Sensor Technologies for Fall Detection Systems: A Review

Anuradha Singh, Saeed Ur Rehman, Sira Yongchareon, Peter Han Joo Chong

Research output: Contribution to journalReview articlepeer-review

68 Citations (Scopus)


The risk of falls in older adults restrict their social life and independent living. The assisted living devices help older adults to live independently in their home, giving a psychological boost, and releasing the burden on the caregiver and the healthcare providers. A robust and accurate fall detection system is essential to provide immediate help and to reduce the severe post-fall consequences, and the associated medical care cost significantly. This review aims to provide a comprehensive technical insight into the existing fall detection system, to classify various approaches and the challenges encountered during implementation. The fall detectors are broadly classified into three categories, namely wearable, ambiance-based, and hybrid sensing detectors, which are further explored by the sensor technology. This review provides a comprehensive overview of each competing sensor technology ranging from an accelerometer, pressure sensor, and radar to camera-based and their infusion into a complete fall detection system. It outlines the strength and limitations of different sensor fall detection systems in terms of feature extraction, classification, performance, and experimental dataset. The user adaptability, installation complexity, and power requirement of the systems are the main areas, which are not addressed adequately in the literature. In the end, the review provides a basic framework in deciding the technology for a specific scenario or location according to the prerequisites for the deployment.

Original languageEnglish
Pages (from-to)6889-6919
Number of pages31
JournalIEEE Sensors Journal
Issue number13
Publication statusPublished - 1 Jul 2020


  • Assisted living
  • elderly assisted living
  • fall detection
  • sensor technology
  • smart homes
  • wearable sensor


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