Felipe Ballen-Moreno, Kevin Langlois, Pasquale Ferrentino, Joost Brancart, Christopher Van Vlerken, Bram Vanderborght, Nico Buls, Tom Verstraten
{"title":"Robotically Aided Method to Characterise the Soft Tissue Interaction with Wearable Robots.","authors":"Felipe Ballen-Moreno, Kevin Langlois, Pasquale Ferrentino, Joost Brancart, Christopher Van Vlerken, Bram Vanderborght, Nico Buls, Tom Verstraten","doi":"10.1109/ICORR58425.2023.10304757","DOIUrl":null,"url":null,"abstract":"<p><p>Wearable robots are widely used to enhance, support or assist humans in different tasks. To accomplish this scope, the interaction between the human body and the device should be comfortable, smooth, high-efficient to transfer forces, and safe for the user. Nevertheless, the pressure and shear stress related to these goals have been overlooked or partially analysed. In this sense, it is crucial to understand the soft tissue response through the in-vivo characterisation of multiple areas of the human body. In fact, soft tissue characterisation plays an essential role in calculating the pressure distribution and shear stress. However, current approaches to estimating soft tissue properties are unsuitable for deployment with multiple human body areas. Hence, this work presents a novel methodology to ease the characterisation of soft tissues using a robotic arm and a 3D superficial scanner. First, the robotic arm is validated by comparing the tensile and compression tests to the indentation tests done by the robot, estimating a 10,4% error. The preliminary experimental tests present the hyperelastic model which fit two adjacent zones of the forearm. This analysis can be extended in several ways, such as: calculating the shear stress, the energy losses or deformations caused by the interaction, and investigating the pressure distribution of different types of physical interfaces.</p>","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICORR58425.2023.10304757","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Wearable robots are widely used to enhance, support or assist humans in different tasks. To accomplish this scope, the interaction between the human body and the device should be comfortable, smooth, high-efficient to transfer forces, and safe for the user. Nevertheless, the pressure and shear stress related to these goals have been overlooked or partially analysed. In this sense, it is crucial to understand the soft tissue response through the in-vivo characterisation of multiple areas of the human body. In fact, soft tissue characterisation plays an essential role in calculating the pressure distribution and shear stress. However, current approaches to estimating soft tissue properties are unsuitable for deployment with multiple human body areas. Hence, this work presents a novel methodology to ease the characterisation of soft tissues using a robotic arm and a 3D superficial scanner. First, the robotic arm is validated by comparing the tensile and compression tests to the indentation tests done by the robot, estimating a 10,4% error. The preliminary experimental tests present the hyperelastic model which fit two adjacent zones of the forearm. This analysis can be extended in several ways, such as: calculating the shear stress, the energy losses or deformations caused by the interaction, and investigating the pressure distribution of different types of physical interfaces.