Estimation of spatio-temporal parameters of gait from magneto-inertial measurement units: multicenter validation among Parkinson, mildly cognitively impaired and healthy older adults

Abstract

BackgroundThe use of miniaturized magneto-inertial measurement units (MIMUs) allows for an objective evaluation of gait and a quantitative assessment of clinical outcomes. Spatial and temporal parameters are generally recognized as key metrics for characterizing gait. Although several methods for their estimate have been proposed, a thorough error analysis across different pathologies, multiple clinical centers and on large sample size is still missing. The aim of this study was to apply a previously presented method for the estimate of spatio-temporal parameters, named Trusted Events and Acceleration Direct and Reverse Integration along the direction of Progression (TEADRIP), on a large cohort (236 patients) including Parkinson, mildly cognitively impaired and healthy older adults collected in four clinical centers. Data were collected during straight-line gait, at normal and fast walking speed, by attaching two MIMUs just above the ankles. The parameters stride, step, stance and swing durations, as well as stride length and gait velocity, were estimated for each gait cycle. The TEADRIP performance was validated against data from an instrumented mat.ResultsLimits of agreements computed between the TEADRIP estimates and the reference values from the instrumented mat were − 27 to 27 ms for Stride Time, − 68 to 44 ms for Stance Time, − 31 to 31 ms for Step Time and − 67 to 52 mm for Stride Length. For each clinical center, the mean absolute errors averaged across subjects for the estimation of temporal parameters ranged between 1 and 4%, being on average less than 3% (< 30 ms). Stride length mean absolute errors were on average 2% (≈ 25 mm). Error comparisons across centers did not show any significant difference. Significant error differences were found exclusively for stride and step durations between healthy elderly and Parkinsonian subjects, and for the stride length between walking speeds.ConclusionsThe TEADRIP method was effectively validated on a large number of healthy and pathological subjects recorded in four different clinical centers. Results showed that the spatio-temporal parameters estimation errors were consistent with those previously found on smaller population samples in a single center. The combination of robustness and range of applicability suggests the use of the TEADRIP as a suitable MIMU-based method for gait spatio-temporal parameter estimate in the routine clinical use. The present paper was awarded the “SIAMOC Best Methodological Paper 2017”.

Design of a Machine Learning-Assisted Wearable Accelerometer-Based Automated System for Studying the Effect of Dopaminergic Medicine on Gait Characteristics of Parkinson’s Patients

“…Walking speed, stride length, and stride time have been given high importance by Schlachetzki et al [29] for the discrimination of healthy subjects from the PD subjects. Bertoli et al estimated the spatiotemporal parameters such as stride time, step time, swing time, stance time, stride length, and gait velocity for the quantitative assessment of PD, mild cognitive impairment patients, and healthy older adults [30]. e step time can be calculated based on the IC events [9] as follows:…”

A wearable solution for accurate step detection based on the direct measurement of the inter-foot distance

“…During the last decade, inertial measurement units (IMUs) have been increasingly used to measure human movement both in clinical settings and in free-living conditions [5] [6]. IMU-based step detection is obtained by recording accelerations and angular velocities from various body locations and by analysing the signals features using one of several methods proposed in the literature [1] [2] [4] [9] [13] [14]. However, the performance of IMU-based methods generally deteriorates when highly abnormal gait patterns are analysed, when walking aids are used and when walking at low speed [8] [10] [15].…”

Gait event detection using inertial measurement units in people with transfemoral amputation: a comparative study

“…However, in pathological gait, a robust detection of both IC and FC events is compromised because of gait inherent variability and stronger attenuation of feet-ground impacts at trunk level [9,16]. Consequently, algorithms based on the use of two IMUs located on both shanks [4,[17][18][19][20][21][22][23][24] or feet [24][25][26] have been developed and are generally considered to be more accurate [9,16,21].…”