Low Back Exoskeletons in Industry 5.0: From Machines to Perceiving Co-Pilots—A State-of-the-Art Review
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 w...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/7/1958 |
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| author | Andrea Dal Prete Marta Gandolla Giuseppe Andreoni Francesco Braghin |
| author_facet | Andrea Dal Prete Marta Gandolla Giuseppe Andreoni Francesco Braghin |
| author_sort | Andrea Dal Prete |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-b55df2d5fd8e4ce4afd59bf73268a921 |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-b55df2d5fd8e4ce4afd59bf73268a9212025-08-20T03:08:56ZengMDPI AGSensors1424-82202025-03-01257195810.3390/s25071958Low Back Exoskeletons in Industry 5.0: From Machines to Perceiving Co-Pilots—A State-of-the-Art ReviewAndrea Dal Prete0Marta Gandolla1Giuseppe Andreoni2Francesco Braghin3Mechanical Engineering Department, Politecnico di Milano, Via Giuseppe La Masa 1, 20156 Milan, ItalyMechanical Engineering Department, Politecnico di Milano, Via Giuseppe La Masa 1, 20156 Milan, ItalyMechanical Engineering Department, Politecnico di Milano, Via Giuseppe La Masa 1, 20156 Milan, ItalyMechanical Engineering Department, Politecnico di Milano, Via Giuseppe La Masa 1, 20156 Milan, ItalyThis 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.https://www.mdpi.com/1424-8220/25/7/1958back exoskeletonlower-back painintelligent frameworkwearable technology |
| spellingShingle | Andrea Dal Prete Marta Gandolla Giuseppe Andreoni Francesco Braghin Low Back Exoskeletons in Industry 5.0: From Machines to Perceiving Co-Pilots—A State-of-the-Art Review Sensors back exoskeleton lower-back pain intelligent framework wearable technology |
| title | Low Back Exoskeletons in Industry 5.0: From Machines to Perceiving Co-Pilots—A State-of-the-Art Review |
| title_full | Low Back Exoskeletons in Industry 5.0: From Machines to Perceiving Co-Pilots—A State-of-the-Art Review |
| title_fullStr | Low Back Exoskeletons in Industry 5.0: From Machines to Perceiving Co-Pilots—A State-of-the-Art Review |
| title_full_unstemmed | Low Back Exoskeletons in Industry 5.0: From Machines to Perceiving Co-Pilots—A State-of-the-Art Review |
| title_short | Low Back Exoskeletons in Industry 5.0: From Machines to Perceiving Co-Pilots—A State-of-the-Art Review |
| title_sort | low back exoskeletons in industry 5 0 from machines to perceiving co pilots a state of the art review |
| topic | back exoskeleton lower-back pain intelligent framework wearable technology |
| url | https://www.mdpi.com/1424-8220/25/7/1958 |
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