Author(s):
Francisco P. M. Oliveira 
; João Manuel R. S. Tavares
Date: 2013
Persistent ID: http://hdl.handle.net/10216/65780
Origin: Repositório Aberto da Universidade do Porto
Subject(s): Ciências Tecnológicas
Document details
Automated spatio-temporal alignment of plantar pressure image sequences
Description
The analysis of plantar pressure data provides information on the role of the foot and ankle during gait and other activities. The information gather can be used to define suitable rehabilitation programs through alterations of footwear, foot orthoses, exercise programs and weight-bearing restrictions. It can also assist the diagnosis and rehabilitation of impairments associated with various musculoskeletal, integumentary and neurological disorders. Particularly, it has a vital role in the assessment and prevention of ulceration of patients with diabetes and peripheral neuropathy. Generally, the plantar pressure data can be converted into a discrete rectangular array at a point in time or over a period of time, giving rising to static images or to image sequences. The number of trials required to obtain reliable representations of the plantar pressure pattern is an important factor in dynamic data acquisition: three to five walking trials enhances the reliability of the pressure measurements [1]. Hence, the automatically spatio-temporal, i.e. simultaneously in time and space, alignment of sequence trials is important to build a representative plantar image sequence for the subject under study, as it is more reliable than a single trial and supports comparisons among plantar pressure image sequences on a pixel-by-pixel basis. Here, the use of automated computational method for the spatio-temporal alignment of plantar pressure image sequences [2-3] is discussed. Using the method, the spatial position and orientation of a foot in an image sequence are changed to match the foot represented in a second sequence, and simultaneously the temporal scale of the first sequence is transformed with the aim of synchronizing the two input sequences. As such, the spatial correspondence of the foot regions along the sequences as well as the temporal synchronizing is obtained.
The analysis of plantar pressure data provides information on the role of the foot and ankle during gait and other activities. The information gather can be used to define suitable rehabilitation programs through alterations of footwear, foot orthoses, exercise programs and weight-bearing restrictions. It can also assist the diagnosis and rehabilitation of impairments associated with various musculoskeletal, integumentary and neurological disorders. Particularly, it has a vital role in the assessment and prevention of ulceration of patients with diabetes and peripheral neuropathy. Generally, the plantar pressure data can be converted into a discrete rectangular array at a point in time or over a period of time, giving rising to static images or to image sequences. The number of trials required to obtain reliable representations of the plantar pressure pattern is an important factor in dynamic data acquisition: three to five walking trials enhances the reliability of the pressure measurements [1]. Hence, the automatically spatio-temporal, i.e. simultaneously in time and space, alignment of sequence trials is important to build a representative plantar image sequence for the subject under study, as it is more reliable than a single trial and supports comparisons among plantar pressure image sequences on a pixel-by-pixel basis. Here, the use of automated computational method for the spatio-temporal alignment of plantar pressure image sequences [2-3] is discussed. Using the method, the spatial position and orientation of a foot in an image sequence are changed to match the foot represented in a second sequence, and simultaneously the temporal scale of the first sequence is transformed with the aim of synchronizing the two input sequences. As such, the spatial correspondence of the foot regions along the sequences as well as the temporal synchronizing is obtained.
Document Type
Conference Object
Language English
Language English
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