Micro-doppler radar systems and methods for evaluating human motion

A method for evaluating human movement using micro-Doppler radar (MDR), the method implemented by an MDR system and comprising:

• capturing via a reception antenna a received radar signal reflected from a human subject in motion following output via a transmission antenna of a first transmitted radar signal toward the human subject in motion;
• filtering the first transmitted radar signal from the received radar signal to yield an analog MDR signal that reflects modulation caused by movement of the human subject;
• applying a trained machine learning model to digital micro-Doppler signal (MDS) data converted from the analog MDR signal to generate a result indicative of a likelihood that the human subject is at risk for an injury or other pathological condition;
• and
• outputting an indication of the result for display on a display device to facilitate prediction of the injury or other pathological condition.

A micro-Doppler radar (MDR) system, comprising a reception antenna, a transmission antenna, memory having instructions stored thereon for evaluating human movement using MDR, and one or more processors coupled to the memory and configured to execute the stored instructions to:

• capture via the reception antenna a received radar signal reflected from a human subject in motion following output via the transmission antenna of a first transmitted radar signal toward the human subject in motion;
• filter the first transmitted radar signal from the received radar signal to yield an analog MDR signal that reflects modulation caused by movement of the human subject;
• apply a trained machine learning model to digital micro-Doppler signal (MDS) data converted from the analog MDR signal to generate a result indicative of a likelihood that the human subject is at risk for an injury or other pathological condition;
• and
• output an indication of the result for display on a display device to facilitate prediction of the injury or other pathological condition.

A non-transitory computer readable medium having stored thereon instructions for evaluating human movement using micro-Doppler radar (MDR) comprising executable code that, when executed by one or more processors, causes the one or more processors to:

• train a machine learning model based on a first micro-Doppler signal (MDS) data set captured from a first population of human subjects known to be at risk for an injury or other pathological condition and a second MDS data set captured from a second population of human subjects healthy with respect to the injury or other pathological condition;
• capture via a reception antenna a received radar signal reflected from a human subject in motion following output via a transmission antenna of a first transmitted radar signal toward the human subject in motion;
• filter the first transmitted radar signal from the received radar signal to yield an analog MDR signal that reflects modulation caused by movement of the human subject;
• apply a trained machine learning model to digital MDS data converted from the analog MDR signal to generate a result indicative of a likelihood that the human subject is at risk for the injury or other pathological condition;
• and
• output an indication of the result for display on a display device to facilitate prediction of the injury or other pathological condition.