Algorithm for tissue ischemia estimation based on electrical impedance spectroscopy

• Published in: IEEE transactions on biomedical engineering Vol. 50; no. 12; pp. 1352 - 1359
• Main Authors: Kun, S., Ristic, B., Peura, R.A., Dunn, R.M.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.12.2003; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Animals; Artificial neural networks; Biological and medical sciences; Data mining; Diagnosis, Computer-Assisted - methods; Electric Impedance; Electrochemical impedance spectroscopy; Frequency measurement; Hydrogen-Ion Concentration; Impedance measurement; In vivo; Ischemia - diagnosis; Ischemia - physiopathology; Ischemic pain; Medical sciences; Models, Biological; Muscle, Skeletal - blood supply; Muscle, Skeletal - chemistry; Muscle, Skeletal - physiopathology; Muscles; Neural Networks (Computer); Predictive Value of Tests; Rabbits; Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects); Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Spectrum Analysis - methods; Technology. Biomaterials. Equipments. Material. Instrumentation; ischemia estimation; spectroscopy; Biomedical engineering; Electrical impedance
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2003.819846

The purpose of this paper is to present an algorithm developed for real-time estimation of skeletal muscle ischemia, based on parameters extracted from in vivo obtained electrical impedance spectra. A custom impedance spectrometer was used to acquire data sets: complex impedance spectra measured at 27 frequencies in the range of 100 Hz-1 MHz, and tissue pH. Twenty-nine in vivo animal studies on rabbit anterior tibialis muscle were performed to gather data on the behavior of tissue impedance during ischemia. An artificial neural network (ANN) was used to quantitatively describe the relationship between the parameters of complex tissue impedance spectra and tissue ischemia via pH. The ANN was trained on 1249, and tested on 946 ischemic tissue impedance data sets. A correlation of 94.5% and a standard deviation of 0.15 pH units was achieved between the ANN estimated pH and measured tissue pH values.