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Sensor Technologies and Their Applications in Biomechanics
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Sensor Technologies and Their Applications in Biomechanics

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

Deadline for manuscript submissions: closed (25 July 2024) | Viewed by 4319

Special Issue Editor

Dr. Amy B. Silder

E-Mail Website
Guest Editor
Warfighter Performance Department, Naval Health Research Center, San Diego, CA 92106, USA
Interests: musculoskeletal injury and recovery; experimental design and data analysis; wearable sensors; computer modeling of human movement

Special Issue Information

Dear Colleagues,

This Special Issue aims to provide a comprehensive overview of sensor technologies and their applications in biomechanics. We seek research articles and reviews that provide insight into the design, development, and validation of sensors for biomechanics applications, as well as mathematical modeling and machine learning algorithms for medical, healthcare, and sports applications. Topics of interest include (but are not limited to):

  • Gyroscopes;
  • Force sensors;
  • Ultrasound sensors;
  • Gait analysis;
  • Wireless sensors for biomechanics applications;
  • The continuous monitoring of human motion in rehabilitation and sports;
  • Biomechanical sensors in disease assessment, functional diagnosis, treatment, and rehabilitation;
  • Data processing, simulation, and validation of sensors for biomechanics applications.

Dr. Amy B. Silder
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.

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

11 pages, 5160 KiB  
Article
Methods for Evaluating Tibial Accelerations and Spatiotemporal Gait Parameters during Unsupervised Outdoor Movement
by Amy Silder, Ethan J. Wong, Brian Green, Nicole H. McCloughan and Matthew C. Hoch
Sensors 2024, 24(20), 6667; https://doi.org/10.3390/s24206667 - 16 Oct 2024
Viewed by 1404
Abstract
The purpose of this paper is to introduce a method of measuring spatiotemporal gait patterns, tibial accelerations, and heart rate that are matched with high resolution geographical terrain features using publicly available data. These methods were demonstrated using data from 218 Marines, who [...] Read more.
The purpose of this paper is to introduce a method of measuring spatiotemporal gait patterns, tibial accelerations, and heart rate that are matched with high resolution geographical terrain features using publicly available data. These methods were demonstrated using data from 218 Marines, who completed loaded outdoor ruck hikes between 5–20 km over varying terrain. Each participant was instrumented with two inertial measurement units (IMUs) and a GPS watch. Custom code synchronized accelerometer and positional data without a priori sensor synchronization, calibrated orientation of the IMUs in the tibial reference frame, detected and separated only periods of walking or running, and computed acceleration and spatiotemporal outcomes. GPS positional data were georeferenced with geographic information system (GIS) maps to extract terrain features such as slope, altitude, and surface conditions. This paper reveals the ease at which similar data can be gathered among relatively large groups of people with minimal setup and automated data processing. The methods described here can be adapted to other populations and similar ground-based activities such as skiing or trail running. Full article
(This article belongs to the Special Issue Sensor Technologies and Their Applications in Biomechanics)
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18 pages, 4573 KiB  
Article
Analysis of Musculoskeletal Biomechanics of Lower Limbs of Drivers in Pedal-Operation States
by Song Zhang, Hailin Kui, Xiangyu Liu and Zhonglin Zhang
Sensors 2023, 23(21), 8897; https://doi.org/10.3390/s23218897 - 1 Nov 2023
Cited by 3 | Viewed by 2015
Abstract
In this study, to establish the biomechanical characteristics of commercial vehicle drivers’ muscles and bones while operating the three pedals, a driver pedal-operation simulator was built, and the real-life situation was reconstructed in OpenSim 3.3 software. We set up three seat heights to [...] Read more.
In this study, to establish the biomechanical characteristics of commercial vehicle drivers’ muscles and bones while operating the three pedals, a driver pedal-operation simulator was built, and the real-life situation was reconstructed in OpenSim 3.3 software. We set up three seat heights to investigate the drivers’ lower limbs, and the research proceeded in two parts: experiment and simulation. Chinese adult males in the 95th percentile were selected as the research participants. In the experiment, Delsys wireless surface electromyography (EMG) sensors were used to collect the EMG signals of the four main muscle groups of the lower limbs when the drivers operated the three pedals. Then, we analyzed the muscle activation and the degree of muscle fatigue. The simulation was based on OpenSim software to analyze the driver’s lower limb joint angles and joint torque. The results show that the activation of the hamstrings, gastrocnemius, and rectus femoris muscles were higher in the four muscle groups. In respect of torque, in most cases, hip joint torque > knee joint torque > ankle joint torque. The knee joint angles were the largest, and the ankle joint angles changed the most. The experimental results provide a reference for improving drivers’ handling comfort in commercial vehicles and provide theoretical bases for cab design and layout optimization. Full article
(This article belongs to the Special Issue Sensor Technologies and Their Applications in Biomechanics)
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