Abstract: Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to a Sensor for monitoring acetone emitted from the surface of the skin. The Sensor includes a gas impermeable enclosure and a carbonate removal cell enclosed within the gas impermeable enclosure. A gas permeable membrane houses the gas impermeable enclosure. A fuel cell anode is situated adjacent to the gas permeable membrane. At least a portion of a reference electrode is enclosed by a first portion of the fuel cell anode. A bottom surface of the carbonate removal cell is composed of a top surface of a second portion of the fuel cell anode. A top surface of the reference electrode and a top surface of the first portion of the fuel cell anode are in contact with a bottom surface of the gas permeable membrane.

Abstract: Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to a Concentration Prediction Platform. According to various embodiments, the Concentration Prediction Platform receives an electrochemical signal and generates data based on deconvolving a respective contribution of an analyte(s) influencing the electrochemical signal. The Concentration Prediction Platform sends the data into one or more machine learning networks. The Concentration Prediction Platform receives, from the one or more machine learning networks, a predicted concentration of an analyte(s) influencing the electrochemical signal.

Abstract: Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to a Concentration Prediction Platform. According to various embodiments, the Concentration Prediction Platform receives an electrochemical signal and generates data based on deconvolving a respective contribution of an analyte(s) influencing the electrochemical signal. The Concentration Prediction Platform sends the data into one or more machine learning networks. The Concentration Prediction Platform receives, from the one or more machine learning networks, a predicted concentration of an analyte(s) influencing the electrochemical signal.