A toolbox for the identification of foot-floor contact sequences to analyze atypical gait cycles in a real-life scenario: application on patients after proximal femur fracture and healthy elderly
The detection of gait subphases is pivotal for a comprehensive assessment of gait quality, playing a key role in different applications such as rehabilitation programs, movement disorder diagnostics, and fall prevention strategies. However, few methods provide dynamic subphase segmentation relying s...
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| Main Authors: | , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
14 July 2025
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| In: |
Journal of neuroEngineering and rehabilitation
Year: 2025, Volume: 22, Pages: 1-11 |
| ISSN: | 1743-0003 |
| DOI: | 10.1186/s12984-025-01683-z |
| Online Access: | Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s12984-025-01683-z
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| Author Notes: | Marco Ghislieri, Nicolas Leo, Marco Caruso, Clemens Becker, Andrea Cereatti and Valentina Agostini |
| Summary: | The detection of gait subphases is pivotal for a comprehensive assessment of gait quality, playing a key role in different applications such as rehabilitation programs, movement disorder diagnostics, and fall prevention strategies. However, few methods provide dynamic subphase segmentation relying solely on plantar pressure signals in real-life, unsupervised conditions. This work aims to present an open-source, flexible toolbox for the automatic detection of gait subphases, and to introduce novel digital gait biomarkers derived from subphase analysis, enabling effective monitoring of frail patients in real-world, challenging environments. |
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| Item Description: | Gesehen am 14.11.2025 |
| Physical Description: | Online Resource |
| ISSN: | 1743-0003 |
| DOI: | 10.1186/s12984-025-01683-z |