Falls are widely considered to be an increasingly serious public health problem. In addition to being a known cause of injury and death, falls can lead to declines in mobility and self-imposed limitations on daily activities and socialization (1, 2).

Balance and gait impairments in older individuals have been shown to contribute to an increased risk of falling (3). One parameter of gait that has received considerable attention is gait speed. “In older adults, evidence suggests that gait speed can predict several adverse outcomes, including mortality, functional dependence, well-being, cognitive decline, and frailty” (4). As individuals age, gait becomes slower and step length becomes shorter (2, 5). Slower gaits have been shown to be directly associated with an increased fall risk (2). As a result, gait speed is a key variable that health professionals can focus on to differentiate between elderly fallers and non-fallers.

Kinetisense provides an objective, efficient, and easy to use tool that can reproducibly analyze multiple gait parameters (including gait speed) that have been found to be indicative of functionality and subsequently one’s risk of fall. Being able to accurately detect those who are more likely to fall will allow practitioners to determine if a patient requires intervention, and will ultimately aid in the prevention of injury, loss of quality of life, and possibly even death.