Accession Number : ADA620828


Title :   Reliable Real-time Calculation of Heart-rate Complexity in Critically Ill Patients Using Multiple Noisy Waveform Sources


Descriptive Note : Journal article


Corporate Author : ARMY INST OF SURGICAL RESEARCH FORT SAM HOUSTON TX


Personal Author(s) : Liu, Nehemiah T ; Cancio, Leopoldo C ; Salinas, Jose ; Batchinsky, Andriy I


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a620828.pdf


Report Date : Jan 2014


Pagination or Media Count : 10


Abstract : Heart-rate complexity (HRC) has been proposed as a new vital sign for critical care medicine. The purpose of this research was to develop a reliable method for determining HRC continuously in real time in critically ill patients using multiple waveform channels that also compensates for noisy and unreliable data. Using simultaneously acquired electrocardiogram (Leads I, II, V) and arterial blood pressure waveforms sampled at 360 Hz from 250 patients (over 375 h of patient data), we evaluated a new data fusion framework for computing HRC in real time. The framework employs two algorithms as well as signal quality indices. HRC was calculated (via the method of sample entropy), and equivalence tests were then performed. Bland Altman plots and box plots of differences between mean HRC values were also obtained. Finally, HRC differences were analyzed by paired t tests. The gold standard for obtaining true means was manual verification of R waves and subsequent entropy calculations. Equivalence tests between mean HRC values derived from manually verified sequences and those derived from automatically detected peaks showed that the Fusion values were the least statistically different from the gold standard. Furthermore, the fusion of waveform sources produced better error density distributions than those derived from individual waveforms. The data fusion framework was shown to provide in real-time a reliable continuously streamed HRC value, derived from multiple waveforms in the presence of noise and artifacts. This approach will be validated and tested for assessment of HRC in critically ill patients.


Descriptors :   *CLINICAL MEDICINE , *COMPUTER AIDED DIAGNOSIS , *DECISION SUPPORT SYSTEMS , *ELECTROCARDIOGRAPHY , *HEART RATE , ALGORITHMS , BLOOD PRESSURE , COMPUTER LOGIC , DATA FUSION , DATA PROCESSING , ENTROPY , LEARNING MACHINES , MATHEMATICAL FILTERS , NETWORK ARCHITECTURE , PATIENTS , PHYSIOLOGICAL EFFECTS , RELIABILITY , SIGNAL PROCESSING , STATISTICAL ANALYSIS , TEST AND EVALUATION , TIME SERIES ANALYSIS , WAVEFORMS


Subject Categories : Medicine and Medical Research
      Cybernetics
      Biomedical Instrumentation and Bioengineering


Distribution Statement : APPROVED FOR PUBLIC RELEASE