Gait Analysis Literature Notes

Reviews of Gait Event/Phase Detection Methods

Strategy1 & Yield

Search Strategy

  • Scopus, Google Scholar, and PubMed databases were used to perform a literature search on the topic of gait phase partitioning.

  • The electronic search was conducted in September 2015.

  • Keywords included: gait events, gait phases, and their combinations with the words: partitioning, detection, classification, and recognition. In addition, wildcard symbols, such as hyphens or inverted commas, were used to consider all possible variations of root words.

  • To avoid missing some important studies, a cross referencing was applied from each article found during electronic search. A literature search was performed by Taborri.

Inclusion Criteria

  • Articles obtained thorough these searches were evaluated using the title and abstract. The articles were included in this systematic review when they met the following criteria: (i) they were written in English; (ii) they were published from January 2000 to September 2015. We excluded conference proceedings when a journal article published by the same authors with the same contents was already included.

Data Extraction

  • Publications included in this systematic review were downloaded into Mendeley for screening. In order to make the review readable and focused on the authors’ intention, as claimed in the Introduction section, a data extraction was conducted based on major themes: (i) the granularity of the gait cycle ; (ii) sensor placement; and, (iii) method and performance of gait phase classifications.

Quality Assessment

  • A quality assessment of the found articles was provided in addition to the systematic review; in particular, publications were subject to seven criteria, as shown in Table 1, in accordance to Campos and colleagues [84]. Independently, Taborri, Palermo and Rossi used the seven criteria to assess the quality of the publications. Any discrepancy among two reports was adjudicated by the third one.

gait event detection

检索关键词: gait event detection，限定2015及以后123456

Wearable sensor-based real-time gait detection: A systematic review

Rueterbories et al. [26] Review of sensor configurations and placements, and a brief review of gait detection methods

Perez-Ibarra et al. [27] Brief review comparing gait event detection methods, sensors used, placement of sensors and subjects involved

Panebianco et al. [18] Rule-based methods

gait phase detection

检索Author Keywords “gait phase detection”

event detection

检索Author Keywords “event detection”

gait event detection

检索Author Keywords “gait event detection”

Gait events & phases

见"J. Perry, J.M. Burnfield, Gait Analysis: Normal and Pathological Function(2nd ed.), SLACK Incorporated (2010)“以及"Michael W. Whittle, An Introduction to Gait Analysis, 4th Ed. (2007)” （之前的笔记）

此外，一些工作里有不同的划分方式

image-20210813200345964

  1. Taborri, J., Palermo, E., Rossi, S., & Cappa, P. (2016). Gait partitioning methods: A systematic review. Sensors (Switzerland), 16(1). https://doi.org/10.3390/s16010066 ↩︎

  2. Caldas, R., Mundt, M., Potthast, W., Buarque de Lima Neto, F., & Markert, B. (2017). A systematic review of gait analysis methods based on inertial sensors and adaptive algorithms. Gait and Posture, 57, 204–210. https://doi.org/10.1016/j.gaitpost.2017.06.019 ↩︎

  3. Pacini Panebianco, G., Bisi, M. C., Stagni, R., & Fantozzi, S. (2018). Analysis of the performance of 17 algorithms from a systematic review: Influence of sensor position, analysed variable and computational approach in gait timing estimation from IMU measurements. Gait and Posture, 66, 76–82. https://doi.org/10.1016/j.gaitpost.2018.08.025B ↩︎

  4. enson, L. C., Clermont, C. A., Bošnjak, E., & Ferber, R. (2018). The use of wearable devices for walking and running gait analysis outside of the lab: A systematic review. Gait & Posture, 63, 124–138. https://doi.org/10.1016/J.GAITPOST.2018.04.047P ↩︎

  5. rasanth, H., Caban, M., Keller, U., Courtine, G., Ijspeert, A., Vallery, H., & von Zitzewitz, J. (2021). Wearable sensor-based real-time gait detection: A systematic review. Sensors, 21(8). https://doi.org/10.3390/s21082727 ↩︎

  6. Celik, Y., Stuart, S., Woo, W. L., & Godfrey, A. (2021). Gait analysis in neurological populations: Progression in the use of wearables. Medical Engineering & Physics, 87, 9–29. https://doi.org/10.1016/J.MEDENGPHY.2020.11.005 ↩︎