2014 Volume 60 Issue 6 Pages 524
Objective: To develop a gait analysis system for children using new algorithms by improving the device that acquires gait data quantitatively.
Background: Quantitative evaluation of child development is essential for early detection and diagnosis of developmental disorders. Gait analysis has been expected to measure and evaluate child development1). A number of experiments have been undertaken to create a gait analysis system by combining wearable sensors with computational methodologies2). However, these methods are not sufficiently versatile for clinical application. Because the current capabilities of the device and a personal computer (PC) are not sufficient to deal with large data, the methods only provide limited information, such as on joint angle, step length, and gait velocity3). Recently, algorithms using machine-learning schemes have been developed, which can extract patterns from large datasets. In combination with suitable sensor devices, these algorithms could be applied to extract quantitative gait information.
Method: A gait analysis device developed by Hitachi Ltd. for adults was modified for children. This device comprises an inertia sensor to analyze hip joint angles, an insole-type sensor array to measure the center of pressure, and a unit to transmit these gait data to a PC wirelessly. For the safety of children, the device did not feature a hard exoskeleton (stay), although the device for adults used a stay in order to measure knee angle. The device was miniaturized to around 100 grams in weight in order to allow children’s natural movement.
Results: In a trial study on children, the gait analysis device safely acquired the change of hip joint angles and center of pressure in a time series.
Conclusion: Further development of this device and computational methods for gait analysis will facilitate the evaluation of child development.
