Doppler radar system with machine learning applications for fall prediction and detection

A method for fall prediction and detection comprising the steps of:

• transmitting an electromagnetic wave;
• receiving a reflected electromagnetic wave;
• converting the reflected electromagnetic wave into a digital signal;
• and
• processing the digital signal into a spectrogram;
• processing the spectrogram through one or more machine learning algorithms for predicting and detecting falls;
• wherein the system for fall prediction and detection uses one or more dual-polarized radio frequency modules whereby a pair of orthogonal electromagnetic waves are transmitted and received into a combined spectrogram processed by one or more machine learning algorithms for predicting and detecting falls.

A system for fall prediction and detection comprising:

• a smart phone comprising a memory, a processor, and a non-volatile data storage device;
• and
• a radio-frequency module comprising electronic components that cause the radio-frequency module to:
• transmit an electromagnetic wave;
• receive a reflected electromagnetic wave;
• convert the reflected electromagnetic wave into a digital signal;
• and
• send the digital signal to the smart phone;
• the smart phone further comprising a plurality of programming instructions stored in the memory of, and operating on the processor, wherein the plurality of programming instructions, when operating on the processor, cause the smart phone to:
• receive the digital signal;
• process the digital signal into a spectrogram;
• and
• process the spectrogram through one or more machine learning algorithms for predicting and detecting falls;
• wherein the system for fall prediction and detection uses one or more dual-polarized radio frequency modules whereby a pair of orthogonal electromagnetic waves are transmitted and received into a combined spectrogram processed by one or more machine learning algorithms for predicting and detecting falls.