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Comparing the activity profiles of wheelchair rugby using a miniaturised data logger and radio-frequency tracking system.

Barry S MasonJohn LentonJames RhodesRory A CooperVictoria Goosey-Tolfrey
Published in: BioMed research international (2014)
The current study assessed the validity and reliability of a miniaturised data logger (MDL) against a radio-frequency-based indoor tracking system (ITS) for quantifying key aspects of mobility performance during wheelchair rugby. Eleven international wheelchair rugby players were monitored by both devices during four wheelchair rugby matches. MDL data were averaged over both 1-second (MDL-1) and 5-second (MDL-5) intervals to calculate distance, mean, and peak speeds. The results revealed no significant differences between devices for the distance covered or mean speeds, although random errors of 10% and 12%, respectively, were identified in relation to the mean values. No significant differences in peak speed were revealed between ITS (3.91 ± 0.32 m·s(-1)) and MDL-1 (3.85 ± 0.45 m·s(-1)). Whereas peak speeds in MDL-5 (2.75 ± 0.29 m·s(-1)) were significantly lower than ITS. Errors in peak speed led to large random errors in time and distance spent in speed zones relative to peak speed, especially in MDL-5. The current study revealed that MDL provide a reasonable representation of the distance and mean speed reported during wheelchair rugby. However, inaccuracy in the detection of peak speeds limits its use for monitoring performance and prescribing wheelchair rugby training programmes.
Keyphrases
  • electronic health record
  • adverse drug
  • big data
  • patient safety
  • primary care
  • neural network
  • artificial intelligence
  • health risk