|Title:||Development and assessment of a wearable waist-assistive exoskeleton for agricultural tasks||Authors:||Hsu S.-W
|Keywords:||Ergonomic assessment;Exoskeleton;Inertial measurement unit (IMU);Waist assistance;Agricultural robots;Agriculture;Energy storage;Ergonomics;Motion estimation;Object detection;Quality control;Risk assessment;Wearable sensors;Agricultural workers;Ergonomic assessment;Ergonomic evaluation;Inertial measurement unit;Mechanical energy storages;Motion recognition;Rapid upper limb assessments;Work-related musculoskeletal disorders;Exoskeleton (Robotics)||Issue Date:||2021||Journal Volume:||3||Start page/Pages:||1535-1545||Source:||American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2021||Abstract:||
Bone, muscle, and spine diseases caused by workplace tasks are called work-related musculoskeletal disorders (WMSD). Agricultural workers are most likely to suffer with WMSD due to long working hours and intensive manual work. The purpose of this study is to develop and assess a waist-assistive exoskeleton for agricultural workers to reduce the risk of WMSD and improve work efficiency. An ergonomic evaluation system which consists of wearable inertial measurement unit (IMU) sensors was developed to assess work quality in agricultural tasks. The evaluation system was used to conduct three ergonomic assessments: rapid upper limb assessment (RULA), rapid entire body assessment (REBA), and agricultural whole-body assessment (AWBA). The assessment of these four common agricultural tasks in Taiwan revealed that stooping entailed the highest risk of WMSD. Together with the evaluation system, MonoBearExo, a novel and lightweight wearable exoskeleton, was developed to reduce the risk of WMSD. It was designed to support the waist of agricultural workers when performing stooping and repetitive lifting tasks. The exoskeleton, with a total weight of only 5.5 kg, is driven by a hybrid-powered system which consists of electrical rotation motors and a mechanical energy storage system. The system has a maximum output torque of 53.3 Nm for supporting bending motion via cables, and driving both legs. The implemented motion recognition model for precise heavy object lifting detection can achieve an F1-score of 0.92; it was found to be suitable for several individuals. Compared to recently developed waist-assistive exoskeletons, the proposed design has long battery life and offers improved comfort in working conditions. ? ASABE 2021 Annual International Meeting
|Appears in Collections:||生物機電工程學系|
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