Examination of a foot mounted IMU-based methodology for a running gait assessment

Abstract

Gait assessment is essential to understand injury prevention mechanisms during running, where high-impact forces can lead to a range of injuries in the lower extremities. Information regarding the running style to increase efficiency and/or selection of the correct running equipment, such as shoe type, can minimize the risk of injury, e.g., matching a runner's gait to a particular set of cushioning technologies found in modern shoes (neutral/support cushioning). Awareness of training or selection of the correct equipment requires an understanding of a runner's biomechanics, such as determining foot orientation when it strikes the ground. Previous work involved a low-cost approach with a foot-mounted inertial measurement unit (IMU) and an associated zero-crossing-based methodology to objectively understand a runner's biomechanics (in any setting) to learn about shoe selection. Here, an investigation of the previously presented ZC-based methodology is presented only to determine general validity for running gait assessment in a range of running abilities from novice (8 km/h) to experienced (16 km/h+). In comparison to Vicon 3D motion tracking data, the presented approach can extract pronation, foot strike location, and ground contact time with good [ICC(2,1) > 0.750] to excellent [ICC(2,1) > 0.900] agreement between 8–12 km/h runs. However, at higher speeds (14 km/h+), the ZC-based approach begins to deteriorate in performance, suggesting that other features and approaches may be more suitable for faster running and sprinting tasks.

Internet-of-Things-Enabled Markerless Running Gait Assessment from a Single Smartphone Camera

“…For example, wearable sensors or 3D-motion reflective markers often rely upon precise anatomical placement for optimal use [ 14 , 15 ]. Additionally, such technologies are naturally intrusive, often requiring adhesion to the skin or clothes by, e.g., medical tape [ 16 ], which may cause discomfort and thus, affect a natural running cycle; limiting the usability of such approaches for habitual use. Consequently, investigation into the use of markerless assessment systems for running gait assessment is warranted.…”

Accuracy and Interpretation of the Acceleration from an Inertial Measurement Unit When Applied to the Sprint Performance of Track and Field Athletes

“…Although they obtain data in real time, the information is limited and they do not provide essential performance indicators to coaches and athletes, such as the step rate and step length [ 5 , 8 , 9 ]. Motion capture video-based systems and force plates are generally considered the gold standard in running assessments [ 10 ]. They can characterize technical running aspects or verify that high acceleration values occur when high propulsive forces and low braking forces are produced [ 11 , 12 ].…”

“…Additionally, they allow the verification of the ratio of forces related to the best performance during the acceleration phases [ 1 , 13 ]. These kinds of instruments can obtain useful information, but they have limitations in biomechanical studies, such as in their technical execution [ 14 ], because they have difficulties in terms of the clothing restrictions when placing landmarks [ 10 , 15 ]. Furthermore, they are expensive [ 6 , 7 , 16 ], are difficult to transport [ 17 ], and they are very time-consuming [ 18 ].…”

“…They have been applied in sprint testing due to their ease of application and transportation provided by their small size, as well as their ability to acquire validated parameters continuously and systematically and to monitor athletes’ training in real situations [ 6 , 7 , 14 , 15 ]. Recently, Young et al [ 10 ] applied the zero-crossing method for running techniques with velocities between 8 km/h (novice) and 16 km/h (expert) compared with Vicon 3D motion tracking data, obtaining good to excellent agreement with pronation, foot strike location, and ground contact time data. Furthermore, the authors identified that with higher velocities, this agreement decreases [ 10 ].…”

“…Recently, Young et al [ 10 ] applied the zero-crossing method for running techniques with velocities between 8 km/h (novice) and 16 km/h (expert) compared with Vicon 3D motion tracking data, obtaining good to excellent agreement with pronation, foot strike location, and ground contact time data. Furthermore, the authors identified that with higher velocities, this agreement decreases [ 10 ]. Specifically, in the sprint analysis, Kuznetsov [ 4 ] presented an IMU to derive information about the step parameters from acceleration and angular velocity data and identified essential information for coaching during daily workouts with a low time consumption.…”