Generating an Adaptive and Robust Walking Pattern for a Prosthetic Ankle–Foot by Utilizing a Nonlinear Autoregressive Network With Exogenous Inputs

Kouzbary, Hamza Al; Kouzbary, Mouaz Al; Tham, Lai Kuan; Liu, Jinjing; Shasmin, Hanie Nadia; Osman, Noor Azuan Abu

doi:10.1109/tnnls.2021.3076060

Cited by 9 publications

(4 citation statements)

References 55 publications

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“…Compared with the ESAR foot, the only benefit of the powered ankle-foot prosthesis is the input of net positive power, which has made for better performance and slighter influence. Therefore, it is believed that the performance of the designed powered ankle-foot prosthesis can be improved further after applying the optimal assembly and advanced control system based on biomechanical estimation technology [32,33], while the undesirable influence on the users' lower-limb biomechanics can also be reduced. The above results and discussion also imply that, if conditions allow, amputees unfamiliar with using the ankle-foot prosthesis can start with the powered ankle-foot prosthesis rather than the ESAR foot.…”

Section: Discussionmentioning

confidence: 99%

Design and preliminary verification of a novel powered ankle–foot prosthesis: From the perspective of lower-limb biomechanics compared with ESAR foot

Liu,

Cheah

et al. 2024

PLoS ONE

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A novel powered ankle–foot prosthesis is designed. The effect of wearing the novel prosthesis and an energy-storage-and-return (ESAR) foot on lower-limb biomechanics is investigated to preliminarily evaluate the design. With necessary auxiliary materials, a non-amputated subject (a rookie at using prostheses) is recruited to walk on level ground with an ESAR and the novel powered prostheses separately. The results of the stride characteristics, the ground reaction force (GRF) components, kinematics, and kinetics in the sagittal plane are compared. Wearing the powered prosthesis has less prolongation of the gait cycle on the unaffected side than wearing the ESAR foot. Wearing ESAR or proposed powered prostheses influences the GRF, kinematics, and kinetics on the affected and unaffected sides to some extent. Thereinto, the knee moment on the affected side is influenced most. Regarding normal walking as the reference, among the total of 15 indexes, the influences of wearing the proposed powered prosthesis on six indexes on the affected side (ankle’s/knee’s/hip’s angles, hip’s moment, and Z- and X-axis GRF components) and five indexes on the unaffected side (ankle’s/knee’s/hip’s angles and ankle’s/hip’s moments) are slighter than those of wearing the ESAR foot. The influences of wearing the powered prosthesis on two indexes on the unaffected side (knee’s moment and X-axis GRF component) are similar to those of wearing the ESAR foot. The greatest improvement of wearing the powered prosthesis is to provide further plantarflexion after reaching the origin of the ankle joint before toe-off, which means that the designed powered device can provide further propulsive power for the lifting of the human body’s centre of gravity during walking on level ground. The results demonstrate that wearing the novel powered ankle–foot prosthesis benefits the rookie in recovering the normal gait more than wearing the ESAR foot.

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Section: Discussionmentioning

confidence: 99%

Design and preliminary verification of a novel powered ankle–foot prosthesis: From the perspective of lower-limb biomechanics compared with ESAR foot

Liu,

Cheah

et al. 2024

PLoS ONE

Self Cite

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“…The regression algorithms, including linear regression (LR), regression tree, support vector regression (SVR), the feedforward neural network (FFNN), and the nonlinear autoregressive model with the exogenous input (NARX) neural network are investigated. The block diagram of the NARX neural network is shown in Figure 16 [ 40 ]. NARX is a type of recurrent neural network.…”

Section: Ai-based Qasmentioning

confidence: 99%

“…tigated. The block diagram of the NARX neural network is shown in Figure 16 [40]. NARX is a type of recurrent neural network.…”

Section: Ai-based Qasmentioning

confidence: 99%

Artificial Intelligence-Assisted RFID Tag-Integrated Multi-Sensor for Quality Assessment and Sensing

Song,

2024

Sensors

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Radio frequency identification (RFID) is well known as an identification, track, and trace approach and is considered to be the key physical layer technology for the industrial internet of things (IIoT). However, IIoT systems have to introduce additional complex sensor networks for pervasive monitoring, and there are still challenges related to item-level sensing and data recording. To overcome the shortage, this work proposes an artificial intelligence (AI)-assisted RFID-based multi-sensing technology. Both passive and semi-passive RFID tag-integrated multi-sensors are developed. The main contributions and the novelty of this investigation are as follows. A UHF RFID tag-integrated multi-sensor with a boosted charge pump is proposed; it enables high RF signal sensitivity and a long operational range. The whole hardware design, including the antenna and energy harvester, are studied. Moreover, a demonstration with real-world ham product sensing data is conducted. This work also proposes and successfully demonstrates the integration of machine learning algorithms, specifically the NARX neural network, with RFID sensing data for food product quality assessment and sensing (QAS). This application of machine learning to RFID-generated data for quality assessment is also a novel aspect of the research. The deployment of an autoregressive model with an exogenous input (NARX) neural network model, tailored for nonlinear processes, emerges as the most effective, achieving a root mean square error (RMSE) of 0.007 and an R-squared value of 0.99 for ham product QAS. By deploying the technology, low-cost, timely, and flexible product QAS can be achieved in manufacturing industries, which helps product quality improvement and the optimization of the manufacturing line and supply chain.

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“…The extended work was proposed to achieve the trajectory planning of the knee joint [126]. Also, nonlinear autoregressive networks have been proposed to avoid control switching at different walking speeds [127]. Inspired by a pre-existing control strategy developed for bipedal robots, Ryan [128] first applied the virtual constraints to prostheses for extracting the continuous reference trajectories.…”

Section: A Complete Coordination On Structured Terrainsmentioning

confidence: 99%

Robotic Leg Prosthesis: A Survey From Dynamic Model to Adaptive Control for Gait Coordination

Ma,

Zhang,

2024

IEEE Trans. Neural Syst. Rehabil. Eng.

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Gait coordination (GC), meaning that one leg moves in the same pattern but with a specific phase lag to the other, is a spontaneous behavior in the walking of a healthy person. It is also crucial for unilateral amputees with the robotic leg prosthesis to perform ambulation cooperatively in the real world. However, achieving the GC for amputees poses significant challenges to the prostheses' dynamic modeling and control design. Still, there has not been a clear survey on the initiation and evolution of the detailed solutions, hindering the precise decision of future explorations. To this end, this paper comprehensively reviews GCoriented dynamic modeling and adaptive control methods for robotic leg prostheses. Considering the two representative environments concerned with adaptive control, we first classify the dynamic models into the deterministic model for structured terrain and the constrained stochastic model for stochastically uneven terrain. Inspired by the concept of synchronization, we then emphasize three typical problems for the GC realization, i.e., complete coordination on structured terrain, stochastic coordination on stochastically uneven terrain, and finite-time delayed stochastic coordination. Finally, we conclude with a discussion on the remaining challenges and opportunities in controlling robotic leg prostheses.

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Generating an Adaptive and Robust Walking Pattern for a Prosthetic Ankle–Foot by Utilizing a Nonlinear Autoregressive Network With Exogenous Inputs

Cited by 9 publications

References 55 publications

Design and preliminary verification of a novel powered ankle–foot prosthesis: From the perspective of lower-limb biomechanics compared with ESAR foot

Design and preliminary verification of a novel powered ankle–foot prosthesis: From the perspective of lower-limb biomechanics compared with ESAR foot

Artificial Intelligence-Assisted RFID Tag-Integrated Multi-Sensor for Quality Assessment and Sensing

Robotic Leg Prosthesis: A Survey From Dynamic Model to Adaptive Control for Gait Coordination

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