Current State and Design Recommendations of Exoskeletons of Lower Limbs in Military Applications

Leova, Lydie; Cubanova, Slavka; Kutílek, Patrik; Volf, Petr; Hejda, Jan; Hybl, Jan; Šťastný, Petr; Vágner, Michal; Křivánek, Václav

doi:10.1007/978-3-030-98260-7_29

Cited by 4 publications

(1 citation statement)

References 24 publications

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“…They also emphasize that significant adaptation of existing technologies, such as industrial exoskeletons, would be necessary to meet the specific requirements of military applications. Meanwhile, other studies focus on the design considerations for lower [15] and/or upper exoskeletons [15] and/or upper exoskeletons [16] tailored for military use, but they often neglect alternative wearable robots designed particularly for rehabilitation and reintegration purposes. Therefore, this paper aims to define wearable robots within this context and to describe categories of wearable robots employed in the prevention of MSK injuries in the support of military operations and in the enhancement of rehabilitation outcomes and social reintegration efforts.…”

Section: Introductionmentioning

confidence: 99%

Current State, Needs, and Opportunities for Wearable Robots in Military Medical Rehabilitation and Force Protection

Cooper,

Smolinski,

Candiotti

et al. 2024

Actuators

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Despite advances in wearable robots across various fields, there is no consensus definition or design framework for the application of this technology in rehabilitation or musculoskeletal (MSK) injury prevention. This paper aims to define wearable robots and explore their applications and challenges for military rehabilitation and force protection for MSK injury prevention. We conducted a modified Delphi method, including a steering group and 14 panelists with 10+ years of expertise in wearable robots. Panelists presented current wearable robots currently in use or in development for rehabilitation or assistance use in the military workforce and healthcare. The steering group and panelists met to obtain a consensus on the wearable robot definition applicable for rehabilitation or primary injury prevention. Panelists unanimously agreed that wearable robots can be grouped into three main applications, as follows: (1) primary and secondary MSK injury prevention, (2) enhancement of military activities and tasks, and (3) rehabilitation and reintegration. Each application was presented within the context of its target population and state-of-the-art technology currently in use or under development. Capturing expert opinions, this study defines wearable robots for military rehabilitation and MSK injury prevention, identifies health outcomes and assessment tools, and outlines design requirements for future advancements.

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Section: Introductionmentioning

confidence: 99%

Current State, Needs, and Opportunities for Wearable Robots in Military Medical Rehabilitation and Force Protection

Cooper,

Smolinski,

Candiotti

et al. 2024

Actuators

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Terrain slope parameter recognition for exoskeleton robot in urban multi-terrain environments

Guo,

Li,

et al. 2024

Complex Intell. Syst.

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Lower limb augmentation exoskeletons (LLAE) have been applied in several domains to enforce human walking capability. As humans can adjust their joint moments and generate different amounts of mechanical energy while walking on different terrains, the LLAEs should provide adaptive augmented torques to the wearer in multi-terrain environments, which requires LLAEs to implement accurate terrain parameter recognition. However, the outputs of previous terrain parameter recognition algorithms are more redundant, and the algorithms have higher computational complexity and are susceptible to external interference. Therefore, to resolve the above issues, this paper proposed a neural network regression (NNR)-based algorithm for terrain slope parameter recognition. In particular, this paper defined for the first time a unified representation of terrain parameters: terrain slope (TS), a single parameter that can provide enough information for exoskeleton control. In addition, our proposed NNR model uses only basic human parameters and LLAE joint motion posture measured by an Inertial Measurement Unit (IMU) as inputs to predict the TS, which is computationally simpler and less susceptible to interference. The model was evaluated using K-fold cross-validation and the results showed that the model had an average error of only 2.09$$^\circ $$ ∘ . To further validate the effectiveness of the proposed algorithm, it was verified on a homemade LLAE and the experimental results showed that the proposed TS parameter recognition algorithm only produces an average error of 3.73$$^\circ $$ ∘ in multi-terrain environments. The defined terrain parameters can meet the control requirements of LLAE in urban multi-terrain environments. The proposed TS parameter recognition algorithm could facilitate the optimization of the adaptive gait control of the exoskeleton system and improve user experience, energy efficiency, and overall comfort.

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Real-time Human Motion Intention Recognition for Powered Wearable Hip Exoskeleton using LSTM Networks

Ding,

Dong,

2024

2024 WRC Symposium on Advanced Robotics and Automation (WRC SARA)

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Current State and Design Recommendations of Exoskeletons of Lower Limbs in Military Applications

Cited by 4 publications

References 24 publications

Current State, Needs, and Opportunities for Wearable Robots in Military Medical Rehabilitation and Force Protection

Current State, Needs, and Opportunities for Wearable Robots in Military Medical Rehabilitation and Force Protection

Terrain slope parameter recognition for exoskeleton robot in urban multi-terrain environments

Real-time Human Motion Intention Recognition for Powered Wearable Hip Exoskeleton using LSTM Networks

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