Piezoelectric mems contact detection system

A method comprising:

• storing, in a memory of a device, data from a first analog signal generated by a first piezoelectric microelectromechanical systems (MEMS) transducer having a first output, wherein the first piezoelectric MEMS transducer is mechanically coupled to a first surface of an object, and wherein the first piezoelectric MEMS transducer is configured to generate the first analog signal at the first output when the first analog signal is transduced by the first piezoelectric MEMS transducer from vibrations propagating through the object;
• storing, in the memory of the device, data from a second piezoelectric MEMS transducer having a second output, wherein the second piezoelectric MEMS transducer is configured to generate the second analog signal at the second output when the second analog signal is transduced by the second piezoelectric MEMS transducer from acoustic vibrations incident on the first surface of the object;
• and
• processing, using classification circuitry coupled to the output of first piezoelectric MEMS transducer and the output second piezoelectric MEMS transducer, the data from the first analog signal and the data from the second analog signal to categorize combinations of the first analog signal and the second analog signal received during one or more time frames.

A system comprising:

• means for generating a first analog signal transduced from vibrations propagating through an object having a first surface;
• means for generating a second analog signal transduced from acoustic signals incident on the first surface of the object;
• and
• means for processing data from the first analog signal and data from the second analog signal to classify combinations of the first analog signal and the second analog signal received during one or more time frames.

A system comprising:

• a motion sensor;
• a microphone;
• a machine learning engine;
• and
• at least one package containing the motion sensor, the microphone and the machine learning engine, the at least one package having a base to secure the motion sensor and microphone to a surface, the machine learning engine configured to be trained to differentiate different types of contact on the surface.