Development of an Active Exoskeleton for Assisting Back Movements in Lifting Weights

Durante, Francesco; Antonelli, Michele Gabrio; Zobel, Pierluigi Beomonte

doi:10.18178/ijmerr.7.4.353-360

Cited by 23 publications

(12 citation statements)

References 4 publications

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“…Exoskeleton designers in this review tested the exoskeleton control strategies for (1) their ability to follow the user's joint motions, (2) exoskeleton stability, and (3) load reduction for the duration of the task. A few exoskeleton systems looked into user intention (e.g., Durante et al, 2018 ( Findings from this review demonstrated there were no consistent methodologies used to evaluate exoskeletons for manual handling. Further development of current exoskeleton testing and reporting standards (e.g.…”

Section: Discussionmentioning

confidence: 99%

Exoskeleton Application to Military Manual Handling Tasks

et al. 2020

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Objective The aim of this review was to determine how exoskeletons could assist Australian Defence Force personnel with manual handling tasks. Background Musculoskeletal injuries due to manual handling are physically damaging to personnel and financially costly to the Australian Defence Force. Exoskeletons may minimize injury risk by supporting, augmenting, and/or amplifying the user’s physical abilities. Exoskeletons are therefore of interest in determining how they could support the unique needs of military manual handling personnel. Method Industrial and military exoskeleton studies from 1990 to 2019 were identified in the literature. This included 67 unique exoskeletons, for which Information about their current state of development was tabulated. Results Exoskeleton support of manual handling tasks is largely through squat/deadlift (lower limb) systems (64%), with the proposed use case for these being load carrying (42%) and 78% of exoskeletons being active. Human–exoskeleton analysis was the most prevalent form of evaluation (68%) with reported reductions in back muscle activation of 15%–54%. Conclusion The high frequency of citations of exoskeletons targeting load carrying reflects the need for devices that can support manual handling workers. Exoskeleton evaluation procedures varied across studies making comparisons difficult. The unique considerations for military applications, such as heavy external loads and load asymmetry, suggest that a significant adaptation to current technology or customized military-specific devices would be required for the introduction of exoskeletons into a military setting. Application Exoskeletons in the literature and their potential to be adapted for application to military manual handling tasks are presented.

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Section: Discussionmentioning

confidence: 99%

Exoskeleton Application to Military Manual Handling Tasks

et al. 2020

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“…The mannequin resembled the man to which the accident occurred, i.e., 1.75 m height and 75 kg of mass. As for the geometrical and mass proportions, the models by Drillis and Contini (1966) and of Pheasant (1986) were used, as in Durante et al (2018). In Table 2, the segments considered for the model and their masses and dimensions are reported, and Figure 5 shows the scheme of the anthropomorphic model adopted, compared to the profile of the wall of the accident.…”

Section: Accident On Construction Sitementioning

confidence: 99%

Tools and Biomechanical Modeling Use in Legal Disputes: Some Case Studies

Durante

2019

Front. Bioeng. Biotechnol.

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The paper presents some of the biomechanical tools available for the forensic bioengineering expert. The tools range from the simple three-dimensional modeling environment to represent the geometries up to the analytical models based on the free-body diagram and the multibody numerical models of rigid bodies. Through these tools the forensic bioengineering expert is able to solve complex problems by providing quantitative results based on a scientific approach. In this work three case studies, representing real cases that were treated in court, are presented. They relate to accidents which occurred in different contexts. The first relates to an accident in a filament factory where a worker remained with her body stuck in the production line, the second the hit of a pedestrian, and the last concerning a worker who fell from a wall on a construction site. It is shown that the approach to modeling may not always be necessarily complex. It was possible to solve the first case with a simple three-dimensional geometric model that clearly highlighted the development of the facts. In the second case it was possible to set up a simple analytical model based on a free body diagram to search for the relationship between the forces developed on the invested leg, demonstrating the relationship between the accident and the injuries reported. The third case, with the need for more complex modeling, was instead treated with a kinematic and dynamic multibody model which allowed the dynamics of the accident to be traced, starting from the final position in which the victim was found. In each case, the competence of the forensic bioengineering expert was crucial in identifying the correct modeling for the case in question, with the choice of the right data, in order to arrive at reliable quantitative results.

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“…Other examples of use of biological signals are in different kinds of rehabilitation and medical assistive devices (prostheses and orthoses), humanoid robots and industrial robots [18][19][20][21][22][23]. Electromyographic (EMG) signals, an expression of electrical activity of muscles, were widely adopted in several applications: to control the line tracking of a mobile robot [24]; to control an exoskeleton, powered by pneumatic muscles, that supports the back while performing weightlifting movements [25]; in combination with an inertial measurement unit (IMU) sensor, to control a mobile robot based on gesture recognition [26]; in combination with electro-oculography (EOG), EEG, vision systems and head movements, to control a robotic arm [27] or in combination with a Kinect device [28].…”

Section: Introductionmentioning

confidence: 99%

Modeling-Based EMG Signal (MBES) Classifier for Robotic Remote-Control Purposes

et al. 2022

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The fast-growing human–robot collaboration predicts that a human operator could command a robot without mechanical interface if effective communication channels are established. In noisy, vibrating and light sensitive environments, some sensors for detecting the human intention could find critical issues to be adopted. On the contrary, biological signals, as electromyographic (EMG) signals, seem to be more effective. In order to command a laboratory collaborative robot powered by McKibben pneumatic muscles, promising actuators for human–robot collaboration due to their inherent compliance and safety features have been researched, a novel modeling-based electromyographic signal (MBES) classifier has been developed. It is based on one EMG sensor, a Myotrac one, an Arduino Uno and a proper code, developed in the Matlab environment, that performs the EMG signal recognition. The classifier can recognize the EMG signals generated by three hand-finger movements, regardless of the amplitude and time duration of the signal and the muscular effort, relying on three mathematical models: exponential, fractional and Gaussian. These mathematical models have been selected so that they are the best fitting with the EMG signal curves. Each of them can be assigned a consent signal for performing the wanted pick-and-place task by the robot. An experimental activity was carried out to test and achieve the best performance of the classifier. The validated classifier was applied for controlling three pressure levels of a McKibben-type pneumatic muscle. Encouraging results suggest that the developed classifier can be a valid command interface for robotic purposes.

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Development of an Active Exoskeleton for Assisting Back Movements in Lifting Weights

Cited by 23 publications

References 4 publications

Exoskeleton Application to Military Manual Handling Tasks

Exoskeleton Application to Military Manual Handling Tasks

Tools and Biomechanical Modeling Use in Legal Disputes: Some Case Studies

Modeling-Based EMG Signal (MBES) Classifier for Robotic Remote-Control Purposes

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