The Determination of Assistance-as-Needed Support by an Ankle-Foot Orthosis for Patients with Foot Drop

Int J Environ Res Public Health. 2023 Aug 30;20(17):6687. doi: 10.3390/ijerph20176687.

Abstract

Patients who suffer from foot drop have impaired gait pattern functions and a higher risk of stumbling and falling. Therefore, they are usually treated with an assistive device, a so-called ankle-foot orthosis. The support of the orthosis should be in accordance with the motor requirements of the patient and should only be provided when needed, which is referred to as assistance-as-needed. Thus, in this publication, an approach is presented to determine the assistance-as-needed support using musculoskeletal human models. Based on motion capture recordings of multiple subjects performing gaits at different speeds, a parameter study varying the optimal force of a reserve actuator representing the ankle-foot orthosis added in the musculoskeletal simulation is conducted. The results show the dependency of the simulation results on the selected optimal force of the reserve actuator but with a possible identification of the assistance-as-needed support required from the ankle-foot orthosis. The required increase in support due to the increasing severity of foot drop is especially demonstrated with the approach. With this approach, information for the required support of individual subjects can be gathered, which can further be used to derive the design of an ankle-foot orthosis that optimally assists the subjects.

Keywords: ankle–foot orthosis; design for medical devices; digital human models; foot drop; gait assistance; muscle weakness; musculoskeletal simulation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Ankle
  • Braces
  • Foot Orthoses*
  • Humans
  • Patients
  • Peroneal Neuropathies*

Grants and funding

This work was (partly) supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Grant WA 2913/43-1 and MI 2608/2-1. This work was (partly) supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Grant SFB 1483–Project-ID 442419336, EmpkinS.