An Adaptive Neuromuscular Controller for Assistive Lower-Limb Exoskeletons: A Preliminary Study on Subjects with Spinal Cord Injury

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The complexity of modern control systems necessitates architectures that achieve high performance while ensuring robust stability, particularly for nonlinear systems. In this work, we tackle the challenge of designing output-feedback controllers to boost t ...

This paper introduces a novel method for data-driven robust control of nonlinear systems based on the Koopman operator, utilizing Integral Quadratic Constraints (IQCs). The Koopman operator theory facilitates the linear representation of nonlinear system d ...

One of the most common knee injuries is the Anterior Cruciate Ligament (ACL) rupture with severe implications on knee stability. The usual treatment is the ACL Reconstruction (ACLR) surgery where the surgeon replaces the torn ligament with a graft in an ef ...

Background :Sensory reafferents are crucial to correct our posture and movements, both reflexively and in a cognitively driven manner. They are also integral to developing and maintaining a sense of agency for our actions. In cases of compromised reafferen ...

Cartilage homeostasis, crucial for musculoskeletal function, is orchestrated by interconnected biophysical cues. In healthy cartilage, repetitive compressive loading not only elicits a range of mechanical stimuli but also induces a gradual transient temper ...

Background Multiple sclerosis is a progressive neurological disease that affects the central nervous system, resulting in various symptoms. Among these, impaired mobility and fatigue stand out as the most prevalent. The progressive worsening of symptoms ad ...

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

Locomotion is based on a sophisticated interaction among the environment, the musculoskeletal system, the spinal cord, and the brain locomotor areas. Quality of life is strongly related to the proper capability of this movement. However, many pathologies, ...

Objective. Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locom ...

Accurate real-time estimation of the gait phase (GP) is crucial for many control methods in exoskeletons and prostheses. A class of approaches to GP estimation construct the phase portrait of a segment or joint angle, and use the normalized polar angle of ...

There is a lack of knowledge about the accuracy of the Conventional Gait Model (CGM), compared to the true bone motion. Accuracy is hindered by both marker misplacement and soft-tissue artefact (STA). The effect of the lateral knee marker (KNE) misplacemen ...

The growing demand for online gait phase (GP) estimation, driven by advancements in exoskeletons and prostheses, has prompted numerous approaches in the literature. Some approaches explicitly use time, while others rely on state variables to estimate the G ...

Quadruped animal locomotion emerges from the interactions between the spinal central pattern generator (CPG), sensory feedback, and supraspinal drive signals from the brain. Computational models of CPGs have been widely used for investigating the spinal co ...

Exoskeletons intended for partial assistance of walking should be able to follow the gait pattern of their users, via online adaptive control strategies rather than imposing predefined kinetic or kinematic profiles. NeuroMuscular Controllers (NMCs) are ada ...

Experiments on the lower limbs are the only approaches being used to study how hypogravity (HG) (0 < g < 1, e.g., Moon: 1/6 g, Mars: 3/8 g) affects human movement. The goal of this study was to expand this field experimentally by investigating the effect o ...

The transition from aquatic to terrestrial environments represents a significant event in the history of evolution. For this transition to occur, animals had to adapt their morphology, physiology and locomotory skills to handle the challenges and interacti ...

The frequency response data of a generalized system is used to design fixed-structure controllers for the H2 and H∞ synthesis problem. The minimization of the two and infinity norm of the transfer function between the exogenous inputs and performance outpu ...

Objective: To characterize ambulatory knee moments with respect to medial knee osteoarthritis (OA) severity comprehensively and to assess the possibility of developing a severity index combining knee moment parameters. ...

An Adaptive Neuromuscular Controller for Assistive Lower-Limb Exoskeletons: A Preliminary Study on Subjects with Spinal Cord Injury

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Parametrizations of all stable closed-loop responses: From theory to neural network control design

Koopman-based Data-driven Robust Control of Nonlinear Systems Using Integral Quadratic Constraints

Can lateral tenodesis improve the rotational stability of the ACL reconstruction? A finite element analysis

Augmenting locomotor perception by remapping tactile foot sensation to the back

Synergetic Support of Cartilage Homeostasis via Coupled Thermal-Hydrostatic Pressure Stimuli

Effects of multidisciplinary inpatient rehabilitation on everyday life physical activity and gait in patients with multiple sclerosis

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Investigating the neuromechanical control of healthy gait modulation and pathological gaits observed in cerebral palsy using neuromuscular simulations

Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model

Gait Phase Estimation in Steady Walking: A Comparative Study of Methods Based on the Phase Portrait of the Hip Angle

On the accuracy of the Conventional gait Model: Distinction between marker misplacement and soft tissue artefact errors

State-Based Versus Time-Based Estimation of the Gait Phase for Hip Exoskeletons in Steady and Transient Walking

Puppeteer and Marionette: Learning Anticipatory Quadrupedal Locomotion Based on Interactions of a Central Pattern Generator and Supraspinal Drive

Novel Design and Implementation of a Neuromuscular Controller on a Hip Exoskeleton for Partial Gait Assistance

Hypogravity modeling of upper extremities: an investigation of manual handling in the workplace

Neuromechanical Simulations of Animats with Decentralised Control

Data-driven fixed-structure frequency-based H2 and H∞ controller design

Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index