Development of a step counting algorithm using the ambulatory tibia load analysis system for tibia fracture patients.

Area of Science:

• Biomechanics
• Orthopedics
• Rehabilitation Engineering

Background:

• Ambulation monitoring is crucial for lower extremity fracture healing.
• Continuous quantification of patient ambulation outside clinical settings is challenging.
• Tibia fracture patient ambulatory behavior during recovery is largely unknown.

Purpose of the Study:

• To design and validate an algorithm for assessing tibia fracture patient ambulation.
• To utilize the ambulatory tibial load analysis system for continuous, out-of-clinic monitoring.
• To understand ambulatory behavior patterns during the recovery phase.

Main Methods:

• Algorithm development and validation using simulated data.
• Testing with healthy volunteers during a 2-minute walk test on a treadmill.
• Deployment of the ambulatory tibial load analysis system with 10 tibia fracture patients during recovery.

Main Results:

• The algorithm achieved high accuracy in step detection (2000/2000 steps).
• Strong correlation (r² > 0.98) between algorithm-derived and actual step counts in healthy volunteers.
• Qualitative gait differences observed between early and late recovery stages in patients, with significant daily step count variability (≤3000 steps).

Conclusions:

• The developed algorithm effectively assesses ambulatory activity in tibia fracture patients.
• The system provides valuable insights into patient recovery and behavior outside the clinic.
• This technology can aid in monitoring fracture healing and tailoring rehabilitation strategies.