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Wearable Sensor Systems for Fall Risk Assessment: A Review

期刊

FRONTIERS IN DIGITAL HEALTH
卷 4, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fdgth.2022.921506

关键词

fall risk assessment; fall detection; wearables; smart insole; inertial sensors; plantar pressure; gait analysis; machine learning

资金

  1. Canada Research Chair program
  2. Natural Sciences and Engineering Research Council (NSERC) of Canada

向作者/读者索取更多资源

Fall risk assessment and fall detection are crucial for preventing adverse health outcomes. Wearable sensor systems, including inertial measurement units (IMUs) and insole-based devices, can provide meaningful information about gait characteristics and fall-related parameters by collecting motion data and plantar pressure distribution data. By improving existing systems, future wearable sensors can enable more accurate and convenient fall risk assessment.
Fall risk assessment and fall detection are crucial for the prevention of adverse and long-term health outcomes. Wearable sensor systems have been used to assess fall risk and detect falls while providing additional meaningful information regarding gait characteristics. Commonly used wearable systems for this purpose are inertial measurement units (IMUs), which acquire data from accelerometers and gyroscopes. IMUs can be placed at various locations on the body to acquire motion data that can be further analyzed and interpreted. Insole-based devices are wearable systems that were also developed for fall risk assessment and fall detection. Insole-based systems are placed beneath the sole of the foot and typically obtain plantar pressure distribution data. Fall-related parameters have been investigated using inertial sensor-based and insole-based devices include, but are not limited to, center of pressure trajectory, postural stability, plantar pressure distribution and gait characteristics such as cadence, step length, single/double support ratio and stance/swing phase duration. The acquired data from inertial and insole-based systems can undergo various analysis techniques to provide meaningful information regarding an individual's fall risk or fall status. By assessing the merits and limitations of existing systems, future wearable sensors can be improved to allow for more accurate and convenient fall risk assessment. This article reviews inertial sensor-based and insole-based wearable devices that were developed for applications related to falls. This review identifies key points including spatiotemporal parameters, biomechanical gait parameters, physical activities and data analysis methods pertaining to recently developed systems, current challenges, and future perspectives.

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