Methods and systems for detecting oxygen saturation from a camera

A system for predicting a characteristic of a neonate comprising:

• a ballistographic monitoring device configured to measure movement of the neonate and create a ballistographic signal from the measured movement;
• a vital measurement device configured to measure a vitals measurement of the neonate and create a vital signal from the vitals measurement;
• a camera configured to capture an image of the neonate and create a camera signal from the image;
• a memory including instructions;
• and
• at least one processor to execute the instructions to:
• obtain the ballistographic signal from the ballistographic monitoring device;
• obtain the vital signal from the vital measurement device;
• obtain the camera signal from the camera;
• process the ballistographic signal, the vital signal, and the camera signal using a learning model trained to generate a prediction for a characteristic of the neonate;
• and
• display the prediction from the learning model on a user interface.

A system for predicting a characteristic of a neonate comprising:

• a ballistographic monitoring device configured to measure movement of the neonate and create a ballistographic signal from the measured movement;
• a vital measurement device configured to measure a vitals measurement of the neonate and create a vital signal from the vitals measurement;
• a camera configured to capture an image of the neonate and create a camera signal from the image;
• a memory including instructions;
• and
• at least one processor to execute the instructions to:
• obtain the ballistographic signal from the ballistographic monitoring device;
• process the ballistographic signal using a first learning model trained to generate a first score;
• obtain the vital signal from the vital measurement device;
• process the vital signal using a second learning model trained to generate a second score;
• obtain the camera signal from the camera;
• process the camera signal using a third learning model trained to generate a third score;
• process the first score, the second score, and the third score using a learning model trained to generate a prediction for a characteristic of the neonate;
• and
• display the prediction from the learning model on a user interface.