Exoskeleton Application to Military Manual Handling Tasks

Proud, Jasmine K.; Lai, Daniel T. H.; Mudie, Kurt; Carstairs, Greg L.; Billing, Daniel C.; Garofolini, Alessandro; Begg, Rezaul

doi:10.1177/0018720820957467

Cited by 61 publications

(28 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…knee angle). A known future gait trajectory adds a feedforward term to powered exoskeleton devices instead of predominantly relying on feedback sensors [ 1 , 27 , 29 , 69 ]. This would improve device performance by narrowing down the nonlinear kinematic differences between the user and the device and therefore avoid altering the user’s natural gait trajectories [ 70 , 71 ].…”

Section: Discussionmentioning

confidence: 99%

Prediction of gait trajectories based on the Long Short Term Memory neural networks

et al. 2021

Self Cite

View full text Add to dashboard Cite

The forecasting of lower limb trajectories can improve the operation of assistive devices and minimise the risk of tripping and balance loss. The aim of this work was to examine four Long Short Term Memory (LSTM) neural network architectures (Vanilla, Stacked, Bidirectional and Autoencoders) in predicting the future trajectories of lower limb kinematics, i.e. Angular Velocity (AV) and Linear Acceleration (LA). Kinematics data of foot, shank and thigh (LA and AV) were collected from 13 male and 3 female participants (28 ± 4 years old, 1.72 ± 0.07 m in height, 66 ± 10 kg in mass) who walked for 10 minutes at preferred walking speed (4.34 ± 0.43 km.h-1) and at an imposed speed (5km.h-1, 15.4% ± 7.6% faster) on a 0% gradient treadmill. The sliding window technique was adopted for training and testing the LSTM models with total kinematics time-series data of 10,500 strides. Results based on leave-one-out cross validation, suggested that the LSTM autoencoders is the top predictor of the lower limb kinematics trajectories (i.e. up to 0.1s). The normalised mean squared error was evaluated on trajectory predictions at each time-step and it obtained 2.82–5.31% for the LSTM autoencoders. The ability to predict future lower limb motions may have a wide range of applications including the design and control of bionics allowing improved human-machine interface and mitigating the risk of falls and balance loss.

show abstract

Section: Discussionmentioning

confidence: 99%

Prediction of gait trajectories based on the Long Short Term Memory neural networks

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the application of PAEs is not limited to gait rehabilitation and assistance. Strength augmentation ankle exoskeletons have been developed for powering the ankle joint in healthy users to enhance their performance and reduce the risk of injuries during normal walking, running, or manual handling activities [1,4,5]. The concept of robotic exoskeletons as we know them today goes back to the 1950s when Zaroodny of the U.S. Army Exterior Ballistic Research Laboratory initiated a project on a 'powered orthopedic supplement', publishing a report in 1963 [6].…”

Section: Introductionmentioning

confidence: 99%

“…Sensors 2022, 22, x FOR PEER REVIEW 2 of 42 reduce the risk of injuries during normal walking, running, or manual handling activities [1,4,5].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Application of Wearable Sensors in Actuation and Control of Powered Ankle Exoskeletons: A Comprehensive Review

kian

Widanapathirana

Joseph

et al. 2022

Sensors

Self Cite

View full text Add to dashboard Cite

Powered ankle exoskeletons (PAEs) are robotic devices developed for gait assistance, rehabilitation, and augmentation. To fulfil their purposes, PAEs vastly rely heavily on their sensor systems. Human–machine interface sensors collect the biomechanical signals from the human user to inform the higher level of the control hierarchy about the user’s locomotion intention and requirement, whereas machine–machine interface sensors monitor the output of the actuation unit to ensure precise tracking of the high-level control commands via the low-level control scheme. The current article aims to provide a comprehensive review of how wearable sensor technology has contributed to the actuation and control of the PAEs developed over the past two decades. The control schemes and actuation principles employed in the reviewed PAEs, as well as their interaction with the integrated sensor systems, are investigated in this review. Further, the role of wearable sensors in overcoming the main challenges in developing fully autonomous portable PAEs is discussed. Finally, a brief discussion on how the recent technology advancements in wearable sensors, including environment—machine interface sensors, could promote the future generation of fully autonomous portable PAEs is provided.

show abstract

“…In [12][13][14] the theoretical development of mathematical models of exoskeletons with controlled hydraulic and electromechanical drives as well as their analytical and numerical study are provided. In [15] a review of the possibilities of using the exoskeleton for military purposes is given.…”

Section: Introductionmentioning

confidence: 99%

3d Models of Controllable Hinged Mechanisms With Links of Variable Length for Human Exoskeletons

et al. 2021

View full text Add to dashboard Cite

A spatial (3D) model of an exoskeleton with links of variable length is considered. The construction of a multi-link model is based on the analysis of a one-link model of with one fixed point in space and a two-link model of variable length. In connection with the difficulties arising in the construction of systems of differential equations of motion with a relatively large number of links that are associated with a long compilation time even when using modern computational systems and algorithms, a generalization for the mechanism for the case of an arbitrary finite number of links is considered and a high-speed method for constructing systems of differential equations of motion for the considered models of mechanisms is given. A five-link 3D model of an exoskeleton with of variable length that can be used to create a working exoskeleton or an anthropomorphic robot is presented. We propose a model with two solid weighty sections located at both ends of the link and a weightless section between them in the center of the link. Analytically synthesized trajectories of movement are obtained and the results of numerical simulation of the movement of a man-machine system in the form of a man in an exoskeleton are presented. Application of the proposed model allows one to reduce the load on the joints, increase strength, comfort and time of continuous use of the exoskeleton.

show abstract

Exoskeleton Application to Military Manual Handling Tasks

Cited by 61 publications

References 82 publications

Prediction of gait trajectories based on the Long Short Term Memory neural networks

Prediction of gait trajectories based on the Long Short Term Memory neural networks

Application of Wearable Sensors in Actuation and Control of Powered Ankle Exoskeletons: A Comprehensive Review

3d Models of Controllable Hinged Mechanisms With Links of Variable Length for Human Exoskeletons

Contact Info

Product

Resources

About