scholarly journals Intracranial pulse pressure waveform analysis using the higher harmonics centroid

Author(s):  
Agnieszka P. Zakrzewska ◽  
Michał M. Placek ◽  
Marek Czosnyka ◽  
Magdalena Kasprowicz ◽  
Erhard W. Lang

Abstract Background The pulse waveform of intracranial pressure (ICP) is its distinctive feature almost always present in the clinical recordings. In most cases, it changes proportionally to rising ICP, and observation of these changes may be clinically useful. We introduce the higher harmonics centroid (HHC) which can be defined as the center of mass of harmonics of the ICP pulse waveform from the 2nd to 10th, where mass corresponds to amplitudes of these harmonics. We investigate the changes in HHC during ICP monitoring, including isolated episodes of ICP plateau waves. Material and methods Recordings from 325 patients treated between 2002 and 2010 were reviewed. Twenty-six patients with ICP plateau waves were identified. In the first step, the correlation between HHC and ICP was examined for the entire monitoring period. In the second step, the above relation was calculated separately for periods of elevated ICP during plateau wave and the baseline. Results For the values averaged over the whole monitoring period, ICP (22.3 ± 6.9 mm Hg) correlates significantly (R = 0.45, p = 0.022) with HHC (3.64 ± 0.46). During the ICP plateau waves (ICP increased from 20.9 ± 6.0 to 53.7 ± 9.7 mm Hg, p < 10−16), we found a significant decrease in HHC (from 3.65 ± 0.48 to 3.21 ± 0.33, p = 10−5). Conclusions The good correlation between HHC and ICP supports the clinical application of pressure waveform analysis in addition to the recording of ICP number only. Mean ICP may be distorted by a zero drift, but HHC remains immune to this error. Further research is required to test whether a decline in HHC with elevated ICP can be an early warning sign of intracranial hypertension, whether individual breakpoints of correlation between ICP and its centroid are of clinical importance.

2021 ◽  
Vol 91 ◽  
pp. 107285
Author(s):  
Inanc Karakoyun ◽  
Ayfer Colak ◽  
Melda Turken ◽  
Zeynep Altin ◽  
Fatma Demet Arslan ◽  
...  

2005 ◽  
Vol 95 (3) ◽  
pp. 273-276 ◽  
Author(s):  
Patrick S. Igbigbi ◽  
Boniface C. Msamati ◽  
Macfenton B. Shariff

We determined the arch index of able-bodied indigenous Kenyan and Tanzanian individuals free of foot pain by using their dynamic footprints to classify the foot arch type and determine the prevalence of pes planus according to a previously described method. Males had a significantly higher arch index than females in both groups, and the prevalence of pes planus in Kenyans was 432 per 1,000 population, the highest ever documented and twice as high as that in Tanzanians (203 per 1,000 population). The arch index is useful in determining the prevalence of pes planus and possibly predicting pathologic foot conditions, and it may serve as an early warning sign of structural and functional defects of the foot in a given population. (J Am Podiatr Med Assoc 95(3): 273–276, 2005)


2009 ◽  
Vol 21 (02) ◽  
pp. 139-147 ◽  
Author(s):  
Shing-Hong Liu ◽  
Kang-Ming Chang ◽  
Chu-Chang Tyan

The purpose of this study is to build an automatic disease classification algorithm by pulse waveform analysis, based on a Fuzzy C-means clustering algorithm. A self designed three-axis mechanism was used to detect the optimal position to accurately measure the pressure pulse waveform (PPW). Considering the artery as a cylinder, the sensor should detect the PPW with the lowest possible distortion, and hence an analysis of the vascular geometry and an arterial model were used to design a standard positioning procedure based on the arterial diameter changed waveform for the X-axes (perpendicular to the forearm) and Z-axes (perpendicular to the radial artery). A fuzzy C-means algorithm was used to estimate the myocardial ischemia symptoms in 35 elderly subjects with the PPW of the radial artery. Two type parameters were used to make the features, one was a harmonic value of Fourier transfer, and the other was a form factor value. A receiver operating characteristics curve was used to determine the optimal decision function. The harmonic feature vector contain second, third and fourth harmonics ( H 2, H 3, H 4) performed at the level of 69% for sensitivity and 100% for specificity while the form factor feature vector derived from left hand (LFF) and right hand (RFF) performed at the level of 100% for sensitivity and 53% for specificity. The FCM- and ROC-based clustering approach may become an efficient alternative for distinguishing patients in the risk of myocardial ischemia, besides the traditional exercise ECG examination.


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