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Asked: 2026-05-19T11:32:42+00:00

I saw many examples about filtering Accelermeter’s values, to cancel out the gravity (High-pass

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I saw many examples about filtering Accelermeter’s values, to cancel out the gravity (High-pass filter).

But most of them were 1st order one, which is said to be simple, but laggy and not the best one (though I know nothing about the filters or DSP).

Somebody in here said that there exists the better solution used in DSP to sense the motion. Regretfully I can’t even imagine what it would be, as I am completely outsider to the field.

I hope somebody could tell at least the type of filters that can be used when dealing with the sensor. Of course, even brief introduction to the specific algorithm will be very pleased 🙂

Thanks in advance.

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  1. Editorial Team

    You want to utilize Android’s SensorListener() Class. For example, “The Schwartz Unsheathed” is open source Android project hosted on Google Code that looks like it should be quite useful (written by Clark Scheff).

    You can check out its source via SVN http://code.google.com/p/the-schwartz-unsheathed/source/checkout or just browse it on the web. The source is broken up into an Activity (TheSchwartz.java) and a View (GraphView.java). GraphView.java contains SensorListener() ad onSensorChanged() classes which is where the accelerometer processing occurs. Lines 284 and 285:

    magnitude = (float)Math.sqrt(values[0]*values[0]+values[1]*values[1]+values[2]*values[2]);
magnitude = Math.abs(magnitude - SensorManager.GRAVITY_EARTH);

    The value of magnitude is evaluated for no movement, a “hit” or a “swing” of the Android phone. I realize this does not filter the data in a signal processing sense, but it does show a way to classify sensor data. Hope it helps.

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