ArticleFrontiers in digital health2024
The walking surface influences vertical ground reaction force and centre of pressure data obtained with pressure-sensing insoles.
Article in Frontiers in digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Timed Up-and-Go Test Using Instrumented Insoles to Monitor Tibial or Malleolar Fracture Healing in Patients With Healing Fractures or Nonunion: Longitudinal and Cross-Sectional Exploratory Study.JMIR mHealth and uHealth · 2026Article
- Differences Between Tibial or Malleolar Fracture Types and Union or Nonunion in Spatiotemporal and Kinematic Gait Parameters Throughout Healing: An Observational Study.Annals of biomedical engineering · 2026Observational
- Effects of Soft Ground on Paw Center of Pressure Metrics in Dogs During Walk and Trot.Animals : an open access journal from MDPI · 2026Article
- Outdoor Walking Classification Based on Inertial Measurement Unit and Foot Pressure Sensor Data.Sensors (Basel, Switzerland) · 2025Article
- Characteristics of Ground Reaction Force Variability During Walking in Post-Stroke Patients.Sensors (Basel, Switzerland) · 2025Article
- Recovery of Patient-Reported Outcome Measures vs Gait Parameters Obtained by Instrumented Insoles After Tibial and Malleolar Fractures: Prospective Longitudinal Observational Study.JMIR mHealth and uHealth · 2025Observational
- Gait analysis with smart insoles can identify patients at risk of tibial shaft fracture nonunion as early as six weeks after surgery: longitudinal and cross-sectional study.Frontiers in bioengineering and biotechnology · 2025Article
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6 authors.
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Abstract
Background: Gait can be continuously monitored via vertical ground reaction force (VGRF) and centre of pressure (COP) measurement with pressure-sensing insoles. During daily living, a variety of walking surfaces will be encountered, which could affect the collected data. These effects might need to be taken into account when analysing disease- or injury-related gait characteristics to prevent misinterpretation, especially when drawing conclusions from data obtained in clinical populations. We hypothesized characteristic changes in insole-derived VGRF and COP parameters of healthy participants when walking on different surfaces. Methods: Participants walked on flat indoor surface, flat and inclined outdoor surfaces, as well as on forest, gravel, grass, and sand surfaces while wearing pressure-sensing insoles with 16 pressure sensors each at a recording frequency of 100 Hz. Several gait parameters were extracted from the VGRF and COP data, and were compared between surfaces using repeated measures ANOVA. Results: Thirty participants were included (22 women and 7 men, age 30 ± 12 years, height 172 ± 8 cm, weight 76 ± 23 kg). VGRF and COP data were significantly influenced by the type of surface. The rmANOVA revealed significant within-subject differences between the walking surfaces in all calculated parameters. The largest changes in the VGRF and COP patterns occurred during uphill and downhill walking. Walking on compliant surfaces led to increased gait variability. The highest variability was observed when walking on sand. The change from walking indoors to outdoors, be it on flat, inclined, forest, gravel, grass or sand surfaces, was characterized by a characteristic change in the VGRF stance-phase curve. Based on these characteristic changes, it could be possible to identify whether someone is walking on a slope, as well as on non-compliant or compliant surfaces, while it is difficult to distinguish between different types of compliant surfaces. Conclusion: VGRF data are affected by the type of walking surface in healthy adults. Walking on a slope affects VGRF and COP parameters, and in addition, the compliance of the surface increases their variability. When analysing gait data measured via insoles during daily living, we recommend to correct for the surface type to decrease variability.
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