The Feasibility of a Cross-Coupled Adaptive Canceller       for Real-Time Signal Extraction
{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}
{'SignBlockName': 'Ritchie B. Coryell', 'PO_EMAI': None, 'PO_PHON': None}
This research focuses its attention on the study of a cross-coupled             adaptive noise cancellation algorithm that is suitable for                      applications in which the primary and noise inputs may be closely               spaced, thus a pure noise reference is not available for effective              noise cancellation from the primary signal.  The structure of this new          algorithm is based on two Least-Mean Squared (LMS) delay                        line cancellers with cross-coupled feedback.  The PI's overall                  objective is to determine the feasibility of this novel cross-coupled           adaptive algorithm to improve the signal-to-noise ratio of data                 composed of recurring pulses in noise for systems in which a pure               noise reference input can not be found, i.e., in the problem of                 extracting the fetal electrocardiographic (FECG) signals embedded in            muscle noise recorded from the pregnant maternal abdomen.  He hopes to          show that this LMS cross-coupled canceller algorithm, which does                not require a pure noise reference input, effectively cancels maternal          muscle noise from recorded fetal ECG data without distortion of the             FECG signal, thus, providing an enhanced fetal signal for subsequent            analysis or detection.  The evaluation of this cross-coupled                    cancellation algorithm for the real-time cancellation of muscle noise           from the FECG signal is the expected result of this research.                   Successful application of this algorithm to this fetal                          electrocardiography problem would suggest other applications to                 problems in electrical and biomedical signal processing, since many             problems of noise cancellation are difficult to solve due to the lack           of a pure noise signal.
{'FirstName': 'Thomas', 'LastName': 'Frank', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Thomas H Frank', 'EmailAddress': None, 'PI_PHON': '3012616610', 'NSF_ID': '000290435', 'StartDate': '01/01/1989', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Perinatronics Medical Systems Inc', 'CityName': 'Crofton', 'ZipCode': '211141314', 'PhoneNumber': '3012616610', 'StreetAddress': '1651 Crofton Blvd Suite 3', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MD05', 'ORG_UEI_NUM': None, 'ORG_LGL_BUS_NAME': None, 'ORG_PRNT_UEI_NUM': None}
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{'Code': '5371', 'Text': 'SBIR Phase I'}
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