| dc.description.abstract | English Abstract
Background: Peripheral Arterial Occlusive disease (PAOD) is a major public health burden requiring more intensive population screening. It is one of the most underrated disease in the low-income countries and it could lead to severe cardiovascular events. Early detection of PAOD is therefore crucial for clinical practice. The PAOD is identified traditionally through the Doppler ultrasound and Ankle brachial index (ABI) which derived from the ratio of maximal pressure waveforms record from arm and ankle cuffs can be a convenient alternative method. However, it requires a rigorous methodology by trained operators and also time-consuming. And by using the traditional ABI value it is not easy for the doctors to identify the occlusion on the lower leg arteries due to the ABI values falling in the normal range of (0.9 to 1.4).
Objective: Photoplethysmography (PPG), which is similar to the pressure waveform but less expensive, can be recorded from the fingers or toes and measures volumetric blood changes brought on by pulse pressure propagation within arteries. The purpose of this study is to validate the ability of using the features derived from the PPG can helps us to identify the PAOD better when compared to the traditional ABI and can be used as alternative tool for PAOD detection.
And also, to get the PPG feature which can better differentiate the occlusion on the leg when compared to the other locations foe which the traditional ABI is in the normal range.
Material and Method: In total 130 patients suspected to have PAOD were recruited and they underwent Doppler ultrasound method to diagnose PAOD and the traditional ABI was calculated using the pressure cuff. Then the PPG signals were recorded simultaneously from the 4 locations (right and left index fingers and toes) for 10seconds, and then four 10-second sequential PPG signals were also recorded from the same locations using a single probe. The noise of PPG signals was removed by a bandpass filter (1-10 Hz) and after peak detection, the peak of the pulsatile waveforms was aligned and averaged. The averaged waveform was used to extract the waveform onset, Peak, inflection point, and end point from the second derivative of the signal. Extracted multiple features from the PPG and used those for the classification. Found the PPG features exhibit AUC of 0.8481, 74% sensitivity, 84% Specificity whereas the traditional ABI has AUC of 0.7914, 52% sensitivity, 98% Specificity. Found the PPG features have better Sensitivity and AUC when compared to the traditional ABI. Hence to improve the results extracted more features from the signal and did the classification. Found the PPG features have 0.8448 AUC, Sensitivity of 73%, specificity of 84% whereas the traditional ABI has 0.7692 AUC, Sensitivity of 48%, Specificity of 98% at the optimum threshold. The classification of the arterial occlusion location with the PPG features gave better results when compared to the traditional ABI. PPG features can identify 91.6% of patients above knee and found 65% of the patients below knee whereas at the optimum threshold of 0.9 the ABI found 75% of patients above knee and 36.7% of the patients below knee. Then Kurtosis and the Diastolic with at the 90% of the pulse height gave the better differentiation for the arteries on the above and below knee region.
Discussion: The PPG features exhibit better Sensitivity and AUC is more when compared to the traditional ABI. But the Specificity is less of the PPG features when compared to the traditional ABI. One advantage of this system is here we have used the PPG signal from the toes compared to the previous studies and done the classification using the Ultrasound results which is more reliable other than comparing it with the range of the ABI values. With the minimum amount of data on the above region the Kurtosis gave the better differentiation at the threshold of 1.7208 and the Diastolic width provided the better results for the arteries below knee. Because the nearly 30% of the PPG signal obtained from the Patients with PAOD are noisy due to the severity of the occlusion and not able to get any useful information from those values. Since the PPG signal cannot be acquired when the Occlusion is more severe. Hence it can be used as tool for the initial investigation of the PAOD detection where there is no need of complex measuring techniques are required. When we classify the patients according to the location of the occlusion such as the arteries above and below knee at the optimum threshold found for the PPG features gave better identification results when compared to the traditional ABI. Hence PPG can be used as an initial investigation tool for the identification of occlusion in all arterial position gave promising results when compared to the traditional ABI.
Incorporating deep learning techniques could offer potential improvements, paving the way for more accurate and efficient PAOD diagnosis and treatment planning, ultimately benefiting patient outcomes and healthcare practices. | en_US |