Preliminary training volume and progression algorithm to tackle fragility fracture risk during exoskeleton-assisted overground walking in individuals with a chronic spinal cord injury

Individuals with spinal cord injuries often have reduced bone density, leading to a higher risk of fractures. Exoskeletons can help with weight-bearing, which strengthens bones. However, there's a risk of fractures during exoskeleton use. This paper introduces an algorithm based on bone mineral density to reduce the risk of fractures during exoskeleton-assisted walking for people with spinal cord injuries. The algorithm classifies individuals based on bone density (osteoporotic, osteopenic, or preserved) and assigns them to slow, moderate, or fast-progression walking programs. The walking programs gradually increase in frequency and duration over 16 weeks, aiming to balance the benefits of weight-bearing with the risk of fractures. The frequency of training sessions increases from 1 to 3 times per week over an initial period of 16 weeks, fragmented into distinct phases.

• 1
  The developed algorithm classifies individuals into osteoporotic, osteopenic, and preserved bone mineral density profiles, assigning them to corresponding slow, moderate, and fast progression exoskeleton-assisted walking programs.
• 2
  The training programs increase in frequency and number of steps, from 1 to 3 times per week over an initial period of 16 weeks.
• 3
  Clinical experience suggests the algorithm is feasible, particularly for paraplegic participants, with no fractures reported in the study sample.
• 4
  This early-stage algorithm has limitations, some of which are discussed hereunder, that warrant further reflection and discussion among rehabilitation experts in an effort to refine it.