# Low Back Exoskeletons in Industry 5.0: From Machines to Perceiving Co-Pilots—A State-of-the-Art Review

## TL;DR

This paper reviews back exoskeletons used in industry, focusing on how sensor technology can make them smarter and more adaptive for workers.

## Contribution

The paper introduces a structured design pipeline and highlights the limited integration of intelligent and adaptive features in current exoskeletons.

## Key findings

- Only 39.39% of exoskeletons support asymmetric activities, while kinematic compatibility remains a challenge.
- Just 33.33% of systems include intelligent features, with only one adapting to posture or real-time feedback.
- Advanced sensors and decision-making capabilities are underutilized, limiting adaptive support potential.

## Abstract

This manuscript presents an updated review of back exoskeletons for occupational use, with a particular focus on sensor technology as a key enabler for intelligent and adaptive support. The study aims to identify key barriers to adoption and explore design characteristics which align these systems with the Industry 5.0 paradigm, where machines function as collaborative co-pilots alongside humans. We propose a structured design pipeline and analyze 32 exoskeletons across multiple dimensions, including design, actuation, control strategies, sensor networks, and intelligence. Additionally, we review eight simulation environments which support the early stages of exoskeleton development. Special emphasis is placed on sensor technology, highlighting its critical role in enhancing adaptability and intelligence. Our findings reveal that while 39.39% of exoskeletons accommodate asymmetric activities, kinematic compatibility remains a challenge. Furthermore, only 33.33% of the systems incorporated intelligent features, with just one being capable of adapting its response based on poor posture or real-time human–machine interaction feedback. The limited integration of advanced sensors and decision-making capabilities constrains their potential for dynamic and adaptive support. Open questions remain in high-level decision making, enhanced environmental awareness, and the development of generalizable methods for integrating sensor data into adaptive control strategies.