Processing the signals generated by the sensor at the expense of sensitivity / selectivity
I suggest you read the AppNotes from Analog Devices Incorporated. As a kid, I learned much useful analog/signal_processing ideas and maths and building ideas from their freely available publications.
The Analog Dialogue was one which I received monthly. So google that, and start reading, and perhaps BUILDING real circuits.
Use an old loudspeaker, from anold transistor radio, as your microphone.
You might reverse_wire the tiny transformer, to stepup the voltage to be a useful level.
You can touch the wires to your earbuds, and hear your fingernail scratching across the loudspeaker's paper cone.
Get starting learning.
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To be concrete about discerning important output signals from sensors ----- theories exist on Matched_Filtering, to optimally extract signals from noise or to optimally discriminate between TWO choices of possible signals.
Just consider the integral, over a complete period, of [ sin(x) * cosine(x)]
The integral is ZERO, when integrated over N * period_duration.
Such signals (sin, cosing) are deemed orthogonal.
Many other &quot;signals&quot; have been defined, to achieve orthogonality.
Some of these &quot;signals&quot; look like noise (randomness) yet to the crafted receiver of such signals, able to implement correlators, a strong and robust datalink exists.
Peter Mallory did much work in this area.