Functional gastrointestinal motility diseases are common and make up about 40% of all gastroenterology patients. Typical esophageal motor disorders include dysphasia, gastroesophageal reflux disease (GERD), non-cardiac chest pain, etc., however the effective diagnosis and treatment of these diseases are still a major challenge for clinical gastroenterology. At present the commercially available diagnosis systems are primitive and require users to have extensive operational experiences and profound specialized knowledges to interpret the data, which have greatly impeded the widespread use of such systems. The long-term goal of this project is to develop an interactive and automated esophageal motility assessment system. The system is designed to be interactive during the procedure and to provide an automated diagnosis of various motility disorders. These novel features will popularize the esophageal motility test and make it possible to be used by healthcare providers with little experience in esophageal motility. The phase I of the project is to prove the feasibility of such an assessment system with the following specific aims:
Aim 1 : Automated localization of the lower esophageal sphincter and interactive data acquisition;
Aim 2 : The removal of respiratory artifacts in the LES pressure recording;
Aim 3 : Data analysis and knowledge- based automated diagnosis;
Aim 4 : Development of the user friendly software platform. Software will be developed to test the feasibility of implementing these innovative features of the proposed system and will be tested and optimized using existing clinical data. A comprehensive team has been established with expertise in software programming, biomedical signal processing and clinical testing of esophageal motility. Relevance: Esophageal motility disorders are seen in about 40% of clinical gastroenterology patients. While commercial systems are currently available to identify these disorders, their widespread uses are hindered by the requirement of extensive knowledges on esophgeal motility. The automated diagnostic system to be developed in this project will solve this problem and popularize this important diagnostic method. ? ?
