Gait symmetry methods: Comparison of waveform-based Methods and recommendation for useVisa övriga samt affilieringar
2020 (Engelska)Ingår i: Biomedical Signal Processing and Control, ISSN 1746-8094, E-ISSN 1746-8108, Vol. 55, artikel-id 101643Artikel i tidskrift (Refereegranskat) Published
Abstract [en]
Gait symmetry has been shown to be a relevant measure for differentiating between normal and pathological gait. Although a number of symmetry methods exist, it is not clear which of these methods should be used as they have been developed using data collected from varying experimental protocols. This paper presents a comparison of state-of-the-art waveform-based symmetry methods and tests them on walking data collected from different environments. Acceleration signals collected from the ankle are used to analyse symmetry methods under different signal circumstances, such as phase shift, waveform shape difference, signal length (i.e. number of gait cycles) and gait initiation phase. The cyclogram based method is invariant to signal phase shifts, signal length and the gait initiation phase. The trend symmetry method is not affected by signal scaling and the gait initiation phase but is affected by signal length depending on the environment. Similar to the trend method, the cross-correlation symmetry method is not responsive to signal scaling and the gait initiation phase. The results of the symbolic method are not influenced by signal scaling, gait initiation and depending on the environment by the signal phase shift. From the results of the performed analysis, we recommend the trend method to gait symmetry assessment. The comparison of waveform-based symmetry methods brings new knowledge that will help in selecting an appropriate method for gait symmetry assessment under different experimental protocols. © 2019 Elsevier Ltd. All rights reserved.
Ort, förlag, år, upplaga, sidor
Amsterdam: Elsevier, 2020. Vol. 55, artikel-id 101643
Nyckelord [en]
Gait symmetry, Trend method, Cyclogram, Symbolic method, Cross-Correlation
Nationell ämneskategori
Signalbehandling
Identifikatorer
URN: urn:nbn:se:hh:diva-40497DOI: 10.1016/j.bspc.2019.101643ISI: 000502893200017Scopus ID: 2-s2.0-85071544741OAI: oai:DiVA.org:hh-40497DiVA, id: diva2:1348405
Anmärkning
Funding: The Czech Health Research Council (Czech Republic), Grant no. 16-28119a, “Analysis of movement disorders for the study of extrapyramidal diseases mechanism using motion capture camera systems”.
2019-09-042019-09-042020-05-08Bibliografiskt granskad