Deep learning based time-dependent reliability analysis of an underactuated lower-limb robot exoskeleton for gait rehabilitation
Hussain F. Goyal T. Hussain S. Jamwal P. Goecke R.
July 2025SAGE Publications Ltd
Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine
2025#239Issue 7656 - 665 pp.
This study evaluates the reliability of an underactuated wearable lower-limb exoskeleton designed to assist with gait rehabilitation. Recognizing the complexity of system reliability, a deep learning framework augmented with Long short-term Memory (LSTM) was utilized for the time-dependent reliability analysis of dynamic systems. The research commenced with the development of a lower-limb gait robot, modeled on a Stephenson III six-bar linkage mechanism. Following the mechanical design, computer-aided design (CAD) tools were employed to conceptualize a lower-limb robotic exoskeleton for rehabilitation purposes. The design incorporated two metallic materials (aluminum and steel), and a composite material (carbon fiber) tested using SolidWorks®. The prototype achieved a lightweight design (~1.63 kg) for carbon fiber material. An LSTM-enhanced deep neural network algorithm was implemented to predict the time-dependent reliability of joint displacements and end-effector trajectories. Finally, conditional probability methods were applied to complete the time-dependent system reliability assessment. The designed mechanical system for gait rehabilitation demonstrated high reliability (R ≈ 0.87). Over 200 simulation runs, reliability trends showed consistent and robust predictions.
feed-forward neural network , LSTM , material characterization , system reliability analysis , Underactuated mechanism
Text of the article Перейти на текст статьи
School of Information Technology and Systems, University of Canberra, Canberra, ACT, Australia
School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan
School of Systems and Computing, University of New South Wales, Canberra, ACT, Australia
School of Information Technology and Systems
School of Engineering and Digital Sciences
School of Systems and Computing
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026