# Toward model-based individualized fitting of hip-flexion exosuits for persons with unilateral transfemoral amputation

## TL;DR

This paper explores how hip-flexion exosuits can help people with transfemoral amputations walk more comfortably by using personalized models to optimize device configurations.

## Contribution

The study introduces a model-based approach for individualized hip-flexion exosuit fitting for transfemoral amputees using subject-specific simulations and optimization.

## Key findings

- Optimal exosuit configurations varied significantly across individuals.
- Mobility group classification did not consistently reduce configuration variability.
- User-specific design is essential for effective exosuit performance.

## Abstract

The muscular restructuring and loss of function that occurs during a transfemoral amputation surgery has a great impact on the gait and mobility of the individual. The hip of the residual limb adopts a number of functional roles that would previously be controlled by lower joints. In the absence of active plantar flexors, swing initiation must be achieved through an increased hip flexion moment. The high activity of the residual limb is a major contributor to the discomfort and fatigue experienced by individuals with transfemoral amputations during walking. In other patient populations, both passive and active hip exosuits have been shown to positively affect gait mechanics. We believe an exosuit configured to aid with hip flexion could be well applied to individuals with transfemoral amputation. In this article, we model the effects of such a device during whole-body, subject-specific kinematic simulations of level ground walking. The device is simulated for 18 individuals of K2 and K3 Medicare functional classification levels. A user-specific device profile is generated via a three-axis moment-matching optimization using an interior-point algorithm. We employ two related cost functions that reflect an active and passive form of the device. We hypothesized that the optimal device configuration would be highly variable across subjects but that variance within mobility groups would be lower. From the results, we partially accept this hypothesis, as some parameters had high variance across subjects. However, variance did not consistently trend down when dividing into mobility groups, highlighting the need for user-specific design.