Recent Advanced Applications of Computational Biology and Biomedical Informatics Based on AI

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Bioelectronics".

Deadline for manuscript submissions: closed (15 July 2023) | Viewed by 1740

Special Issue Editors


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Guest Editor
Artificial Intelligence Lab, Department of Computer Science, Meiji University, Kawasaki, Kanagawa 214-8571, Japan
Interests: artificial intelligence; knowledge extraction; rule extraction; transparency of deep learning neural networks; medical informatics
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Special Issue Information

Dear Colleagues,

This Special Issue focuses on innovative biomedical informatics using advanced AI methods to:

  1. Enhance performance through human–robot interactions;
  2. Enhance performance using computer vision in biomedical applications;
  3. Enhance performance through Intelligent Biosensor Integration;
  4. Enhance performance through the Brain–Computer Interface (BCI);
  5. Implement new rehabilitation robotics from the perspective of mood/mental/neurological disorders.

AI technology is key in all of the above-mentioned areas.

This Special Issue also welcomes biomedical informatics-related contributions on the following topics:

  • Neural control movements;
  • Body–machine interfaces;
  • Wearable systems;
  • Artificial intelligence and computer vision.

Prof. Dr. Yoichi Hayashi
Prof. Dr. Antonio Lanata
Guest Editors

Manuscript Submission Information

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Keywords

  • enhance performance
  • computational biology
  • biomedical informatics
  • biomedical applications
  • intelligent biosensor integration
  • body–machine interfaces

Published Papers (1 paper)

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Research

16 pages, 4901 KiB  
Article
Validation of a Biomechanical Injury and Disease Assessment Platform Applying an Inertial-Based Biosensor and Axis Vector Computation
by Wangdo Kim, Emir A. Vela, Sean S. Kohles, Victor Huayamave and Oscar Gonzalez
Electronics 2023, 12(17), 3694; https://doi.org/10.3390/electronics12173694 - 31 Aug 2023
Viewed by 1156
Abstract
Inertial kinetics and kinematics have substantial influences on human biomechanical function. A new algorithm for Inertial Measurement Unit (IMU)-based motion tracking is presented in this work. The primary aims of this paper are to combine recent developments in improved biosensor technology with mainstream [...] Read more.
Inertial kinetics and kinematics have substantial influences on human biomechanical function. A new algorithm for Inertial Measurement Unit (IMU)-based motion tracking is presented in this work. The primary aims of this paper are to combine recent developments in improved biosensor technology with mainstream motion-tracking hardware to measure the overall performance of human movement based on joint axis-angle representations of limb rotation. This work describes an alternative approach to representing three-dimensional rotations using a normalized vector around which an identified joint angle defines the overall rotation, rather than a traditional Euler angle approach. Furthermore, IMUs allow for the direct measurement of joint angular velocities, offering the opportunity to increase the accuracy of instantaneous axis of rotation estimations. Although the axis-angle representation requires vector quotient algebra (quaternions) to define rotation, this approach may be preferred for many graphics, vision, and virtual reality software applications. The analytical method was validated with laboratory data gathered from an infant dummy leg’s flexion and extension knee movements and applied to a living subject’s upper limb movement. The results showed that the novel approach could reasonably handle a simple case and provide a detailed analysis of axis-angle migration. The described algorithm could play a notable role in the biomechanical analysis of human joints and offers a harbinger of IMU-based biosensors that may detect pathological patterns of joint disease and injury. Full article
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