Automated Detection of Caffeinated Coffee-Induced Short-Term Effects on ECG Signals Using EMD, DWT, and WPD

Evaluation of the responsiveness pattern to caffeine through a smart data-driven ECG non-linear multi-band analysis

This study aimed to explore more efficient ways of administering caffeine to the body by investigating the impact of caffeine on the modulation of the nervous system's activity through the analysis of electrocardiographic signals (ECG). An ECG non-linear multi-band analysis using Discrete Wavelet Transform (DWT) was employed to extract various features from healthy individuals exposed to different caffeine consumption methods: expresso coffee (EC), decaffeinated coffee (ED), Caffeine Oral Films (OF_caffeine), and placebo OF (OF_placebo). Non-linear feature distributions representing every ECG minute time series have been selected by PCA with different variance percentages to serve as inputs for 23 machine learning models in a leave-one-out cross-validation process for analyzing the behavior differences between ED/EC and OF_placebo/OF_caffeine groups, respectively, over time. The study generated 50-point accuracy curves per model, representing the discrimination power between groups throughout the 50 min. The best model accuracies for ED/EC varied between 30 and 70 %, (using the decision tree classifier) and OF_placebo/OF_caffeine ranged from 62 to 84 % (using Fine Gaussian). Notably, caffeine delivery through OFs demonstrated effective capacity compared to its placebo counterpart, as evidenced by significant differences in accuracy curves between OF_placebo/OF_caffeine. Caffeine delivery via OFs also exhibited rapid dissolution efficiency and controlled release rate over time, distinguishing it from EC. The study supports the potential of caffeine delivery through Caffeine OFs as a superior technology compared to traditional methods by means of ECG analysis. It highlights the efficiency of OFs in controlling the release of caffeine and underscores their promise for future caffeine delivery systems.

A Review on the Applications of Time-Frequency Methods in ECG Analysis

The joint time-frequency analysis method represents a signal in both time and frequency. Thus, it provides more information compared to other one-dimensional methods. Several researchers recently used time-frequency methods such as the wavelet transform, short-time Fourier transform, empirical mode decomposition and reported impressive results in various electrophysiological studies. The current review provides comprehensive knowledge about different time-frequency methods and their applications in various ECG-based analyses. Typical applications include ECG signal denoising, arrhythmia detection, sleep apnea detection, biometric identification, emotion detection, and driver drowsiness detection. The paper also discusses the limitations of these methods. The review will form a reference for future researchers willing to conduct research in the same field.

The acute effects of coffee consumption on blood glucose and it’s relationship with serum cortisol and insulin in females

This research was aimed at analyzing the acute effects of Arabica black coffee consumption on blood glucose, insulin, and serum cortisol levels, as well as determining the pharmacological effects of black coffee as an antihyperglycemic. A randomized control trial with healthy female subjects was used in this study. There were 20 volunteers in total: 9 as the control group and 11 as the trial group. The treatment included brewing 10 grams of Gayo Arabica black coffee powder with 150 ml of boiling water. Blood glucose, insulin, and cortisol levels were measured twice, before and after 60 minutes of coffee consumption. An independent sample t-test (p < 0.05), Pearson correlation test (p < 0.05), and simple linear correlation test (p < 0.05) were used to analyze the data. Blood glucose levels and serum cortisol levels decreased significantly after coffee consumption in the trial group (p = 0.002* and p = 0.001*). There was no significant negative correlation between glucose and insulin levels (r = -0.122; p = 0.721). On the other hand, there was a significant positive correlation between cortisol levels and blood glucose (r = 0.651; p = 0.002*). In conclusion, a single cup of Gayo Arabica black coffee reduces blood sugar and serum cortisol levels, but does not increase serum insulin levels. Blood glucose levels correlate positively with serum cortisol levels in healthy female.