98%
921
2 minutes
20
During the development and assessment of an exoskeleton, many different analyzes need to be performed. The most frequently used evaluate the changes in muscle activations, metabolic consumption, kinematics, and kinetics. Since human-exoskeleton interactions are based on the exchange of forces and torques, the latter of these, kinetic analyzes, are essential and provide indispensable evaluation indices. Kinetic analyzes, however, require access to, and use of, complex experimental apparatus, involving many instruments and implicating lengthy data analysis processes. The proposed methodology in this paper, which is based on data collected EMG and motion capture systems, considerably reduces this burden by calculating kinetic parameters, such as torque and power, without needing ground reaction force measurements. This considerably reduces the number of instruments used, allows the calculation of kinetic parameters even when the use of force sensors is problematic, does not need any dedicated software, and will be shown to have high statistical validity. The method, in fact, combines data found in the literature with those collected in the laboratory, allowing the analysis to be carried out over a much greater number of cycles than would normally be collected with force plates, thus enabling easy access to statistical analysis. This new approach evaluates the kinetic effects of the exoskeleton with respect to changes induced in the user's kinematics and muscular activation patterns and provides indices that quantify the assistance in terms of torque (AMI) and power (API). Following the User-Center Design approach, which requires driving the development process as feedback from the assessment process, this aspect is critical. Therefore, by enabling easy access to the assessment process, the development of exoskeletons could be positively affected.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643542 | PMC |
http://dx.doi.org/10.3389/fnbot.2022.982950 | DOI Listing |
ObjectiveThis study empirically investigates the embodiment of occupational exoskeletons (OEs) through repeated use.BackgroundOEs are wearable devices designed to assist operators' movements. Their embodiment- the phenomenon by which they come to be perceived as an integral part of oneself - remains underexplored, thus limiting our understanding of OE adoption.
View Article and Find Full Text PDFIEEE Trans Neural Syst Rehabil Eng
August 2025
Unlabelled: This study aims to address the limitations of traditional exoskeleton designs by developing a biomimetic actuation path and a hierarchical motion recognition framework to improve integration with human biomechanics and reduce muscular effort during walking.
Methods: A musculoskeletal model was used to quantify lower limb muscle force patterns, enabling the design of actuation paths aligned with natural muscle contraction trajectories. A hierarchical motion recognition system, combining an auto-encoder and an artificial neural network (ANN), was developed for real-time identification of gait events, activity levels, and walking speeds.
Sensors (Basel)
July 2025
Fraunhofer Institute for Manufacturing Engineering and Automation IPA, 70569 Stuttgart, Germany.
Exoskeletons transfer loads to the human body via physical human-exoskeleton interfaces (pHEI). However, the human-exoskeleton interaction remains poorly understood, and the mechanical properties of the pHEI are not well characterized. Therefore, we present a novel methodology to precisely characterize pHEI interaction stiffnesses under various loading conditions.
View Article and Find Full Text PDFWearable Technol
June 2025
Department of Engineering Design, Indian Institute of Technology Madras, Chennai, TN, India.
The human need for rehabilitation, assistance, and augmentation has led to the development and use of wearable exoskeletons. Upper limb exoskeletons under research and development are tested on human volunteers to gauge performance and usability. Direct testing can often cause straining of the joints, especially the shoulder joint, which is the most important and flexible joint in the upper extremity of the human body.
View Article and Find Full Text PDFIEEE Trans Neural Syst Rehabil Eng
July 2025
The human-machine interface is a crucial component of exoskeleton design, and understanding how the human nervous system adapts to and learns to coordinate with wearable robotic systems is essential for optimizing assistive device functionality. Research has shown that brain activity reflects movement-related effort and adaptation, with studies using mobile brain-body imaging approaches and EEG analysis revealing changes in cortical activity during locomotion and exoskeleton-assisted walking. This study aimed to investigate cortical dynamics during human-exoskeleton interactions using multi-model Adaptive Mixture ICA (AMICA), hypothesizing that the approach would separate EEG data into distinct phases corresponding to adaptation levels and reveal changes in brain area engagement over time.
View Article and Find Full Text PDF