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Related Concept Videos

Structural Classification of Joints01:20

Structural Classification of Joints

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Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
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Functional Classification of Joints01:09

Functional Classification of Joints

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Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
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Classification of Connective Tissues01:30

Classification of Connective Tissues

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The connective tissues have different properties and functions in the human body. They are broadly categorized into proper, supporting, or fluid connective tissues.
Connective Tissue Proper
Connective tissue proper is the most abundant class of connective tissues. As its name implies, it predominantly connects different tissues in the body. Depending on the cell types, ground substance, viscosity, and fiber types in the ECM, connective tissue proper is further categorized into loose and dense....
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Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

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Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...
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Classification of Epithelial Tissues: Overview01:22

Classification of Epithelial Tissues: Overview

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Epithelial tissues are classified according to the shape of the cells and the number of cell layers formed. Cell shapes can be squamous (flattened and thin), cuboidal (square-like, as wide as it is tall), or columnar (rectangular, taller than it is wide). Additionally, the nucleus shape helps identify the type of epithelial cells. Squamous cells have flattened disc-shaped nuclei, cuboidal cells have spherical nuclei, and columnar cells have elongated nuclei.
Based on the number of cell layers,...
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Classification of Epithelial Tissues: Simple Epithelium01:30

Classification of Epithelial Tissues: Simple Epithelium

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Simple epithelium consists of a single layer of cells that lines body cavities and blood vessels. The shape of the cells in the epithelium reflects the function of the tissue. Cells in simple squamous epithelium appear as thin scales with flat, elliptical nuclei that mirror the form of the cell.
Because of the thinness of the cells, simple squamous epithelium is present where the rapid passage of chemical compounds is observed. For example, the endothelium that lines the capillaries and vessels...
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Related Experiment Video

Updated: Jan 20, 2026

Agarose-based Tissue Mimicking Optical Phantoms for Diffuse Reflectance Spectroscopy
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Agarose-based Tissue Mimicking Optical Phantoms for Diffuse Reflectance Spectroscopy

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Machine learning classification of human joint tissue from diffuse reflectance spectroscopy data.

Rajitha Gunaratne1, Isaac Monteath1, Joshua Goncalves2

  • 1Curtin University, Kent Street, Bentley 6102, Australia.

Biomedical Optics Express
|August 28, 2019
PubMed
Summary
This summary is machine-generated.

Diffuse reflectance spectroscopy (DRS) shows promise for differentiating human joint tissues during robotic surgery. This cost-effective, non-contact technology achieved over 99% accuracy in classifying tissues, aiding surgical precision.

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A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data
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Area of Science:

  • Biomedical Engineering
  • Surgical Technology
  • Spectroscopy

Background:

  • Robotic surgery systems can benefit from enhanced real-time tissue differentiation.
  • Diffuse reflectance spectroscopy (DRS) offers a simple, cost-effective, non-contact method for tissue analysis.

Purpose of the Study:

  • To evaluate the potential of integrating DRS sensing into real-time robotic surgery systems.
  • To assess DRS's efficacy in differentiating human joint tissues.

Main Methods:

  • Supervised machine learning algorithms were employed.
  • Diffuse reflectance spectra from human joint tissues obtained during surgery were analyzed.
  • Classification accuracy, sensitivity, and optimal spectral parameters were determined.

Main Results:

  • Achieved classification accuracy exceeding 99% for human joint tissues.
  • High sensitivity for specific tissues: cartilage (99.7%), subchondral bone (99.2%), meniscus (100%), and cancellous bone (100%).
  • Optimal parameters identified: full wavelength range, >8nm resolution, SNR >10:1, with 800-900nm range yielding highest accuracy.

Conclusions:

  • DRS is a viable technology for distinguishing human joint tissues.
  • DRS has significant potential for integration into robotic orthopedic surgery systems to improve outcomes.