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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
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Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
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Research on Control Strategy of Lower Limb Exoskeleton Robots: A Review.

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  • 1China Coal Research Institute, Beijing 100013, China.

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Summary

This review explores control strategies for rehabilitative lower limb exoskeletons, crucial for gait training and recovery. It analyzes key tasks and challenges to advance human-robot interaction in assistive devices.

Keywords:
adaptive controlcontrol strategyend-effector controlhuman–robot interactionlower limb exoskeleton robots

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Area of Science:

  • Robotics
  • Rehabilitation Engineering
  • Human-Computer Interaction

Background:

  • Aging populations and neurological diseases increase demand for assistive devices.
  • Lower limb exoskeleton robots are vital for gait training and functional recovery.
  • Effective control strategies are essential for seamless human-robot interaction.

Purpose of the Study:

  • To systematically review control strategies for rehabilitative lower limb exoskeleton robots.
  • To analyze mechanisms, scenarios, and characteristics of typical control tasks.
  • To identify challenges and constraints in exoskeleton control.

Main Methods:

  • Review of recent research on control strategies within a hierarchical "perception-decision-execution" framework.
  • Analysis focused on trajectory reproduction, motion following, Assist-As-Needed (AAN), and motion intention prediction.
  • Examination of challenges related to drive systems, multi-source perception, and algorithm adaptability.

Main Results:

  • Detailed analysis of core mechanisms and technical characteristics for four key control tasks.
  • Identification of challenges including drive system coupling, multi-source perception, and algorithm universality.
  • Innovative separation of end-effector control from hardware for a universal framework.

Conclusions:

  • Advancing control strategies is critical for enhancing exoskeleton performance in rehabilitation.
  • Addressing challenges in perception, adaptability, and hardware-software integration is key.
  • A universal control framework can improve the effectiveness and applicability of rehabilitative exoskeletons.