sensors-logo

Journal Browser

Journal Browser

IMU Sensors, Techniques and Methods for Movement Analysis in the Context of Health Monitoring and Clinical Applications

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

Deadline for manuscript submissions: closed (15 October 2022) | Viewed by 8292

Special Issue Editor

Department of surgery, Faculty of medicine and health sciences, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
Interests: wearable sensors (IMU, GPS, PPG, EMG) for activity and mobility monitoring; signal processing; validation and usability studies

Special Issue Information

Dear Colleagues,

Wearable systems integrating multiple sensing technologies are now more than ever present in research and clinical environments. Wearable systems using inertial sensors offer unique opportunities to capture movement-related metrics that can be used as outcomes for health monitoring and clinical applications. Health monitoring and clinical applications encompass both synchronous and asynchronous use of metrics derived from IMU data in varying contexts and settings with validated algorithms. The usability of IMU-based wearable systems in these contexts and settings and the validity of the measures obtained are key to their acceptance and large-scale use. We are pleased to invite you to contribute to this Special Issue of Sensors entitled “IMU Sensors, Techniques, and Methods for Movement Analysis in the Context of Health Monitoring and Clinical Applications”. This Special Issue aims to bring together contributions concerning the use of wearable IMUs and their underlying sensors, sensing techniques, and signal processing methods and algorithms for quantitatively assessing gait, posture, joint kinematics, physical activity, energy expenditure, sleep, mood, movements disorders, assistive technologies, and their integration in the context of health monitoring and clinical applications.

We will accept contributions in the form of either full-length research papers, systematic reviews or papers reporting new results on:

  • Empirical demonstration of IMU sensor data use cases and usability for health monitoring and clinical applications;
  • Algorithm development with validation results leveraging IMU sensor data and other sources for health monitoring and clinical applications;
  • Innovative data fusion strategies and signal processing for enhanced accuracy and precision of IMU sensor data for health monitoring and clinical applications.

Dr. Patrick Boissy
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Wearable systems and inertial sensing
  • IMU, MIMU
  • Gait and joint kinematics
  • Physical activity and energy expenditure
  • Sleep and mood
  • Movement disorders
  • Assistive technologies
  • Accuracy
  • Precision
  • Usability
  • M-health
  • Telehealth
  • Biomechanics

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

17 pages, 1752 KiB  
Article
Stateful Rotor for Continuity of Quaternion and Fast Sensor Fusion Algorithm Using 9-Axis Sensors
by Takashi Kusaka and Takayuki Tanaka
Sensors 2022, 22(20), 7989; https://0-doi-org.brum.beds.ac.uk/10.3390/s22207989 - 19 Oct 2022
Cited by 2 | Viewed by 1925
Abstract
Advances in micro-electro-mechanical systems technology have led to the emergence of compact attitude measurement sensor products that integrate acceleration, magnetometer, and gyroscope sensors on a single chip, making them important devices in the field of three-dimensional (3D) attitude measurement for unmanned aerial vehicles, [...] Read more.
Advances in micro-electro-mechanical systems technology have led to the emergence of compact attitude measurement sensor products that integrate acceleration, magnetometer, and gyroscope sensors on a single chip, making them important devices in the field of three-dimensional (3D) attitude measurement for unmanned aerial vehicles, smartphones, and other devices. Sensor fusion algorithms for posture measurement have become an indispensable technology in cutting-edge research, such as human posture measurement using wearable sensors, and stabilization problems in robot position and posture measurement. We have also developed wearable sensors and powered suits in our previous research. We needed a technology for the real-time measurement of a 3D human body motion. It is known that quaternions can be used to algebraically handle 3D rotations; however, sensor fusion algorithms for three sensors are presently complex. This is because these algorithms deal with the post-rotation attitude (pure quaternions) rather than rotation information (the rotor) to avoid a double covering problem involving the rotor. If we are dealing with rotation, it may be possible to make the algorithm simpler and faster by dealing directly with the rotor. In this study, to solve the double covering problem involving the rotor, we propose a stateful rotor and develop a technique for uniquely determining the time-varying states of the rotor. The proposed stateful rotor guarantees the continuity of the rotor parameters with respect to angular changes, and this paper confirms its effectiveness by simulating two rotations around an arbitrary axis. In addition, we verify experimentally that a fast sensor fusion method using stateful rotor can be used for attitude calculation. Experiments also confirm that the calculated results converge to the desired rotation angle for two spatial rotations around an arbitrary axis. Since the proposed stateful rotor extends and stabilizes the definition of the rotor, it is applicable to any algorithm that deals with time-varying quaternionic rotors. In this research, an algorithm based on a multiply–add operation is designed to reduce computational complexity as a high-speed calculation for embedded systems. This method is theoretically equivalent to other methods, while contributing to power saving and the cost reduction of products. Full article
Show Figures

Figure 1

16 pages, 1612 KiB  
Article
Body-Worn IMU-Based Human Hip and Knee Kinematics Estimation during Treadmill Walking
by Timothy McGrath and Leia Stirling
Sensors 2022, 22(7), 2544; https://0-doi-org.brum.beds.ac.uk/10.3390/s22072544 - 26 Mar 2022
Cited by 13 | Viewed by 4301
Abstract
Traditionally, inertial measurement unit (IMU)-based human joint angle estimation techniques are evaluated for general human motion where human joints explore all of their degrees of freedom. Pure human walking, in contrast, limits the motion of human joints and may lead to unobservability conditions [...] Read more.
Traditionally, inertial measurement unit (IMU)-based human joint angle estimation techniques are evaluated for general human motion where human joints explore all of their degrees of freedom. Pure human walking, in contrast, limits the motion of human joints and may lead to unobservability conditions that confound magnetometer-free IMU-based methods. This work explores the unobservability conditions emergent during human walking and expands upon a previous IMU-based method for the human knee to also estimate human hip angles relative to an assumed vertical datum. The proposed method is evaluated (N=12) in a human subject study and compared against an optical motion capture system. Accuracy of human knee flexion/extension angle (7.87 absolute root mean square error (RMSE)), hip flexion/extension angle (3.70 relative RMSE), and hip abduction/adduction angle (4.56 relative RMSE) during walking are similar to current state-of-the-art self-calibrating IMU methods that use magnetometers. Larger errors of hip internal/external rotation angle (6.27 relative RMSE) are driven by IMU heading drift characteristic of magnetometer-free approaches and non-hinge kinematics of the hip during gait, amongst other error sources. One of these sources of error, soft tissue perturbations during gait, is explored further in the context of knee angle estimation and it was observed that the IMU method may overestimate the angle during stance and underestimate the angle during swing. The presented method and results provide a novel combination of observability considerations, heuristic correction methods, and validation techniques to magnetic-blind, kinematic-only IMU-based skeletal pose estimation during human tasks with degenerate kinematics (e.g., straight line walking). Full article
Show Figures

Figure 1

Back to TopTop