Journal
COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING
Volume 24, Issue 3, Pages 299-307Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/10255842.2020.1828375
Keywords
Ensemble feature selection; classification; surface topography; spine; motion; gender
Funding
- BMBF [16SV7115, 03IHS075B]
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This study introduces a method to capture the potential of biomechanical data and demonstrates good results in gender classification. Dynamic movements of the lumbar spine and pelvis are found to best map gender differences.
Modern technologies enable to capture multiple biomechanical parameters often resulting in relational data. The current work proposes a generally applicable method comprising automated feature extraction, ensemble feature selection and classification to best capture the potentials of the data also for generating new biomechanical knowledge. Its benefits are demonstrated in the concrete biomechanically and medically relevant use case of gender classification based on spinal data for stance and gait. Very good results for accuracy were obtained using gait data. Dynamic movements of the lumbar spine in sagittal and frontal plane and of the pelvis in frontal plane best map gender differences.
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