-EMG maps and 3) intensity of a single differential EMG channel (gold standard).; Results show that the combination of intensity and spatial features in classification identifies tasks and effort levels properly (Acc = 98.8 %; S = 92.5 %; P = 93.2 %; SP = 99.4 %) and outperforms significantly the other two feature sets (p < 0.05).; Conclusion: In spite of the limited motor functionality, a specific co-activation pattern for each patient exists for both intensity, and spatial distribution of myoelectric activity. The spatial distribution is less sensitive than intensity to myoelectric changes that occur due to fatigue, and other time-dependent influences.Peer ReviewedPostprint (published version
It's the Human that Matters: Accurate User Orientation Estimation for Mobile Computing Applications
Ubiquity of Internet-connected and sensor-equipped portable devices sparked a
new set of mobile computing applications that leverage the proliferating
sensing capabilities of smart-phones. For many of these applications, accurate
estimation of the user heading, as compared to the phone heading, is of
paramount importance. This is of special importance for many crowd-sensing
applications, where the phone can be carried in arbitrary positions and
orientations relative to the user body. Current state-of-the-art focus mainly
on estimating the phone orientation, require the phone to be placed in a
particular position, require user intervention, and/or do not work accurately
indoors; which limits their ubiquitous usability in different applications. In
this paper we present Humaine, a novel system to reliably and accurately
estimate the user orientation relative to the Earth coordinate system.
Humaine requires no prior-configuration nor user intervention and works
accurately indoors and outdoors for arbitrary cell phone positions and
orientations relative to the user body. The system applies statistical analysis
techniques to the inertial sensors widely available on today's cell phones to
estimate both the phone and user orientation. Implementation of the system on
different Android devices with 170 experiments performed at different indoor
and outdoor testbeds shows that Humaine significantly outperforms the
state-of-the-art in diverse scenarios, achieving a median accuracy of
averaged over a wide variety of phone positions. This is
better than the-state-of-the-art. The accuracy is bounded by the error in the
inertial sensors readings and can be enhanced with more accurate sensors and
sensor fusion.Comment: Accepted for publication in the 11th International Conference on
Mobile and Ubiquitous Systems: Computing, Networking and Services
(Mobiquitous 2014
NOMINAL EXCHANGE RATE MISALIGNMENT: IS IT PARTICULARLY IMPORTANT TO AGRICULTURAL TRADE?
This paper examines whether exchange rate misalignment negatively affects agricultural trade, compared to other industry sectors. Nominal exchange rate misalignment is obtained from the percentage deviation of real exchange rates from their long-run equilibrium based on the theory of purchasing power parity. In order to explore this issue, a bilateral trade matrix involving trade flows between 10 developed countries is constructed. Using panel data analysis, a gravity model is estimated for 4 industry sectors over the period 1974-1999. The study finds that over-valuation (under-valuation) of the nominal exchange rate negatively (positively) affects export performance of the agricultural sector in particular. In the large-scale manufacturing sectors considered in this paper, exports are not significantly affected by exchange rate misalignment.exchange rate misalignment, agricultural trade, gravity model, International Relations/Trade,
DETERMINING BILATERAL TRADE PATTERNS USING A DYNAMIC GRAVITY EQUATION
Using a dynamic gravity equation, we show that the national product differentiation model explains food and agricultural trade more properly, while the product differentiation model is more appropriate to explain large-scale manufacturing trade. In this context, our result is not consistent with the one found by Head and Ries (2001) in the short-run. The intuitive explanation for this result is that inward foreign direct investment can occur through either merger or acquisition in the short-run. Second, the pattern of bilateral trade could quickly adjust to changes in relative income between countries. Furthermore, we illustrate the positive impacts of world income growth on bilateral trade, which is in sharp contrast with the conventional analysis. This reveals yet another way to test the pattern of bilateral trade.dynamic gravity equation, national product differentiation, product differentiation, world income growth, International Relations/Trade,
THE CAUSES OF INTRA-INDUSTRY TRADE BETWEEN THE U.S. AND CANADA:TIME-SERIES APPROACH WITH A GRAVITY MODEL
This study proposes alternative reasons to explain an asymmetric intra-industry trade for agricultural products between Canada and the United States after the free trade agreement became effective. Using time-series data, a gravity model is developed which enables us to examine the significance of exchange rates and different trade patterns on bilateral trade.International Relations/Trade,
Prediction of isometric motor tasks and effort levels based on high-density EMG in patients with incomplete spinal cord injury
Objective. The development of modern assistive and rehabilitation devices requires reliable and easy-to-use methods to extract neural information for control of devices. Group-specific pattern recognition identifiers are influenced by inter-subject variability. Based on high-density EMG (HD-EMG) maps, our research group has already shown that inter-subject muscle activation patterns exist in a population of healthy subjects. The aim of this paper is to analyze muscle activation patterns associated with four tasks (flexion/extension of the elbow, and supination/pronation of the forearm) at three different effort levels in a group of patients with incomplete Spinal Cord Injury (iSCI). Approach. Muscle activation patterns were evaluated by the automatic identification of these four isometric tasks along with the identification of levels of voluntary contractions. Two types of classifiers were considered in the identification: linear discriminant analysis and support vector machine. Main results. Results show that performance of classification increases when combining features extracted from intensity and spatial information of HD-EMG maps (accuracy = 97.5%). Moreover, when compared to a population with injuries at different levels, a lower variability between activation maps was obtained within a group of patients with similar injury suggesting stronger task-specific and effort-level-specific co-activation patterns, which enable better prediction results. Significance. Despite the challenge of identifying both the four tasks and the three effort levels in patients with iSCI, promising results were obtained which support the use of HD-EMG features for providing useful information regarding motion and force intentionPeer ReviewedPostprint (author's final draft
Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 314)
This bibliography lists 139 reports, articles, and other documents introduced into the NASA scientific and technical information system in August, 1988
Effects of Impedance Reduction of a Robot for Wrist Rehabilitation on Human Motor Strategies in Healthy Subjects during Pointing Tasks
Studies on human motor control demonstrated the existence of simplifying strategies (namely
`Donders' law') adopted to deal with kinematically redundant motor tasks. In recent research we
showed that Donders' law also holds for human wrist during pointing tasks, and that it is heavily
perturbed when interacting with a highly back-drivable state-of-the-art rehabilitation robot. We
hypothesized that this depends on the excessive mechanical impedance of the Pronation/Supination
(PS) joint of the robot and in this work we analyzed the effects of its reduction. To this end we
deployed a basic force control scheme, which minimizes human-robot interaction force. This resulted
in a 70% reduction of the inertia in PS joint and in decrease of 81% and 78% of the interaction
torques during 1-DOF and 3-DOFs tasks. To assess the effects on human motor strategies, pointing
tasks were performed by three subjects with a lightweight handheld device, interacting with the
robot using its standard PD control (setting impedance to zero) and with the force-controlled robot.
We quantified Donders' law as 2-dimensional surfaces in the 3-dimensional configuration space of
rotations. Results revealed that the subject-specific features of Donders' surfaces reappeared after
the reduction of robot impedance obtained via the force control
Hierarchical Salient Object Detection for Assisted Grasping
Visual scene decomposition into semantic entities is one of the major
challenges when creating a reliable object grasping system. Recently, we
introduced a bottom-up hierarchical clustering approach which is able to
segment objects and parts in a scene. In this paper, we introduce a transform
from such a segmentation into a corresponding, hierarchical saliency function.
In comprehensive experiments we demonstrate its ability to detect salient
objects in a scene. Furthermore, this hierarchical saliency defines a most
salient corresponding region (scale) for every point in an image. Based on
this, an easy-to-use pick and place manipulation system was developed and
tested exemplarily.Comment: Accepted for ICRA 201
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