Walking speed estimation using shank-mounted accelerometers

Abstract

We studied the feasibility of estimating walking speed using two shank-mounted accelerometers. Our approach took advantage of the inverted pendulum-like behavior of the stance leg during walking to identify a new method for dividing up walking into individual stride cycles and estimating the initial conditions for the direct integration of the accelerometer signals. To test its accuracy, we compared speed to known values during treadmill walking. The speed estimation method worked well across treadmill speeds yielding a root mean square speed estimation error of only 8%. This accuracy is comparable to that achieved from shank-mounted inertial measurement unit, providing a robust and low-cost alternative in using accelerometer for walking speed estimation. Shank-mounted accelerometer may be of great benefit for estimating speed in walking for the embedded control of knee-mounted devices such as prostheses and energy harvesters.

A Review on Accelerometry-Based Gait Analysis and Emerging Clinical Applications

“…Based on the results, the hypothesis that the IP model accounts for the displacement during single stance phase has been supported. In [149] the inverted pendulum-like behavior of the stance leg during walking has been used to identify individual stride cycles using the direct integration of the accelerometer signals. It shows that two-shank mounted accelerometers are useful to estimate walking speed which are validated using treadmill information.…”

A Kinematic Human-Walking Model for the Normal-Gait-Speed Estimation Using Tri-Axial Acceleration Signals at Waist Location

“…Using the homogeneous coordinate representation, the location of the COM relative to the virtual center G can be derived as Taking the time derivatives of (14) and assuming thatβ ≈ 0 andγ ≈ 0, the COM velocity V COM and acceleration A COM can be computed as…”

“…Very few works consider the characteristics of the modelbased kinematic walking models to estimate walking speed. Bishop and Li [14] used two shank-mounted accelerometers to take advantage of the inverted pendulum-like behavior of the stance phase to estimate the walking speed. For biped walking, the inverted pendulum model is the simplest one for analysis of the kinematics or energy-spending sequences.…”

Multi-modal gait: A wearable, algorithm and data fusion approach for clinical and free-living assessment

“…Additionally, spatial parameters (e.g. step length) are derived through additional modelling of inertial data [22,23]. Those technical developments have enabled novel clinical studies to examine neurological gait in greater detail within a laboratory and free-living environments [24][25][26][27][28].…”