| AI | Artificial intelligence |
| ML | Machine learning |
| NLP | Natural language processing |
| LLMs | Large language models |
| PLS | Partial least squares |
| SVR | Support Vector Regression |
| SVM | Support Vector Machine |
| XGBoost | Extreme Gradient Boosting |
| RF | Random Forest |
| NN | Neural Network |
| KNN | K-Nearest Neighbors |
| ANN | Artificial Neural Network |
| DL | Deep Learning |
| RMSE | Root mean square error |
| DT | Decision tree |
| GC–MS | Gas chromatography–mass spectrometry |
| EEM | Excitation–Emission Matrix |
| ENR | Elastic Net Regression |
| PLS-DA | Partial least squares discriminant analysis |
| BP | Back-propagation |
| XR | Extended reality |
| VR | Virtual reality |
| AR | Augmented reality |
| MR | Mixed reality |
| HMD | Head-mounted display |
| EEG | Electroencephalogram |
| fNIRS | Functional near-infrared spectroscopy |
| fMRI | Functional magnetic resonance imaging |
| BOLD | Blood oxygenation level-dependent |
| HR | Heart rate |
| HRV | Heart rate variability |
| ANS | Autonomic nervous system |
| EDA/GSR | Electrodermal activity/Galvanic skin response |
| SC | Skin conductance |
| SCL | Skin conductance level |
| SR | Skin resistance |
| ECG | Electrocardiography |
| B.P. | Blood pressure |
| FEA | Facial expression analysis |
| EMG | Electromyography |
| IoT | Internet of Things |
| E-nose | Electronic noses |
| E-tongue | Electronic tongues |