The weak relationship between ankle proprioception and gait speed after stroke a robotic assessment study
<|reference_start|>The weak relationship between ankle proprioception and gait speed after stroke a robotic assessment study: Ankle proprioceptive deficits are common after stroke and occur independently of ankle motor impairments. Despite this independence, some studies have found that ankle proprioceptive deficits predict gait function, consistent with the concept that somatosensory input plays a key role in gait control. Other studies, however, have not found a relationship, possibly because of variability in proprioception assessments. Robotic assessments of proprioception offer improved consistency and sensitivity. Here we relationships between ankle proprioception, ankle motor impairment, and gait function after stroke using robotic assessments of ankle proprioception. We quantified ankle proprioception using two different robotic tests (Joint Position Reproduction and Crisscross) in 39 persons in the chronic phase of stroke. We analyzed the extent to which these robotic proprioception measures predicted gait speed, measured over a long distance (6-minute walk test) and a short distance (10-meter walk test). We also studied the relationship between robotic proprioception measures and lower extremity motor impairment, quantified with measures of ankle strength, active range of motion, and the lower extremity Fugl-Meyer exam. Impairment in ankle proprioception was present in 87% of the participants. Ankle proprioceptive acuity measured with JPR was weakly correlated with 6MWT gait speed (\r{ho} = -0.34, p = 0.039) but not 10mWT (\r{ho} = -0.29, p = 0.08). Ankle proprioceptive acuity was not correlated with lower extremity motor impairment (p > 0.2). These results confirm the presence of a weak relationship between ankle proprioception and gait after stroke that is independent of motor impairment.<|reference_end|>
@article{johnson2024the,
    title={The weak relationship between ankle proprioception and gait speed after
  stroke a robotic assessment study},
    author={Christopher A. Johnson, Piyashi Biswas, Rubi Tapia, Jill See, Lucy
  Dodakian, Vicky Chan, Po T. Wang, Zoran Nenadic, An H. Do, David J.
  Reinkensmeyer},
    journal={arXiv preprint arXiv:2402.11110},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.11110},
    primaryClass={cs.RO}
}