Wearable Sensor Systems for Fall Risk Assessment: A Review - Subramaniam, Sophini; Faisal, Abu Ilius; Deen, M. Jamal (Frontiers in Digital Health, 2022)
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. The most 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. Insole-based systems are wearable systems that have also been 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. Parameters relevant to falls that have been investigated using inertial sensor-based and insole-based devices include but are not limited to centre 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 render 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 manuscript reviews inertial sensor-based and insole-based wearable devices that have been developed for applications related to falls. Key points including spatiotemporal parameters, biomechanical gait parameters, physical activities and data analysis methods pertaining to recently developed systems, current challenges and future perspectives are described in this review.