Portable Gait Lab: Estimating 3D GRF Using a Pelvis IMU in a Foot IMU Defined Frame

Abstract

Ground Reaction Forces (GRF) during gait are measured using expensive laboratory setups such as in-floor or treadmill force plates. Ambulatory measurement of GRF using wearables enables remote monitoring of gait and balance. Here, we propose using an Inertial Measurement Unit (IMU) mounted on the pelvis to estimate the GRF during gait in daily life. Calibration procedures and an Error State Extended Kalman filter (EEKF) were used to transform the accelerations at the center of mass (CoM) to the 3D GRF. The instantaneous 3D GRF was estimated for different overground walking patterns and compared with the 3D GRF measured using the reference ForceShoe TM system. Furthermore, we introduce a changing reference frame called the current step frame that followed the direction of each step made. The frame was defined using movement of the feet, and the estimated GRF were expressed in this new frame. This allowed direct comparison and validation with the reference. The mean and standard deviation of error between the estimated instantaneous 3D GRF and the reference, normalized against the range of the reference, was 12.1 ± 3.3% across all walking tasks, in the horizontal plane. The error margins show that a single pelvis IMU could be a minimal and ambulatory sensing alternative for estimating the instantaneous 3D components of GRF during overground gait.

Estimation of 3D Body Center of Mass Acceleration and Instantaneous Velocity from a Wearable Inertial Sensor Network in Transfemoral Amputee Gait: A Case Study

“…In order to facilitate MIMU-based segmental analysis in the clinical field, it is essential to keep the number of required sensors as low as possible while achieving sufficient accuracy [ 14 , 17 ]. Therefore, similarly to what is done with OMCSs, the sacral method paradigm, consisting of using a single sensor positioned on the lower back, has been widely investigated [ 34 , 35 , 36 , 37 , 38 , 39 ]. While this approach is quick and easy to implement, it was shown to lack accuracy when dynamical motion of the upper body was involved [ 2 , 37 , 39 ] or in case of asymmetrical gait pattern [ 15 , 35 ], such as for people with lower-limb amputation [ 40 , 41 ].…”

Real-Time Vertical Ground Reaction Force Estimation in a Unified Simulation Framework Using Inertial Measurement Unit Sensors

“…IMUs have recently become even more reliable as several methods to estimate GRFs using IMUs have been developed [9,10,[18][19][20][21][22]. A recent study analyzed the feasibility of using an IMU mounted underneath the walking surface and measured comparable accuracy to IMUs attached to the body [18].…”

“…An interesting trend is the addition of machine learning methods to estimate GRFs using IMUs. Most of the studies that have been previously discussed use machine learning methods to estimate GRFs with the use of IMUs [9,10,[19][20][21][22]. These studies have demonstrated promising results when estimating vertical and three-dimensional GRFs.…”

Estimating Lower Limb Kinematics using a Lie Group Constrained Extended Kalman Filter with a Reduced Wearable IMU Count and Distance Measurements

“…To achieve better performance, one may leverage long-term recordings by averaging out cycle-to-cycle variation in estimation errors over many gait cycles, or use additional sensing modalities, preferably packaged such that the number of sensor units will not increase. For example, distance ranging measurements or pressure insoles can be used to infer position of the pelvis [11,43]. Attaching cameras to the body is another interesting approach (e.g., Xu et al tracked body pose using cap-mounted fisheye cameras pointing downwards [44]; using cameras with IMUs for better position estimation [45]).…”