Table 1.
Attributes of experimental datasets used for fall detection.
Fig 1.
Detailed flowchart of the fall detection system using extracted geometric pose data.
Algorithm 1.
Pose angle-based fall detection systems (PIFR)
Table 2.
Hyperparameters for training machine learning classifiers.
Fig 2.
Correlation plot illustrating the significance and relationships of extracted features for feature importance analysis.
Fig 3.
Visualization of feature changes over sequential frames for pose-based fall detection analysis.
Table 3.
Performance evaluation results of each classifier on the test dataset.
Table 4.
Performance evaluation results of the proposed systems.
Fig 4.
Demonstration of fall detection system results using pose-based analysis in an indoor environment.
Fig 5.
Demonstration of fall detection system results using pose-based analysis in an outdoor environment.