Open access
2026
Evaluation of Deep Learning Architectures on Synthetic LiDAR Sequences for Fall Detection
The study evaluates four temporal deep learning models including LSTM, GRU, CNN1D and Transformer Lite to analyze spatio temporal motion patterns from 3D LiDAR point sequences and identify the most suitable approach for accurate fall detection.
Amir Ali, Teodoro Montanaro, Ahmad Alsharoa et al.
· IEEE Access · 0 citations