Motion envelopes: unfolding longitudinal rotation data from walking stick-figures.

Ivo F RoupaSérgio B GonçalvesMiguel Tavares da SilvaRichard R NeptuneDaniel Simões Lopes

Published in: Computer methods in biomechanics and biomedical engineering (2021)

This work presents Motion Envelopes (ME), a simple method to estimate the missing longitudinal rotations of minimal stick figures, which is based on the spatial-temporal surface traced by line segments that connect contiguous pairs of joints. We validate ME by analyzing the gait patterns of 6 healthy subjects, comprising a total of 18 gait cycles. A strong correlation between experimental and estimated data was obtained for lower limbs and upper arms, indicating that ME can predict their longitudinal orientation in normal gait, hence, ME can be used to complement the kinematic information of stick figures whenever it is incomplete.

Keyphrases

cross sectional
cerebral palsy
electronic health record
big data
high speed
mass spectrometry
data analysis
social media
lower limb
artificial intelligence