Data and code of the research article titled: "Recurrence quantification analysis of photoplethysmography time series for assessing patients with peripheral artery disease"

Data and code used to obtain the results in our research article titled: "Recurrence quantification analysis of photoplethysmography time series for assessing patients with peripheral artery disease" by David Hernández-Obín, Gertrudis Hortensia González-Gómez, Adriana Torres Machorro and Claudia Lerma. This article will be published as an original article in the special issue “Recurrence-Based Methods Across Disciplines: From Theory to Practice” of the journal The European Physical Journal Special Topics. Files description: PublicData_RQA_PPG_DHO.xlsx: Database with mean and standard deviation of recurrence quantification analysis (RQA) of photoplethysmography (PPG) morphological parameters evaluated from 40 legs of patients with peripheral artery disease (PAD). This database include demographic and clinical data for patients. Ankle brachial index (ABI) is included to classify if the leg had a normal or an altered ABI. times_ar: binary file that contains the annotated times of the time series. Upload this file when running the python notebook RQA_PPG_DHO.ipynb. values_wl: binary file that contains the time series with linear trend. Upload this file when running the python notebook RQA_PPG_DHO.ipynb. RQA_PPG_DHO.ipynb: In this notebook, we will show an example to compute RQA for PPG signals from patients with peripheral artery disease (PAD). The code shows the general procedure we followed to obtain the results in our research article. RQAdatabase_columns.txt: text file that describes the columns of the database PublicData_RQA_PPG_DHO.xlsx.