Birth asphyxia a potential cause of death is also associated with acute, and chronic morbidities. The traditional and immediate approach to monitor birth asphyxia (i.e., arterial blood gas analysis) is highly invasive and intermittent. Additionally, alternative non-invasive approaches such as pulse oximeter can be problematic, due to the possibility of false and erroneous measurements. Therefore, further research is needed to explore alternative non-invasive and accurate monitoring methods for asphyxiated neonates. This study aims to investigate prominent ECG features based on pH estimation that could potentially be used to explore non-invasive, accurate, and continuous monitoring of asphyxiated neonates. The dataset contains 274 segments of ECG and pH values recorded simultaneously. After pre-processing of data, principal component analysis and Pan-Tompkins algorithm are used for each segment, to determine the most significant ECG cycle, and to compute the ECG features. Descriptive statistics are performed to describe the main properties of the dataset. The Kruskal-Wallis nonparametric test is then used to analyse differences between the two groups. Finally, Dunn–Šidák post-hoc test is utilised for individual comparison among mean ranks of all groups. This study showed that ECG features (mainly QT, QTc, and Tslope/ T) based on pH estimation differed significantly in asphyxiated neonates.