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Inertial Sensor-Based Biomechanical Analysis
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Inertial Sensor-Based Biomechanical Analysis

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

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 20358

Special Issue Editors

Prof. Dr. Michael Skipper Andersen

E-Mail Website
Guest Editor
Department of Materials and Production, Aalborg Universitet, 9220 Aalborg, Denmark
Interests: biomechanics; orthopedics; musculoskeletal modeling; inertial sensor-based biomechanical analysis
Dr. Mark de Zee

E-Mail Website
Guest Editor
Department of Health Science and Technology, Sport Sciences—Performance and Technology, Aalborg University, Denmark
Interests: mining equipment; mining transformation; structural engineering; mechanical engineering; finite element analysis (FEA); testing and measurements; vibrations; modal analysis; signal processing; R&D

Special Issue Information

Dear Colleagues,

The fields of inertial sensor-based motion capture and biomechanical analysis have been developed and applied for quite some time now. To a large extent, biomechanical analysis has traditionally relied on marker-based motion capture, but in recent years the research and development of inertial sensor-based motion capture and abilities to perform biomechanical analysis without the need for measurements of external forces has been opening up the doors for ambulatory biomechanical analysis that was previously infeasible.

The aim of this Special Issue is stimulate further research into inertial sensor-based biomechanical analysis and its applications.

We invite manuscripts for the forthcoming Special Issue entitled: "Inertial Sensor-based Biomechanical Analysis" in all aspects from novel theoretical approaches to applications. Both reviews and original research articles are welcome. Reviews should provide an up-to-date and critical overview of state-of-the-art technologies and both reviews and original research articles should be in the following research fields applied to inertial sensor-based biomechanical analysis:

  • Sensor fusion methodologies tailored to biomechanical analysis
  • Biomechanical modeling and simulation based on inertial sensor data
  • Reliability and validity of the estimated biomechanical quantifies from inertial-based motion capture
  • Applications of inertial sensor-based biomechanical analysis

Dr. Michael Skipper Andersen
Dr. Mark de Zee
Guest Editors

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

  • Biomechanical analysis
  • Inertial sensors
  • Reliability
  • Validation
  • Biomechanical modeling and simulation

Published Papers (6 papers)

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17 pages, 4086 KiB  
Article
The Added Value of Musculoskeletal Simulation for the Study of Physical Performance in Military Tasks
by Ilona Kessels, Bart Koopman, Nico Verdonschot, Marco Marra and Kaj Gijsbertse
Sensors 2021, 21(16), 5588; https://doi.org/10.3390/s21165588 - 19 Aug 2021
Viewed by 2870
Abstract
The performance of military tasks is often exacerbated by additional load carriage, leading to increased physical demand. Previous studies showed that load carriage may lead to increased risk of developing musculoskeletal injuries, a reduction in task speed and mobility, and overall performance degradation. [...] Read more.
The performance of military tasks is often exacerbated by additional load carriage, leading to increased physical demand. Previous studies showed that load carriage may lead to increased risk of developing musculoskeletal injuries, a reduction in task speed and mobility, and overall performance degradation. However, these studies were limited to a non-ambulatory setting, and the underlying causes of performance degradation remain unclear. To obtain insights into the underlying mechanisms of reduced physical performance during load-carrying military activities, this study proposes a combination of IMUs and musculoskeletal modeling. Motion data of military subjects was captured using an Xsens suit during the performance of an agility run under three different load-carrying conditions (no load, 16 kg, and 31 kg). The physical performance of one subject was assessed by means of inertial motion-capture driven musculoskeletal analysis. Our results showed that increased load carriage led to an increase in metabolic power and energy, changes in muscle parameters, a significant increase in completion time and heart rate, and changes in kinematic parameters. Despite the exploratory nature of this study, the proposed approach seems promising to obtain insight into the underlying mechanisms that result in performance degradation during load-carrying military activities. Full article
(This article belongs to the Special Issue Inertial Sensor-Based Biomechanical Analysis)
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9 pages, 1410 KiB  
Article
The ‘Ride’ Feeling during Running under Field Conditions—Objectified with a Single Inertial Measurement Unit
by Sabrina Bräuer, Pierre Kiesewetter, Thomas L. Milani and Christian Mitschke
Sensors 2021, 21(15), 5010; https://doi.org/10.3390/s21155010 - 23 Jul 2021
Cited by 2 | Viewed by 2294
Abstract
Foot rollover and the ‘ride’ feeling that occurs during heel–toe transition during running have been investigated mostly in laboratory settings due to the technical requirements of ‘golden standard’ measurement devices. Hence, the purpose of the current study was to investigate ‘ride’ and rollover [...] Read more.
Foot rollover and the ‘ride’ feeling that occurs during heel–toe transition during running have been investigated mostly in laboratory settings due to the technical requirements of ‘golden standard’ measurement devices. Hence, the purpose of the current study was to investigate ‘ride’ and rollover with a heel cap-mounted inertial measurement unit (IMU) when running under field conditions to get realistic results. Twenty athletes ran on a 1 km outdoor track with five different shoe conditions, only differing in their midsole bending stiffness. The peak angular velocity (PAV) in the sagittal plane of the shoe was analyzed. The subjective evaluation of the ‘ride’ perception during heel–toe transition was rated on a visual analogue scale. The results revealed that PAV and ‘ride’ varied for the different shoes. The regression analysis showed that PAV has a significant impact on the ‘ride’ rating (R2 = 0.952; p = 0.005). The shoe with a medium midsole bending stiffness had the lowest value for PAV (845.6 deg/s) and the best rating of perceived ‘ride’ on average. Our results show that IMU can be used as a low-cost method to investigate the heel–toe transition during field-running. In addition, we found that midsole bending stiffness influenced PAV and the subjective feeling of ‘ride’. Full article
(This article belongs to the Special Issue Inertial Sensor-Based Biomechanical Analysis)
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11 pages, 857 KiB  
Article
Validity of Inertial Sensors for Assessing Balance Kinematics and Mobility during Treadmill-Based Perturbation and Dance Training
by Ernest Kwesi Ofori, Shuaijie Wang and Tanvi Bhatt
Sensors 2021, 21(9), 3065; https://doi.org/10.3390/s21093065 - 28 Apr 2021
Cited by 5 | Viewed by 2119
Abstract
Inertial sensors (IS) enable the kinematic analysis of human motion with fewer logistical limitations than the silver standard optoelectronic motion capture (MOCAP) system. However, there are no data on the validity of IS for perturbation training and during the performance of dance. The [...] Read more.
Inertial sensors (IS) enable the kinematic analysis of human motion with fewer logistical limitations than the silver standard optoelectronic motion capture (MOCAP) system. However, there are no data on the validity of IS for perturbation training and during the performance of dance. The aim of this present study was to determine the concurrent validity of IS in the analysis of kinematic data during slip and trip-like perturbations and during the performance of dance. Seven IS and the MOCAP system were simultaneously used to capture the reactive response and dance movements of fifteen healthy young participants (Age: 18–35 years). Bland Altman (BA) plots, root mean square errors (RMSE), Pearson’s correlation coefficients (R), and intraclass correlation coefficients (ICC) were used to compare kinematic variables of interest between the two systems for absolute equivalency and accuracy. Limits of agreements (LOA) of the BA plots ranged from −0.23 to 0.56 and −0.21 to 0.43 for slip and trip stability variables, respectively. The RMSE for slip and trip stabilities were from 0.11 to 0.20 and 0.11 to 0.16, respectively. For the joint mobility in dance, LOA varied from −6.98–18.54, while RMSE ranged from 1.90 to 13.06. Comparison of IS and optoelectronic MOCAP system for reactive balance and body segmental kinematics revealed that R varied from 0.59 to 0.81 and from 0.47 to 0.85 while ICC was from 0.50 to 0.72 and 0.45 to 0.84 respectively for slip–trip perturbations and dance. Results of moderate to high concurrent validity of IS and MOCAP systems. These results were consistent with results from similar studies. This suggests that IS are valid tools to quantitatively analyze reactive balance and mobility kinematics during slip–trip perturbation and the performance of dance at any location outside, including the laboratory, clinical and home settings. Full article
(This article belongs to the Special Issue Inertial Sensor-Based Biomechanical Analysis)
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34 pages, 1714 KiB  
Article
Optimization-Based Online Initialization and Calibration of Monocular Visual-Inertial Odometry Considering Spatial-Temporal Constraints
by Weibo Huang, Weiwei Wan and Hong Liu
Sensors 2021, 21(8), 2673; https://doi.org/10.3390/s21082673 - 10 Apr 2021
Cited by 16 | Viewed by 3380
Abstract
The online system state initialization and simultaneous spatial-temporal calibration are critical for monocular Visual-Inertial Odometry (VIO) since these parameters are either not well provided or even unknown. Although impressive performance has been achieved, most of the existing methods are designed for filter-based VIOs. [...] Read more.
The online system state initialization and simultaneous spatial-temporal calibration are critical for monocular Visual-Inertial Odometry (VIO) since these parameters are either not well provided or even unknown. Although impressive performance has been achieved, most of the existing methods are designed for filter-based VIOs. For the optimization-based VIOs, there is not much online spatial-temporal calibration method in the literature. In this paper, we propose an optimization-based online initialization and spatial-temporal calibration method for VIO. The method does not need any prior knowledge about spatial and temporal configurations. It estimates the initial states of metric-scale, velocity, gravity, Inertial Measurement Unit (IMU) biases, and calibrates the coordinate transformation and time offsets between the camera and IMU sensors. The work routine of the method is as follows. First, it uses a time offset model and two short-term motion interpolation algorithms to align and interpolate the camera and IMU measurement data. Then, the aligned and interpolated results are sent to an incremental estimator to estimate the initial states and the spatial–temporal parameters. After that, a bundle adjustment is additionally included to improve the accuracy of the estimated results. Experiments using both synthetic and public datasets are performed to examine the performance of the proposed method. The results show that both the initial states and the spatial-temporal parameters can be well estimated. The method outperforms other contemporary methods used for comparison. Full article
(This article belongs to the Special Issue Inertial Sensor-Based Biomechanical Analysis)
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12 pages, 3354 KiB  
Communication
Portable Gait Lab: Estimating Over-Ground 3D Ground Reaction Forces Using Only a Pelvis IMU
by Mohamed Irfan Mohamed Refai, Bert-Jan F. van Beijnum, Jaap H. Buurke and Peter H. Veltink
Sensors 2020, 20(21), 6363; https://doi.org/10.3390/s20216363 - 07 Nov 2020
Cited by 4 | Viewed by 4622
Abstract
As an alternative to force plates, an inertial measurement unit (IMU) at the pelvis can offer an ambulatory method for measuring total center of mass (CoM) accelerations and, thereby, the ground reaction forces (GRF) during gait. The challenge here is to estimate the [...] Read more.
As an alternative to force plates, an inertial measurement unit (IMU) at the pelvis can offer an ambulatory method for measuring total center of mass (CoM) accelerations and, thereby, the ground reaction forces (GRF) during gait. The challenge here is to estimate the 3D components of the GRF. We employ a calibration procedure and an error state extended Kalman filter based on an earlier work to estimate the instantaneous 3D GRF for different over-ground walking patterns. The GRF were then expressed in a body-centric reference frame, to enable an ambulatory setup not related to a fixed global frame. The results were validated with ForceShoesTM, and the average error in estimating instantaneous shear GRF was 5.2 ± 0.5% of body weight across different variable over-ground walking tasks. The study shows that a single pelvis IMU can measure 3D GRF in a minimal and ambulatory manner during over-ground gait. Full article
(This article belongs to the Special Issue Inertial Sensor-Based Biomechanical Analysis)
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11 pages, 2540 KiB  
Letter
Efficacy of Inertial Measurement Units in the Evaluation of Trunk and Hand Kinematics in Baseball Hitting
by Niroshan G. Punchihewa, Shigeaki Miyazaki, Etsuo Chosa and Go Yamako
Sensors 2020, 20(24), 7331; https://doi.org/10.3390/s20247331 - 20 Dec 2020
Cited by 12 | Viewed by 3929
Abstract
Baseball hitting is a highly dynamic activity, and advanced methods are required to accurately obtain biomechanical data. Inertial measurement units (IMUs) can capture the motion of body segments at high sampling rates both indoor and outdoor. The bat rotates around the longitudinal axis [...] Read more.
Baseball hitting is a highly dynamic activity, and advanced methods are required to accurately obtain biomechanical data. Inertial measurement units (IMUs) can capture the motion of body segments at high sampling rates both indoor and outdoor. The bat rotates around the longitudinal axis of the body; thus, trunk motion plays a key role in baseball hitting. Segmental coordination is important in transferring power to a moving ball and, therefore, useful in evaluating swing kinematics. The current study aimed to investigate the validity and reliability of IMUs with a sampling rate of 1000 Hz attached on the pelvis, thorax, and hand in assessing trunk and hand motion during baseball hitting. Results obtained using the IMU and optical motion capture system (OMCS) were compared. Angular displacements of the trunk segments and spine joint had a root mean square error of <5°. The mean absolute error of the angular velocities was ≤5%. The intra-class correlation coefficient (>0.950) had excellent reliability for trunk kinematics along the longitudinal-axis. Hand velocities at peak and impact corresponded to the values determined using the OMCS. In conclusion, IMUs with high sampling rates are effective in evaluating trunk and hand movement coordination during hitting motion. Full article
(This article belongs to the Special Issue Inertial Sensor-Based Biomechanical Analysis)
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