Application of wearable sensors for human gait analysis using fuzzy computational algorithm

The authors have developed and tested a wearable inertial sensor system for the acquisition of gait features. The sensors were placed on anatomical segments of the lower limb: foot, shank, thigh, and hip, and the motion data were then captured in conjunction with 3D ground reaction forces (GRFs). Th...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Engineering applications of artificial intelligence Jg. 24; H. 6; S. 1018 - 1025
Hauptverfasser: Alaqtash, Murad, Yu, Huiying, Brower, Richard, Abdelgawad, Amr, Sarkodie-Gyan, Thompson
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.09.2011
Schlagworte:
Algorithms
Fuzzy
Fuzzy computational algorithm
Fuzzy logic
Fuzzy set theory
Gait
Ground reaction forces (GRFs)
Human locomotion
Inertial sensor
Mathematical models
Sensors
Similarity
Human locomotion
Inertial sensor
Ground reaction forces (GRFs)
Fuzzy computational algorithm
ISSN:0952-1976, 1873-6769
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The authors have developed and tested a wearable inertial sensor system for the acquisition of gait features. The sensors were placed on anatomical segments of the lower limb: foot, shank, thigh, and hip, and the motion data were then captured in conjunction with 3D ground reaction forces (GRFs). The method of relational matrix was applied to develop a rule-based system, an intelligent fuzzy computational algorithm. The rule-based system provides a feature matrix model representing the strength of association or interaction amongst the elements of the gait functions (limb-segments accelerations and GRFs) throughout the gait cycle. A comparison between the reference rule-based data and an input test data was evaluated using a fuzzy similarity algorithm. This system was tested and evaluated using two subject groups: 10 healthy subjects were recruited to establish the reference fuzzy rule-base, and 4 relapsing remitting multiple sclerosis subjects were used as an input test data; and the grade of similarity between them was evaluated. This similarity provides a quantitative assessment of mobility state of the impaired subject. This algorithmic tool may be helpful to the clinician in the identification of pathological gait impairments, prescribe treatment, and assess the improvements in response to therapeutic intervention.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0952-1976
1873-6769
DOI:10.1016/j.engappai.2011.04.010