Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2012;12(5):6102-16.
doi: 10.3390/s120506102. Epub 2012 May 10.

Inertial sensor-based methods in walking speed estimation: a systematic review

Shuozhi Yang  1 , Qingguo Li
Affiliations

Inertial sensor-based methods in walking speed estimation: a systematic review

Shuozhi Yang et al. Sensors (Basel). 2012.

Abstract

Self-selected walking speed is an important measure of ambulation ability used in various clinical gait experiments. Inertial sensors, i.e., accelerometers and gyroscopes, have been gradually introduced to estimate walking speed. This research area has attracted a lot of attention for the past two decades, and the trend is continuing due to the improvement of performance and decrease in cost of the miniature inertial sensors. With the intention of understanding the state of the art of current development in this area, a systematic review on the exiting methods was done in the following electronic engines/databases: PubMed, ISI Web of Knowledge, SportDiscus and IEEE Xplore. Sixteen journal articles and papers in proceedings focusing on inertial sensor based walking speed estimation were fully reviewed. The existing methods were categorized by sensor specification, sensor attachment location, experimental design, and walking speed estimation algorithm.

Keywords: ambulatory; biomechanics; gait segmentation; inertial sensors; review; spatio-temporal parameters; walking speed.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Generic walking speed estimation method. (a). Inertial sensors (accelerometer and/or gyroscope) are attached to different parts of the user. (b). Inertial sensors measure the accelerations and/or angular velocities which contain information related to the walking speed. (c). A walking speed estimation algorithm extracts the walking speed information from these sensor measurements. (d). Different walking speed are distinguished as outputs of the algorithm.
Figure 2.
Figure 2.
Article review procedures. After the initial search, the title and abstract were reviewed first to exclude unrelated articles. The full articles were then retrieved and reviewed with the detailed inclusion/exclusion criteria. 16 articles were finally included in this review.
See this image and copyright information in PMC

References

    1. Cohen J., Sveen J., Walker J., Brummel-Smith K. Establishing criteria for community ambulation. Topics Geriatric Rehab. 1987;3:71–78.
    1. Richards C., Malouin F., Dumas F., Tardif D. Gait Analysis: Theory and Application. Mosby; St Louis, MO, USA: 1995. Gait velocity as an outcome measure of locomotor recovery after stroke; pp. 355–364.
    1. Schmid A., Duncan P., Studenski S., Lai S., Richards L., Perera S., Wu S. Improvements in speed-based gait classifications are meaningful. Stroke. 2007;38:2096–2100. - PubMed
    1. Mudge S., Stott N. Outcome measures to assess walking ability following stroke: A systematic review of the literature. Physiotherapy. 2007;93:189–200.
    1. Balasubramanian C., Bowden M., Neptune R., Kautz S. Relationship between step length asymmetry and walking performance in subjects with chronic hemiparesis. Arch. Phys. Med. Rehab. 2007;88:43–49. - PubMed

Publication types

LinkOut - more resources