Abstract: Measurements of esophageal pressure and geometry are classified using a trained machine learning algorithm, such as a neural network or other classifier algorithm. Contractile response patterns can be identified in the esophageal pressure and geometry data, from which classified feature data can be generated. The classified feature data classify the esophageal pressure and geometry data as being indicative of an upper gastrointestinal disorder in the subject.