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Pręgowska A., Pauk K.♦, Tutak J.♦, Pauk J.♦, Benchmarking implicit neural representations of pediatric gait waveforms against conventional biomechanical descriptors,
Biomedical Signal Processing and Control, ISSN: 1746-8094, DOI: 10.1016/j.bspc.2026.111450, Vol.129, No.111450, pp.1-17, 2027 Streszczenie:
Machine-learning representations of gait waveforms are increasingly used in movement analysis, but their added value over conventional biomechanical descriptors remains uncertain, particularly in pediatric cohorts. We evaluated whether implicit neural representations (INRs) provide useful encodings of pediatric gait waveforms for reconstruction and developmental modeling. The full cohort comprised 78 healthy children
and adolescents, of whom 73 had waveform files conforming to the predefined data structure required for the repeated cross-validation analyses. Selected waveforms were modeled using several INR architectures, and reconstruction quality was assessed using Słowa kluczowe:
Pediatric gait, Biomechanics, Waveform analysis, Implicit neural representations, Movement development, Gait analysis Afiliacje autorów:
| Pręgowska A. | - | IPPT PAN | | Pauk K. | - | inna afiliacja | | Tutak J. | - | inna afiliacja | | Pauk J. | - | inna afiliacja |
|  | 140p. |
