Are wearable insoles a validated tool for quantifying transfemoral amputee gait asymmetry?

BACKGROUND: Amputee gait is known to be asymmetrical, especially during loading of the lower limb. Monitoring asymmetry could be useful in quantifying patient performance during rehabilitation. Wearable insoles can provide normal ground reaction force asymmetry in real-life conditions. OBJECTIVES: To characterize the validity of Loadsol® insoles versus force plates in quantifying normal ground reaction force and gait asymmetry. To determine the influence walking speed has on loading asymmetry in transfemoral amputees. STUDY DESIGN: This is a prospective study. METHODS: Six transfemoral amputees, wearing Loadsol® insoles, walked at three self-selected speeds on force plates. Validity was assessed by comparing normal ground reaction force data from the insoles and force plates. The Absolute Symmetry Index was used to calculate gait loading asymmetry at each speed. RESULTS: Normalized root mean square errors for the normal ground reaction forces were 6.6% (standard deviation = 2.3%) and 8.9% (standard deviation = 3.8%); correlation coefficients were 0.91 and 0.95 for the prosthetic and intact limb, respectively. The mean error for Absolute Symmetry Index parameters ranged from -2.67% to 4.35%. Loading asymmetry increased with walking speed. CONCLUSION: This study quantified the validity of Loadsol® insoles in assessing loading asymmetry during gait in transfemoral amputees. The calibration protocol could be improved to better integrate it into a clinical setting. However, our results support the relevance of using such insoles during the clinical follow-up of transfemoral amputees. CLINICAL RELEVANCE: This is the first study to validate Loadsol® insoles versus force plates and report on loading asymmetry during gait at three different speeds in transfemoral amputees. Loadsol® insoles, which provide visual and audio feedback, are clinically easy to use and could have beneficial application in the amputee's rehabilitation and follow-up.

Real Time Estimation of the Pose of a Lower Limb Prosthesis from a Single Shank Mounted IMU.

The command of a microprocessor-controlled lower limb prosthesis classically relies on the gait mode recognition. Real time computation of the pose of the prosthesis (i.e., attitude and trajectory) is useful for the correct identification of these modes. In this paper, we present and evaluate an algorithm for the computation of the pose of a lower limb prosthesis, under the constraints of real time applications and limited computing resources. This algorithm uses a nonlinear complementary filter with a variable gain to estimate the attitude of the shank. The trajectory is then computed from the double integration of the accelerometer data corrected from the kinematics of a model of inverted pendulum rolling on a curved arc foot. The results of the proposed algorithm are evaluated against the optoelectronic measurements of walking trials of three people with transfemoral amputation. The root mean square error (RMSE) of the estimated attitude is around 3°, close to the Kalman-based algorithm results reported in similar conditions. The real time correction of the integration of the inertial measurement unit (IMU) acceleration decreases the trajectory error by a factor of 2.5 compared to its direct integration which will result in an improvement of the gait mode recognition.

Estimation of the walking speed of individuals with transfemoral amputation from a single prosthetic shank-mounted IMU.

Microprocessor prosthetic knees, able to restore the gait of people with transfemoral amputation, are now often equipped with sensors embedded in the prosthetic shank, which could be used to assess some gait characteristics during real-life activities. In particular, an estimation of the walking speed during the locomotion of those subjects would be a relevant indicator of the performance. However, if methods have already been proposed in the literature to compute this walking speed, none are directly usable in this context and with this population. For these reasons, the current study proposed to estimate the instantaneous walking speed with a shank-embedded Inertial Measurement Units based on a biomechanical model of the prosthetic lower limb. Averaged walking speed estimation has been quantified for nine individuals with transfemoral amputation walking on a treadmill at different speeds and slopes when wearing an instrumented knee ankle prosthesis. Experimental results demonstrated the ability of the model to estimate the walking speed with an accuracy of 9% (normalized root mean squared errors over all the patients), which is consistent with previous reported walking speed estimation errors. In addition, as the walking speed estimation is instantaneous, the proposed method can provide the estimation by the end of the stance phase, which is an originality compared to other methods based on step length estimation. The present method is relevant for the estimation of walking speed during real-life activities of above-knee amputees opening the way to direct activity monitoring from the prosthesis.