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ALICE: Conceptual Development of a Lower Limb Exoskeleton Robot Driven by an On-Board Musculoskeletal Simulator. | LitMetric

AI Article Synopsis

  • The article discusses the development of ALICE, a robotics platform designed for analyzing and improving gait patterns through a wearable exoskeleton and a muscle-driven simulator.
  • ALICE addresses the issue of variability in movement kinetics among individuals, aiming to enhance personalized rehabilitation strategies.
  • By utilizing a combination of real patient data and advanced sensor technology, ALICE seeks to advance the diagnosis and treatment of gait abnormalities in conditions like multiple sclerosis.

Article Abstract

Objective: In this article, we present the conceptual development of a robotics platform, called ALICE (Assistive Lower Limb Controlled Exoskeleton), for kinetic and kinematic gait characterization. The ALICE platform includes a robotics wearable exoskeleton and an on-board muscle driven simulator to estimate the user's kinetic parameters.

Background: Even when the kinematics patterns of the human gait are well studied and reported in the literature, there exists a considerable intra-subject variability in the kinetics of the movements. ALICE aims to be an advanced mechanical sensor that allows us to compute real-time information of both kinetic and kinematic data, opening up a new personalized rehabilitation concept.

Methodology: We developed a full muscle driven simulator in an open source environment and validated it with real gait data obtained from patients diagnosed with multiple sclerosis. After that, we designed, modeled, and controlled a 6 DoF lower limb exoskeleton with inertial measurement units and a position/velocity sensor in each actuator.

Significance: This novel concept aims to become a tool for improving the diagnosis of pathological gait and to design personalized robotics rehabilitation therapies.

Conclusion: ALICE is the first robotics platform automatically adapted to the kinetic and kinematic gait parameters of each patient.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7038445PMC
http://dx.doi.org/10.3390/s20030789DOI Listing

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