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See the sample app 'fsensorapp' for more examples.
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## Orientation
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FSensor conforms with the Android API such that the y-axis points north, the x-axis points east, and the z-axis points up. The device is assumed to be in the portrait orientation
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laying flat on a level surface.
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* The orientation vector returned by FSensor will be orientation[]{azimuth, pitch, roll}.
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* The linear acceleration returned by FSensor will be acceleration[]{x, y, z}.
Linear acceleration is defined as linearAcceleration = (acceleration - gravity). An acceleration sensor alone is not capable of determining the difference between gravity/tilt.
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FSensor provides three different estimations of linear acceleration implementing Low-Pass, Complementary and Kalman based sensor fusions.
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## Orientation Sensor Fusions
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FSensor offers two different estimations of rotation implementing both Complementary and Kalman based fusions. The fusions utilize the acceleration, magnetic, and gyroscope sensors
@@ -134,8 +150,5 @@ FSensor uses a median filter designed to smooth the data points based on a time
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occur over a period defined by the time constant... the number of samples that are considered is known as the filter window. The approach allows the filter window to be defined
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over a period of time, instead of a fixed number of samples.
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## Linear Acceleration
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Linear acceleration is defined as linearAcceleration = (acceleration - gravity). An acceleration sensor alone is not capable of determining the difference between gravity/tilt.
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FSensor provides three different estimations of linear acceleration implementing Low-Pass, Complementary and Kalman based sensor fusions.
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