Real-time feedback to improve gait in children with cerebral palsy

Linda van Gelder, Adam T.C. Booth*, Ingrid van de Port, Annemieke I. Buizer, Jaap Harlaar, Marjolein van der Krogt

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

29 Citations (Scopus)


Real-time feedback may be useful for enhancing information gained from clinical gait analysis of children with cerebral palsy (CP). It may also be effective in functional gait training, however, it is not known if children with CP can adapt gait in response to real-time feedback of kinematic parameters. Sixteen children with cerebral palsy (age 6–16; GMFCS I–III), walking with a flexed-knee gait pattern, walked on an instrumented treadmill with virtual reality in three conditions: regular walking without feedback (NF), feedback on hip angle (FH) and feedback on knee angle (FK). Clinically relevant gait parameters were calculated and the gait profile score (GPS) was used as a measure of overall gait changes between conditions. All children, except one, were able to improve hip and/or knee extension during gait in response to feedback, with nine achieving a clinically relevant improvement. Peak hip extension improved significantly by 5.1 ± 5.9° (NF: 8.9 ± 12.8°, FH: 3.8 ± 10.4°, p = 0.01). Peak knee extension improved significantly by 7.7 ± 7.1° (NF: 22.2 ± 12.0°, FK: 14.5 ± 12.7°, p < 0.01). GPS did not change between conditions due to increased deviations in other gait parameters. Responders to feedback were shown to have worse initial gait as measured by GPS (p = 0.005) and functional selectivity score (p = 0.049). In conclusion, ambulatory children with CP show adaptability in gait and are able to respond to real-time feedback, resulting in significant and clinically relevant improvements in peak hip and knee extension. These findings show the potential of real-time feedback as a tool for functional gait training and advanced gait analysis in CP.

Original languageEnglish
Pages (from-to)76-82
JournalGait & Posture
Publication statusPublished - 2017
Externally publishedYes

Bibliographical note

Geen TU Delft-publicatie


  • Biofeedback
  • Clinical gait analysis
  • Gait training
  • Rehabilitation
  • Virtual reality


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