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total: 48
Search results for: AKCELEROMETR
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Modelling an accelerometer for robot position estimation
PublicationThe article describes a new model of a MEMS accelerometer for usage in inertial measurement units (IMU). Such units allow to measure orientation and location of the sensor/system and therefore can be applied for systems positioning. The main purpose of the paper is to model pertinent accelerometer functions substantial in determination of the location of the sensor by means of double integration of acceleration. The model takes...
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Evaluation of position estimation based on accelerometer data
PublicationThe paper concerns the problem of integrating data from accelerometers. A suitable model of a MEMS accelerometer is presented which is a part of inertial measurement units (IMU). Such units allow to measure orientation as well as to localize systems. They also appear to be applicable for systems positioning. The main purpose of the paper is to discuss conditions that must be satisfied to calculate the location of the sensor by...
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STEVAL-MKI063V1, Przykład oprogramowania akcelerometrui magnetometru LSM303DLH
PublicationW artykule opisano moduł STEVAL-MKI1063V1 oparty na układzie LSM303DLHzawierającym akcelerometr i magnetometr oraz przedstawiono sposób komunikacji z nim z poziomu komputera PC na przykładzie aplikacji napisanej w języku C++/CLI (.NET).
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Evaluating the mobile robot positions using accelerometer data
PublicationThis paper analyzes the problem of determining the position of a robot using an accelerometer, which is an essential part of inertial measurement units (IMU). The information gained from such a gauge, however, requires double integration of sensor data. To assure an expected effect, a mathematical model of a low-cost accelerometer of the MEMS type is derived. Moreover, in order to improve the performance of positioning based on...
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Evaluating the position of a mobile robot using accelerometer data
PublicationThis paper analyses the problem of determining the position of a robot using an accelerometer, which is an essential part of inertial measurement units (IMU). The information gained from such a gauge, however, requires double integration of sensor data. To assure an expected effect, a mathematical model of a low-cost accelerometer of the MEMS type is derived. Moreover, in order to improve the performance of positioning based on...
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Accelerometer signal pre-processing influence on human activity recognition
PublicationA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy.
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Estimation of respiration rate using an accelerometer and thermal camera in eGlasses
PublicationRespiration rate is a very important vital sign. Different methods of respiration rate measurement or estimation have been developed. However, especially interesting are those that enable remote and unobtrusive monitoring. In this study, we investigated the use of smart glasses for the estimation of respiration rate especially useful for indoors applications. Two methods were analyzed. The first one is based on measurements of...
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Accelerometer-based Human Activity Recognition and the Impact of the Sample Size
PublicationThe presented study focused on the recognition of eight user activities (e.g. walking, lying, climbing stairs) basing on the measurements from an accelerometer embedded in a mobile device. It is assumed that the device is carried in a specific location of the user’s clothing. Three types of classifiers were tested on different sizes of the samples. The influence of the time window (the duration of a single trial) on selected activities...
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Influence of accelerometer signal pre-processing and classification method on human activity recognition
PublicationA study of data pre-processing influence on accelerometer-based human activity recognition algorithms is presented. The frequency band used to filter-out the accelerometer signals and the number of accelerometers involved were considered in terms of their influence on the recognition accuracy. In the test four methods of classification were used: support vector machine, decision trees, neural network, k-nearest neighbor.
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Visualization and quantification of lab vibratory compacting process for aggregate base materials using accelerometer
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