A versatile knee exoskeleton mitigates quadriceps fatigue in lifting, lowering, and carrying tasks

The quadriceps are particularly susceptible to fatigue during repetitive lifting-lowering and carrying (LLC), affecting worker performance, posture, and ultimately lower-back injury risk. Although robotic exoskeletons have been developed and optimized for specific use cases like lifting-lowering, their controllers lack the versatility or customizability to target critical muscles across many fatiguing tasks. Here we present a task-adaptive knee exoskeleton controller that automatically modulates virtual springs, dampers, and gravity and inertia compensation to assist squatting, level walking, and ramp and stairs ascent/descent. Unlike end-to-end neural networks, the controller is composed of predictable, bounded components with interpretable parameters that are amenable to both data-driven optimization for biomimetic assistance and subsequent application-specific tuning, for example, maximizing quadriceps assistance over multi-terrain LLC. When deployed on a backdrivable knee exoskeleto..., Data collected from 10 able-bodied participants performing non-fatiguing (S1) and fatiguing (S2) lifting-lowering-carrying (LLC) tasks with and without a bilateral knee exoskeleton. dataset_S1 consists of electromyography, kinematics, torque, and footsensor data from non-fatiguing LLC tasks. dataset_S2 consists time, posture, and perceptual measurements from fatiguing squat lifting-lowering and carying tasks., Matlab or Octave (Open Source), # A Versatile Knee Exoskeleton Mitigates Quadriceps Fatigue in Lifting, Lowering, and Carrying Tasks

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Data collected from 10 able-bodied participants performing fatiguing (S1) and non-fatiguing (S2) lifting-lowering-carrying (LLC) tasks with (exo condition) and without (bare condition) a bilateral knee exoskeleton. LLC tasks consist of squat lifting-lowering (LL), ramp ascent (RA), ramp descent (RD), stairs ascent (SA), stairs descent (SD), and level walking (LW). Ramp incline is 15 degrees and step height of stairs is 7 inches. dataset_S1 consists performance and posture measurements from fatiguing squat LL, and perceptual measurements from fatigued LLC tasks. dataset_S2 consists of electromyography, kinematics, torque, and foot sensor data from non-fatiguing LLC tasks.

## Description of the Data and file structure

dataset_S1.mat contains 2 structures: 1) *emg* 2) *exo*.

1. *emg* is organized as emg.muscle.condition.task.measure, where the sub-structures are as follows. muscle:...