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Inertial Motion Capture and Sensing Technologies

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 9563

Special Issue Editor


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Guest Editor
School of ICT, Robotics & Mechanical Engineering, Hankyong National University, Anseong 17579, Gyeonggi-do, Korea
Interests: inertial motion capture; wearable sensing; wearable robotics; biomedical technologies

Special Issue Information

Dear Colleagues,

Due to the universal presence of motion, motion capture is a central theme of many studies. On the subject of motion capture, our particular interest is the use of inertial sensors. The number of inertial sensor applications is increasing exponentially as these inertial sensors continually shrink in size and cost through the advent of the microelectromechanical systems technology. Inertial sensors have become a key enabling technology in a wide variety of applications.

Although optical motion capture technology via an external infrastructure is regarded as the gold standard by showing a high accuracy, there are several benefits to using inertial motion capture instead of the optical motion capture. Above all, inertial motion capture allows us to overcome inherent in-the-lab limitations of the classical optical motion capture, based on its wearability. This wearability makes ubiquitous measurement possible, which is then linked to the tremendous benefits associated with long-term monitoring of individuals in daily living environments. Furthermore, it is important to remind that inertial motion capture is not only a matter of kinematics but also of kinetics.

The purpose of this Special Issue is to bring together researchers in the field of inertial motion capture and sensing technologies for ubiquitous motion capture and various applications, to share their ideas and approaches and to address innovating solutions, paradigms, and emerging issues in this field in depth. New sensing concepts which are especially suited for inertial motion capture, and new application areas of such concepts, are also welcome.

Prof. Dr. Jung Keun Lee
Guest Editor

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Keywords

  • inertial motion capture
  • inertial sensor
  • human motion
  • wearability
  • kinematics
  • kinetics

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Published Papers (1 paper)

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Research

19 pages, 1105 KiB  
Article
A Portable Smart Fitness Suite for Real-Time Exercise Monitoring and Posture Correction
by Abdul Hannan, Muhammad Zohaib Shafiq, Faisal Hussain and Ivan Miguel Pires
Sensors 2021, 21(19), 6692; https://doi.org/10.3390/s21196692 - 8 Oct 2021
Cited by 19 | Viewed by 8522
Abstract
Fitness and sport have drawn significant attention in wearable and persuasive computing. Physical activities are worthwhile for health, well-being, improved fitness levels, lower mental pressure and tension levels. Nonetheless, during high-power and commanding workouts, there is a high likelihood that physical fitness is [...] Read more.
Fitness and sport have drawn significant attention in wearable and persuasive computing. Physical activities are worthwhile for health, well-being, improved fitness levels, lower mental pressure and tension levels. Nonetheless, during high-power and commanding workouts, there is a high likelihood that physical fitness is seriously influenced. Jarring motions and improper posture during workouts can lead to temporary or permanent disability. With the advent of technological advances, activity acknowledgment dependent on wearable sensors has pulled in countless studies. Still, a fully portable smart fitness suite is not industrialized, which is the central need of today’s time, especially in the Covid-19 pandemic. Considering the effectiveness of this issue, we proposed a fully portable smart fitness suite for the household to carry on their routine exercises without any physical gym trainer and gym environment. The proposed system considers two exercises, i.e., T-bar and bicep curl with the assistance of the virtual real-time android application, acting as a gym trainer overall. The proposed fitness suite is embedded with a gyroscope and EMG sensory modules for performing the above two exercises. It provided alerts on unhealthy, wrong posture movements over an android app and is guided to the best possible posture based on sensor values. The KNN classification model is used for prediction and guidance for the user while performing a particular exercise with the help of an android application-based virtual gym trainer through a text-to-speech module. The proposed system attained 89% accuracy, which is quite effective with portability and a virtually assisted gym trainer feature. Full article
(This article belongs to the Special Issue Inertial Motion Capture and Sensing Technologies)
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