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This review aims to analyze and synthesize evidence on fall detection technologies for older adults, focusing on sensor modalities and computational models.

February 17, 2026Open Access

A Systematic Review of Fall Detection and Prediction Technologies for Older Adults: An Analysis of Sensor Modalities and Computational Models

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This review aims to analyze and synthesize evidence on fall detection technologies for older adults, focusing on sensor modalities and computational models.
Conducted a systematic search of electronic databases from 2008 to 2025.
Selected 130 studies meeting inclusion criteria following PRISMA guidelines.
Extracted and thematically synthesized information on sensor technology, algorithms, and performance outcomes.
Identified three main sensor technology categories: wearable systems, ambient systems, and hybrid systems.
Showed a transition from simpler algorithms to deep learning architectures like CNNs and RNNs.
Reported high performance metrics, with accuracy, sensitivity, and specificity often exceeding 95%.

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Systematic review analyzes fall detection technologies in older adults, highlighting sensor modalities and computational models.

Cite This Study

Ishaq et al. (2026) studied this question.

synapsesocial.com/papers/6994055d4e9c9e835dfd630e https://doi.org/10.3390/app16041929

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A Systematic Review of Fall Detection and Prediction Technologies for Older Adults: An Analysis of Sensor Modalities and Computational Models

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Cite This Study

A Systematic Review of Fall Detection and Prediction Technologies for Older Adults: An Analysis of Sensor Modalities and Computational Models

Key Points

Discussion

Implication

Cite This Study

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