Ground Reaction Force Estimates from ActiGraph GT3X+ Hip Accelerations

• Published in: PloS one Vol. 9; no. 6; p. e99023
• Main Authors: Neugebauer, Jennifer M., Collins, Kelsey H., Hawkins, David A.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 10.06.2014; Public Library of Science (PLoS)
• Subjects: Acceleration; Actigraphy; Activities of daily living; Adult; Adults; Analysis; Biology and Life Sciences; Biomechanical Phenomena; Biomedical engineering; Braking; Data collection; Demography; Female; Females; Gait; Hip; Hip - physiology; Humans; Laboratories; Locomotion; Male; Males; Mathematical models; Medicine and Health Sciences; Model accuracy; Neurobiology; Neurosciences; Physiology; Running; Somatotropin-releasing hormone; Walking; Young Adult; Young adults; United States > US; California
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0099023

Simple methods to quantify ground reaction forces (GRFs) outside a laboratory setting are needed to understand daily loading sustained by the body. Here, we present methods to estimate peak vertical GRF (pGRFvert) and peak braking GRF (pGRFbrake) in adults using raw hip activity monitor (AM) acceleration data. The purpose of this study was to develop a statistically based model to estimate pGRFvert and pGRFbrake during walking and running from ActiGraph GT3X+ AM acceleration data. 19 males and 20 females (age 21.2 ± 1.3 years, height 1.73 ± 0.12 m, mass 67.6 ± 11.5 kg) wore an ActiGraph GT3X+ AM over their right hip. Six walking and six running trials (0.95-2.19 and 2.20-4.10 m/s, respectively) were completed. Average of the peak vertical and anterior/posterior AM acceleration (ACCvert and ACCbrake, respectively) and pGRFvert and pGRFbrake during the stance phase of gait were determined. Thirty randomly selected subjects served as the training dataset to develop generalized equations to predict pGRFvert and pGRFbrake. Using a holdout approach, the remaining 9 subjects were used to test the accuracy of the models. Generalized equations to predict pGRFvert and pGRFbrake included ACCvert and ACCbrake, respectively, mass, type of locomotion (walk or run), and type of locomotion acceleration interaction. The average absolute percent differences between actual and predicted pGRFvert and pGRFbrake were 8.3% and 17.8%, respectively, when the models were applied to the test dataset. Repeated measures generalized regression equations were developed to predict pGRFvert and pGRFbrake from ActiGraph GT3X+ AM acceleration for young adults walking and running. These equations provide a means to estimate GRFs without a force plate.