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11
Automatic Linguistic Report on the Quality
of the Gait of a Person
Alberto Alvarez-Alvarez and Gracian Triviño
Abstract.
Gait analysis has been explored thoroughly during the last decade as
a behavioral biometric measurement. Some areas of application include: access
control, surveillance, activity monitoring and clinical analysis. Our work aims to
contribute to the field of human gait modeling by providing a solution based on
the computational theory of perceptions. Our model differs significantly from oth-
ers, e.g., based on machine learning techniques, because we use a linguistic model
to represent the subjective designer's perceptions of the human gait process. This
model is easily understood and provides good results. Using accelerometers in-
cluded in a smart phone, we propose a method for producing a linguistic report
about the quality of the gait in terms of homogeneity and symmetry. This type of
reports could be used to analyze the evolution of the human gait after a recovery
treatment and also for preventing falls in elderly people.
11.1
Introduction
Human gait is a quasi-periodic phenomenon which is defined as the interval between
two successive events of the same foot. Its analysis has been explored thoroughly
during the last decade as a behavioral biometric measurement. Some areas of appli-
cation include: access control, surveillance, activity monitoring and clinical anal-
ysis. Moreover, since the gait is a complex integrated task which requires precise
coordination of the mental and musculoskeletal system, its analysis can help in the
diagnosis and treatment of walking and moving disorders, identification of balance
factors and assessment of clinical gait interventions and rehabilitation programs.
Our work aims to contribute to the field of human gait modeling by providing a
solution based on the computational theory of perceptions. Our model differs sig-
nificantly from others, e.g., based on machine learning techniques, because we use
a linguistic model to represent the subjective designer's perceptions of the human
gait process. This model is easily understood and provides good results. Using
accelerometers included in a smart phone, we propose a method for producing a
