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Gait Posture. 2018 Jul;64:30-37. doi: 10.1016/j.gaitpost.2018.05.025. Epub 2018 May 22.

IMU-based gait analysis in lower limb prosthesis users: Comparison of step demarcation algorithms.

Author information

1
Department of Physical Medicine & Rehabilitation, Vanderbilt University Medical Center, United States. Electronic address: Gerasimos.Bastas@vanderbilt.edu.
2
Department of Mechanical Engineering, Vanderbilt University, United States.
3
Department of Electrical Engineering and Computer Science, Vanderbilt University, United States.
4
Department of Physical Medicine & Rehabilitation, Vanderbilt University Medical Center, United States; Department of Mechanical Engineering, Vanderbilt University, United States; Department of Biomedical Engineering, Vanderbilt University, United States.

Abstract

BACKGROUND:

Inertial Measurement Unit (IMU)-based gait analysis algorithms have previously been validated in healthy controls. However, little is known about the efficacy, performance, and applicability of these algorithms in clinical populations with gait deviations such as lower limb prosthesis users (LLPUs).

RESEARCH QUESTION:

To compare the performance of 3 different IMU-based algorithms to demarcate steps from LLPUs.

METHODS:

We used a single IMU sensor affixed to the midline lumbopelvic region of 17 transtibial (TTA), 16 transfemoral (TFA) LLPUs, and 14 healthy controls (HC). We collected acceleration and angular velocity data during overground walking trials. Step demarcation was evaluated based on fore-aft acceleration, detecting either: (i) maximum acceleration peak, (ii) zero-crossing, or (iii) the peak immediately preceding a zero-crossing. We quantified and compared the variability (standard deviation) in acceleration waveforms from superposed step intervals, and variability in step duration, by each algorithm.

RESULTS:

We found that the zero-crossing algorithm outperformed both peak detection algorithms in 65% of TTAs, 81% of TFAs, and 71% of HCs, as evidenced by lower standard deviations in acceleration, more consistent qualitative demarcation of steps, and more normally distributed step durations.

SIGNIFICANCE:

The choice of feature-based algorithm with which to partition IMU waveforms into individual steps can affect the quality and interpretation of estimated gait spatiotemporal metrics in LLPUs. We conclude that the fore-aft acceleration zero-crossing serves as a more reliable feature for demarcating steps in the gait patterns of LLPUs.

KEYWORDS:

Accelerometer; Amputation; Gait; Inertial measurement unit; Prosthesis

PMID:
29807270
PMCID:
PMC6062463
[Available on 2019-07-01]
DOI:
10.1016/j.gaitpost.2018.05.025
[Indexed for MEDLINE]

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