Sensor-based motion analysis for dementia detection: a systematic review

Compared with traditional dementia diagnostic pathways that often involve lengthy assessment cycles, this review's findings provide guidance on refining motion-based sensor selection, task design, and analytical methods to improve standardisation and reproducibility. Future research should prioritise: (1) large-scale, longitudinal data collection with confirmed dementia diagnoses to support machine learning model development; (2) standardisation of sensor types, placements, and motion metrics to enhance comparability; and (3) integration of multimodal data, including motion and brain signals, using explainable machine learning techniques to improve detection accuracy and clinical interpretability.