Objective: Nowadays, methods for ECG quality assessment are mostly designed to binary distinguish between good/bad quality of the whole signal. Such classification is not suitable to long-term data ...collected by wearable devices. In this paper, a novel approach to estimate long-term ECG signal quality is proposed. Methods: The real-time quality estimation is performed in a local time window by calculation of continuous signal-to-noise ratio (SNR) curve. The layout of the data quality segments is determined by analysis of SNR waveform. It is distinguished between three levels of ECG signal quality: signal suitable for full wave ECG analysis, signal suitable only for QRS detection, and signal unsuitable for further processing. Results: The SNR limits for reliable QRS detection and full ECG waveform analysis are 5 and 18 dB respectively. The method was developed and tested using synthetic data and validated on real data from wearable device. Conclusion: The proposed solution is a robust, accurate and computationally efficient algorithm for annotation of ECG signal quality that will facilitate the subsequent tailored analysis of ECG signals recorded in free-living conditions. Significance: The field of long-term ECG signals self-monitoring by wearable devices is swiftly developing. The analysis of massive amount of collected data is time consuming. It is advantageous to characterize data quality in advance and thereby limit consequent analysis to useable signals.
Accurate automated detection of P waves in ECG allows to provide fast correct diagnosis of various cardiac arrhythmias and select suitable strategy for patients' treatment. However, P waves detection ...is a still challenging task, especially in long-term ECGs with manifested cardiac pathologies. Software tools used in medical practice usually fail to detect P waves under pathological conditions. Most of recently published approaches have not been tested on such the signals at all. Here we introduce a novel method for accurate and reliable P wave detection, which is success in both normal and pathological cases. Our method uses phasor transform of ECG and innovative decision rules in order to improve P waves detection in pathological signals. The rules are based on a deep knowledge of heart manifestation during various arrhythmias, such as atrial fibrillation, premature ventricular contraction, etc. By involving the rules into the decision process, we are able to find the P wave in the correct location or, alternatively, not to search for it at all. In contrast to another studies, we use three, highly variable annotated ECG databases, which contain both normal and pathological records, to objectively validate our algorithm. The results for physiological records are Se = 98.56% and PP = 99.82% for MIT-BIH Arrhythmia Database (MITDP, with MITDB P-Wave Annotations) and Se = 99.23% and PP = 99.12% for QT database. These results are comparable with other published methods. For pathological signals, the proposed method reaches Se = 96.40% and PP = 91.56% for MITDB and Se = 93.07% and PP = 88.60% for Brno University of Technology ECG Signal Database with Annotations of P wave (BUT PDB). In these signals, the proposed detector greatly outperforms other methods and, thus, represents a huge step towards effective use of fully automated ECG analysis in a real medical practice.
The performance of ECG signals compression is influenced by many things. However, there is not a single study primarily focused on the possible effects of ECG pathologies on the performance of ...compression algorithms. This study evaluates whether the pathologies present in ECG signals affect the efficiency and quality of compression. Single-cycle fractal-based compression algorithm and compression algorithm based on combination of wavelet transform and set partitioning in hierarchical trees are used to compress 125 15-leads ECG signals from CSE database. Rhythm and morphology of these signals are newly annotated as physiological or pathological. The compression performance results are statistically evaluated. Using both compression algorithms, physiological signals are compressed with better quality than pathological signals according to 8 and 9 out of 12 quality metrics, respectively. Moreover, it was statistically proven that pathological signals were compressed with lower efficiency than physiological signals. Signals with physiological rhythm and physiological morphology were compressed with the best quality. The worst results reported the group of signals with pathological rhythm and pathological morphology. This study is the first one which deals with effects of ECG pathologies on the performance of compression algorithms. Signal-by-signal rhythm and morphology annotations (physiological/pathological) for the CSE database are newly published.
Autologous cell therapy (ACT) is a new treatment for patients with no-option critical limb ischemia (NO-CLI). We evaluated the factors involved in the nonresponse to ACT in patients with CLI and ...diabetic foot. Diabetic patients (n = 72) with NO-CLI treated using ACT in our foot clinic over a period of 8 years were divided into responders (n = 57) and nonresponders (n = 15). Nonresponder was defined as an insufficient increase in transcutaneous oxygen pressure by <5 mm Hg, 3 months after ACT. Patient demographics, diabetes duration and treatment, and comorbidities as well as a cellular response to ACT, limb-related factors, and the presence of inherited thrombotic disorders were compared between the 2 groups. The main independent predictors for an impaired response to ACT were heterozygote Leiden mutation (OR 10.5; 95% CI, 1.72-4) and homozygote methylenetetrahydrofolate reductase (MTHFR 677) mutation (OR 3.36; 95% CI, 1.0-14.3) in stepwise logistic regression. Univariate analysis showed that lower mean protein C levels (P = .041) were present in nonresponders compared with responders. In conclusion, the significant predictors of an impaired response to ACT in diabetic patients with NO-CLI were inherited thrombotic disorders.
The aim of this study was to compare the serum levels of the anti-angiogenic factor endostatin (S-endostatin) as a potential marker of vasculogenesis after autologous cell therapy (ACT) versus ...percutaneous transluminal angioplasty (PTA) in diabetic patients with critical limb ischemia (CLI). A total of 25 diabetic patients with CLI treated in our foot clinic during the period 2008–2014 with ACT generating potential vasculogenesis were consecutively included in the study; 14 diabetic patients with CLI who underwent PTA during the same period were included in a control group in which no vasculogenesis had occurred. S-endostatin was measured before revascularization and at 1, 3, and 6 months after the procedure. The effect of ACT and PTA on tissue ischemia was confirmed by transcutaneous oxygen pressure (TcPO2) measurement at the same intervals. While S-endostatin levels increased significantly at 1 and 3 months after ACT (both P < 0.001), no significant change of S-endostatin after PTA was observed. Elevation of S-endostatin levels significantly correlated with an increase in TcPO2 at 1 month after ACT (r = 0.557; P < 0.001). Our study showed that endostatin might be a potential marker of vasculogenesis because of its significant increase after ACT in diabetic patients with CLI in contrast to those undergoing PTA. This increase may be a sign of a protective feedback mechanism of this anti-angiogenic factor.
Reliable P wave detection is necessary for accurate and automatic electrocardiogram (ECG) analysis. Currently, methods for P wave detection in physiological conditions are well-described and ...efficient. However, methods for P wave detection during pathology are not generally found in the literature, or their performance is insufficient. This work introduces a novel method, based on a phasor transform, as well as innovative rules that improve P wave detection during pathology. These rules are based on the extraction of a heartbeats' morphological features and knowledge of heart manifestation during both physiological and pathological conditions. To properly evaluate the performance of the proposed algorithm in pathological conditions, a standard database with a sufficient number of reference P wave positions is needed. However, such a database did not exist. Thus, ECG experts annotated 12 chosen pathological records from the MIT-BIH Arrhythmia Database. These annotations are publicly available via Physionet. The algorithm performance was also validated using physiological records from the MIT-BIH Arrhythmia and QT databases. The results for physiological signals were Se = 98.42% and PP = 99.98%, which is comparable to other methods. For pathological signals, the proposed method reached Se = 96.40% and PP = 85.84%, which greatly outperforms other methods. This improvement represents a huge step towards fully automated analysis systems being respected by ECG experts. These systems are necessary, particularly in the area of long-term monitoring.
Abstract Background aims The aim of our study was to compare the effect of autologous stem cell therapy (SCT) and percutaneous transluminal angioplasty (PTA) on diabetic foot disease (DFD) in ...patients with critical limb ischemia (CLI). Methods Thirty-one patients with DFD and CLI treated by autologous stem cells and 30 patients treated by PTA were included in the study; 23 patients with the same inclusion criteria who could not undergo PTA or SCT formed the control group. Amputation-free survival, transcutaneous oxygen pressure (TcPO2 ) and wound healing were assessed over 12 months. Results Amputation-free survival after 6 and 12 months was significantly greater in the SCT and PTA groups compared with controls ( P = 0.001 and P = 0.0029, respectively) without significant differences between the active treatment groups. Increase in TcPO2 did not differ between SCT and PTA groups until 12 months (both P s < 0.05 compared with baseline), whereas TcPO2 in the control group did not change over the follow-up period. More healed ulcers were observed up to 12 months in the SCT group compared with the PTA and control groups (84 versus 57.7 versus 44.4 %; P = 0.042). Conclusions Our study showed comparable effects of SCT and PTA on CLI, a major amputation rate that was superior to conservative therapy in patients with diabetic foot and an observable effect of SCT on wound healing. Our results support SCT as a potential promising treatment in patients with CLI and diabetic foot.
Accurate detection of cardiac pathological events is an important part of electrocardiogram (ECG) evaluation and subsequent correct treatment of the patient. The paper introduces the results of a ...complex study, where various aspects of automatic classification of various heartbeat types have been addressed. Particularly, non-ischemic, ischemic (of two different grades) and subsequent ventricular premature beats were classified in this combination for the first time. ECGs recorded in rabbit isolated hearts under non-ischemic and ischemic conditions were used for analysis. Various morphological and spectral features (both commonly used and newly proposed) as well as classification models were tested on the same data set. It was found that: a) morphological features are generally more suitable than spectral ones; b) successful results (accuracy up to 98.3% and 96.2% for morphological and spectral features, respectively) can be achieved using features calculated without time-consuming delineation of QRS-T segment; c) use of reduced number of features (3 to 14 features) for model training allows achieving similar or even better performance as compared to the whole feature sets (10 to 29 features); d) k-nearest neighbours and support vector machine seem to be the most appropriate models (accuracy up to 98.6% and 93.5%, respectively).
The assessment of ECG signal quality after compression is an essential part of the compression process. Compression facilitates the signal archiving, speeds up signal transmission, and reduces the ...energy consumption. Conversely, lossy compression distorts the signals. Therefore, it is necessary to express the compression performance through both compression efficiency and signal quality. This paper provides an overview of objective algorithms for the assessment of both ECG signal quality after compression and compression efficiency. In this area, there is a lack of standardization, and there is no extensive review as such. 40 methods were tested in terms of their suitability for quality assessment. For this purpose, the whole CSE database was used. The tested signals were compressed using an algorithm based on SPIHT with varying efficiency. As a reference, compressed signals were manually assessed by two experts and classified into three quality groups. Owing to the experts’ classification, we determined corresponding ranges of selected quality evaluation methods’ values. The suitability of the methods for quality assessment was evaluated based on five criteria. For the assessment of ECG signal quality after compression, we recommend using a combination of these methods: PSim SDNN, QS, SNR1, MSE, PRDN1, MAX, STDERR, and WEDD SWT.
Compression of ECG signal is essential especially in the area of signal transmission in telemedicine. There exist many compression algorithms which are described in various details, tested on various ...datasets and their performance is expressed by different ways. There is a lack of standardization in this area. This study points out these drawbacks and presents new compression algorithm which is properly described, tested and objectively compared with other authors. This study serves as an example how the standardization should look like. Single-cycle fractal-based (SCyF) compression algorithm is introduced and tested on 4 different databases-CSE database, MIT-BIH arrhythmia database, High-frequency signal and Brno University of Technology ECG quality database (BUT QDB). SCyF algorithm is always compared with well-known algorithm based on wavelet transform and set partitioning in hierarchical trees in terms of efficiency (2 methods) and quality/distortion of the signal after compression (12 methods). Detail analysis of the results is provided. The results of SCyF compression algorithm reach up to avL = 0.4460 bps and PRDN = 2.8236%.
PDF
