AIMC Topic: Lower Extremity

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Fully automated deep learning for knee alignment assessment in lower extremity radiographs: a cross-sectional diagnostic study.

Skeletal radiology
OBJECTIVES: Accurate assessment of knee alignment and leg length discrepancy is currently measured manually from standing long-leg radiographs (LLR), a process that is both time consuming and poorly reproducible. The aim was to assess the performance...

MotorSkins-a bio-inspired design approach towards an interactive soft-robotic exosuit.

Bioinspiration & biomimetics
The work presents a bio-inspired design approach to a soft-robotic solution for assisting the knee-bending in users with reduced mobility in lower limbs. Exosuits and fluid-driven actuators are fabric-based devices that are gaining increasing relevan...

Feature Selection and Validation of a Machine Learning-Based Lower Limb Risk Assessment Tool: A Feasibility Study.

Sensors (Basel, Switzerland)
Early and self-identification of locomotive degradation facilitates us with awareness and motivation to prevent further deterioration. We propose the usage of nine squat and four one-leg standing exercise features as input parameters to Machine Learn...

Action Recognition of Lower Limbs Based on Surface Electromyography Weighted Feature Method.

Sensors (Basel, Switzerland)
To improve the recognition rate of lower limb actions based on surface electromyography (sEMG), an effective weighted feature method is proposed, and an improved genetic algorithm support vector machine (IGA-SVM) is designed in this paper. First, for...

Walking with robot-generated haptic forces in a virtual environment: a new approach to analyze lower limb coordination.

Journal of neuroengineering and rehabilitation
BACKGROUND: Walking with a haptic tensile force applied to the hand in a virtual environment (VE) can induce adaptation effects in both chronic stroke and non-stroke individuals. These effects are reflected in spatiotemporal outcomes such as gait spe...

Machine learning analysis of multispectral imaging and clinical risk factors to predict amputation wound healing.

Journal of vascular surgery
OBJECTIVE: Prediction of amputation wound healing is challenging due to the multifactorial nature of critical limb ischemia and lack of objective assessment tools. Up to one-third of amputations require revision to a more proximal level within 1 year...

A deep learning approach to automatically quantify lower extremity alignment in children.

Skeletal radiology
OBJECTIVE: To develop and validate a convolutional neural network (CNN) capable of predicting the anatomical landmarks used to calculate the hip-knee-ankle angles (HKAAs) from radiographs and thereby quantify lower extremity alignments in children.

Exoskeleton robots for lower limb assistance: A review of materials, actuation, and manufacturing methods.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
The field of robot-assisted physical rehabilitation and robotics technology for providing support to the elderly population is rapidly evolving. Lower limb robot aided rehabilitation and assistive technology have been a focus for the engineering comm...

Deep learning approach for guiding three-dimensional computed tomography reconstruction of lower limbs for robotically-assisted total knee arthroplasty.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Robotic-assisted total knee arthroplasty (TKA) was performed to promote the accuracy of bone resection and mechanical alignment. Among these TKA system procedures, 3D reconstruction of CT data of lower limbs consumes significant manpower....

Periodic event-triggered sliding mode control for lower limb exoskeleton based on human-robot cooperation.

ISA transactions
This paper presents a periodic event-triggered sliding mode control (SMC) scheme based on human-robot cooperation for lower limb exoskeletons. Firstly, a Genetic Algorithm-Back propagation (GA-BP) neural network is proposed to estimate the motion int...