Human-in-the-Loop Optimization of Wearable Robotic Devices to Improve Human–Robot Interaction: A Systematic Review

This article presents a systematic review on wearable robotic devices that use human-in-the-loop optimization (HILO) strategies to improve human–robot interaction. A total of 46 HILO studies were identified and divided into upper and lower limb robotic devices. The main aspects from HILO were identified, reviewed, and classified in four areas: 1) human–machine systems; 2) optimization methods; 3) control strategies; and 4) experimental protocols. A variety of objective functions (physiological, biomechanical, and subjective), optimization strategies, and optimized control parameters configurations used in different control strategies are presented and analyzed. An overview of experimental protocols is provided, including metrics, tasks, and conditions tested. Moreover, the relevance given to training or adaptation periods was explored. We outline an HILO framework that includes current wearable robots, optimization strategies, objective functions, control strategies, and experimental protocols. We conclude by highlighting current research gaps and defining future directions to improve the development of advanced HILO strategies in upper and lower limb wearable robots.

I. Introduction

Wearable robotic devices have received a lot of attention in the last decade because of their high potential to assist human movement, both in medical and occupational settings. Most common robotic devices are passive, which translates into fixed assistive properties, lack of real-time adaptation, and inability to provide net energy [1], which is relevant in activities where energy needs to be compensated due to energy losses (e.g., energy lost in the form of body heat). These devices do not optimally cooperate with humans because the system cannot respond to human changes, neglecting the user’s functional performance and their experience [2]. Therefore, the interest in active autonomous systems and robots that use powered actuators to generate assistance and synchronize robot action with the user’s motion [3] is rapidly increasing. These types of robotic devices respond to a physiological, biomechanical, or subjective state of the user [4], [5], a state that the user is not always aware of [6].