Background: The anterior-posterior ground reaction force (AP-GRF) and propulsion and braking metrics derived from the AP-GRF time series are meaningful indicators of locomotor function across healthy and neurological diagnostic groups. In this paper, we describe the use of a minimal set of wearable inertial measurement units (IMUs) to indirectly measure the AP-GRF time series during healthy and hemiparetic walking.
Methods: Ten healthy individuals and five individuals with chronic post-stroke hemiparesis completed a 6-minute walk test over a walking track instrumented with six forceplates while wearing three IMUs securely attached to the pelvis, thigh, and shank. Subject-specific models driven by IMU-measured thigh and shank angles and an estimate of body acceleration provided by the pelvis IMU were used to generate indirect estimates of the AP-GRF time series. Propulsion and braking point metrics (i.e., peaks, peak timings, and impulses) were extracted from the IMU-generated time series. A 75%-25% split of 6-minute walk test data was used to train and validate the models. Indirect estimates of the AP-GRF time series and point metrics were compared to direct measurements of the same made by the reference standard forceplates.
Results: Indirect measurements of the AP-GRF time series strongly approximated the direct measurements made by forceplates, with low error and high consistency in both the healthy (RMSE = 4.5 %bw; R2 = 0.93) and post-stroke (RMSE = 2.65 %bw; R2 = 0.90) cohorts. In the healthy cohort, the average error between indirect and direct measurements of the magnitude (% bodyweight, %bw) and timing (% stance phase, %sp) of the peak propulsion and braking point metrics was less than 1.8 %bw and 0.8 %sp in the training dataset and less than 2.7 %bw and 1.4 %sp in the validation dataset. Similarly, the average error for the propulsion and braking impulses was less than 0.52 %bw and 0.68 %bw for the training and validation datasets, respectively. In the post-stroke cohort, the average error was less or comparable for every metric.
Conclusions: Highly accurate estimates of the AP-GRF time series and key propulsion and braking point metrics can be generated using three strategically mounted IMUs and subject-specific calibrations. This study is a foundational step toward the development of point-of-care diagnostic systems that can catalyze the routine assessment and management of propulsion and braking locomotor deficits during rehabilitation.