Accuracy and comparison of sensor-based gait speed estimations under standardized and daily life conditions in children undergoing rehabilitation

Abstract

Background Gait speed is a widely used outcome measure to assess the walking abilities of children undergoing rehabilitation. It is routinely determined during a walking test under standardized conditions, but it remains unclear whether these outcomes reflect the children's performance in daily life. An ankle-worn inertial sensor provides a usable opportunity to measure gait speed in the children's habitual environment. However, sensor-based gait speed estimations need to be accurate to allow for comparison of the children's gait speed between a test situation and daily life. Hence, the first aim of this study was to determine the measurement error of a novel algorithm that estimates gait speed based on data of a single ankle-worn inertial sensor in children undergoing rehabilitation. The second aim of this study was to compare the children’s gait speed between standardized and daily life conditions. Methods Twenty-four children with walking impairments completed four walking tests at different speeds (standardized condition) and were monitored for one hour during leisure or school time (daily life condition). We determined accuracy by comparing sensor-based gait speed estimations with a reference method in both conditions. Eventually, we compared individual gait speeds between the two conditions. Results The measurement error was 0.01 ± 0.07 m/s under the standardized and 0.04 ± 0.06 m/s under the daily life condition. Besides, the majority of children did not use the same speed during the test situation as in daily life. Conclusion This study demonstrates an accurate method to measure children's gait speed during standardized walking tests and in the children's habitual environment after rehabilitation. It only requires a single ankle sensor, which potentially increases wearing time and data quality of measurements in daily life. We recommend placing the sensor on the less affected side, unless the child wears one orthosis. In this latter case, the sensor should be placed on the side with the orthosis. Moreover, this study showed that most children did not use the same speed in the two conditions, which encourages the use of wearable inertial sensors to assess the children's walking performance in their habitual environment following rehabilitation.

Acceptability of wearable inertial sensors, completeness of data, and day-to-day variability of everyday life motor activities in children and adolescents with neuromotor impairments

“…First, lying, sitting, and standing positions were classified with the orientation of the thigh and trunk sensors (10). Then, we derived the time spent in each position per day based on these classifications.…”

“…Wheeling periods were detected with the sensor on the wheel and by applying predefined rules to the gyroscope data of the wheel sensor (23). Subsequently, these wheeling periods were classified as active or passive wheeling with the orientation of the wrist sensor of the dominant hand (10). First, the wheeling speed was determined by multiplying the angular rate with the radius of the wheel.…”

“…Specific characteristics of the ankle's gyroscope signal were used to identify walking periods (10). These periods were further classified as level walking or stair climbing based on the altimeter of the ankle sensor (10).…”

“…Specific characteristics of the ankle's gyroscope signal were used to identify walking periods (10). These periods were further classified as level walking or stair climbing based on the altimeter of the ankle sensor (10). In level walking periods, the walking speed and distance were determined by segmenting the data into individual gait cycles and deriving each stride length and stride time (11,24).…”

“…Then, we verified the validity of this algorithm in three subsequent studies. They showed sufficient criterion validity of the hand use measures (9), good to excellent activity classification accuracy except for stair climbing (10), and accurate gait speed estimations (11).…”