Celiac Disease Data Complicated by Atrial Fibrillation Signals During Electrophysiological Studies
Biomedical data such as videocapsule images from celiac disease patients and atrial fibrillation signals obtained during electrophysiological studies frequently contain extraneous features or noise. This complicates the identification of features important to diagnosis or assessment of response to therapy via traditional techniques such as spectral or wavelet analysis.
Biomedical Data Analyzed by Computing Ensemble Averages for Different Frequencies Result in More Accurate Readings
This technology is a method for analyzing biomedical data by computing the power of the ensemble averages for different frequencies, where the frequency is the reciprocal of the width of each averaged segment. This representation is referred to as the ensemble spectrum. Compared to traditional spectral or wavelet analysis, the ensemble spectrum can more efficiently represent features in a range of medical data such as intestinal wall characteristics obtained via videocapsule imaging and generators in complex fractionated atrial electrogram (CFAE) readings. Important spectral and morphologic components can be detected even when there is blur or jitter in the signals or images.
Applications:
• Can enable more accurate identification of features within medical data that are of importance to diagnosis or assessment of response to therapy.
• The frequency spectrum can be generated to obtain salient information concerning repetitive components.
• Can be used to transform biomedical data into a consistent format amenable to analysis or storage.
• By discarding less significant parts of transformed biomedical data, this technology can be used to compress the data and thereby reduce storage costs.
Advantages:
• The technology is more sensitive to subthreshold image changes and is more robust to the presence of extraneous features and noise as compared with Fourier or Wavelet analysis.
• The algorithm is computationally fast so that it can be used for real-time analysis.
• The technology can be rapidly implemented with a few lines of computer software code.
Patent Status: Patent Pending
Licensing Status: Available for Sponsored Research Support
Publications:
Ciaccio et. al. Biomedical Engineering Online 2010 9:44