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Human Movement Monitoring Using Wearable Sensor Technology—2nd Edition

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

Deadline for manuscript submissions: 20 May 2025 | Viewed by 1738

Special Issue Editor


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Guest Editor
Sports Performance, Recovery, Injury & New Technologies (SPRINT) Research Centre, School of Behavioural and Health Sciences, Australian Catholic University, Melbourne, VIC 4014, Australia
Interests: biomechanics; musculoskeletal modeling; human locomotion; muscle and joint function; predictive simulation; sports science; orthopedic research

Special Issue Information

Dear Colleagues,

Three-dimensional motion capture has been widely used for quantifying human movement during various activities. While the motion capture technique is arguably the gold standard for conducting a detailed analysis of human motion, the cost of equipment and the requirement of specialized laboratories prevent it from having a greater impact. Wearable sensors, such as inertial measurement units (IMU), have increasingly attracted researchers’ attention because of their simplicity and ability to collect data in the field.

The goal of this Special Issue is to show how wearable sensors can be used to advance our knowledge in human movement analysis. With the increase in technology and computational power, the potential of wearable sensors for human motion is yet to be unlocked. The emphasis of this Special Issue is placed on real-world applications of wearable sensors in the areas of human movement. Applications of interest include (but are not limited to) the following:

  • Inertial sensor data validation during various activities (e.g., walking, running, jumping, and cycling);
  • Clinical applications (e.g., elderly fall prevention, rehabilitation, and movement abnormalities, such as stroke and cerebral palsy);
  • Workplace musculoskeletal injury prevention;
  • Sport performance and injury;
  • Developments of advanced sensor fusion algorithms.

Dr. Yi-Chung Lin
Guest Editor

Manuscript Submission Information

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Keywords

  • wearable sensors
  • human movement
  • rehabilitation
  • workplace injury
  • posture
  • sport performance
  • sport injury

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Related Special Issue

Published Papers (3 papers)

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Research

10 pages, 1219 KiB  
Article
Using an Electronic Goniometer to Assess the Influence of Single-Application Kinesiology Taping on Unstable Shoulder Proprioception and Function
by Ewa Bręborowicz, Izabela Olczak, Przemysław Lubiatowski, Piotr Ogrodowicz, Marta Ślęzak, Maciej Bręborowicz and Leszek Romanowski
Sensors 2025, 25(7), 2326; https://doi.org/10.3390/s25072326 - 6 Apr 2025
Viewed by 359
Abstract
Background: Glenohumeral joint instability is associated with a proprioception deficit. Joint position sense can be improved through targeted exercises and kinesiology taping (KT). While previous studies have examined the effects of KT on proprioception, most have focused on the knee joint, with limited [...] Read more.
Background: Glenohumeral joint instability is associated with a proprioception deficit. Joint position sense can be improved through targeted exercises and kinesiology taping (KT). While previous studies have examined the effects of KT on proprioception, most have focused on the knee joint, with limited research on unstable shoulder joints. Most studies have used commonly available equipment (e.g., the Biodex system). An electronic goniometer, the “Propriometer”, is a useful tool for assessing proprioception in shoulder joint instability; however, its application in evaluating the effects of KT on shoulder proprioception remains unexplored. This study aimed to (1) assess the usability of the Propriometer for evaluating the effects of KT on unstable shoulders and (2) determine the impact of a single KT application on joint position sense and limb function in individuals with anterior, post-traumatic shoulder joint instability. Methods and Materials: The study included 30 individuals with anterior, unilateral, post-traumatic shoulder joint instability (8 women, 22 men, mean age 26 years). A control group consisted of 35 healthy volunteers (9 women, 26 men, mean age 24 years). Proprioception assessment (active joint position reproduction evaluation) was performed in both groups using the Propriometer, which measures joint position in real time with an accuracy of 0.1° across all axes. The study methodology was validated and used to examine shoulder proprioception. The current study focused on assessing the effects of KT, which had not been previously tested with this device Assessments were conducted before KT application and three days’ post-application. Additionally, patients completed the Western Ontario Shoulder Instability Index (WOSI) self-assessment questionnaire before and three days after the therapy. Results: Results of the mean joint position reproduction error indicate a proprioceptive deficit in patients with shoulder joint instability. However, the analyzed KT application did not show a significant change in the magnitude of the active joint position reproduction error. Conversely, KT therapy significantly improved patients’ subjective assessment of shoulder function and stability as measured by the WOSI. Conclusions: The Propriometer goniometer and testing methodology are effective tools for assessing the impact of KT on proprioception in shoulder instability. While KT application did not significantly influence shoulder proprioception, it did improve patients’ perceived joint stability and function. Full article
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23 pages, 10659 KiB  
Article
A Fast and Low-Impact Embedded Orientation Correction Algorithm for Hand Gesture Recognition Armbands
by Andrea Mongardi, Fabio Rossi, Andrea Prestia, Paolo Motto Ros and Danilo Demarchi
Sensors 2025, 25(7), 2188; https://doi.org/10.3390/s25072188 - 30 Mar 2025
Viewed by 296
Abstract
Hand gesture recognition is a prominent topic in the recent literature, with surface ElectroMyoGraphy (sEMG) recognized as a key method for wearable Human–Machine Interfaces (HMIs). However, sensor placement still significantly impacts systems performance. This study addresses sensor displacement by introducing a fast and [...] Read more.
Hand gesture recognition is a prominent topic in the recent literature, with surface ElectroMyoGraphy (sEMG) recognized as a key method for wearable Human–Machine Interfaces (HMIs). However, sensor placement still significantly impacts systems performance. This study addresses sensor displacement by introducing a fast and low-impact orientation correction algorithm for sEMG-based HMI armbands. The algorithm includes a calibration phase to estimate armband orientation and real-time data correction, requiring only two distinct hand gestures in terms of sEMG activation. This ensures hardware and database independence and eliminates the need for model retraining, as data correction occurs prior to classification or prediction. The algorithm was implemented in a hand gesture HMI system featuring a custom seven-channel sEMG armband with an Artificial Neural Network (ANN) capable of recognizing nine gestures. Validation demonstrated its effectiveness, achieving 93.36% average prediction accuracy with arbitrary armband wearing orientation. The algorithm also has minimal impact on power consumption and latency, requiring just an additional 500 μW and introducing a latency increase of 408 μs. These results highlight the algorithm’s efficacy, general applicability, and efficiency, presenting it as a promising solution to the electrode-shift issue in sEMG-based HMI applications. Full article
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11 pages, 1555 KiB  
Article
Impact of Playing Position on Competition External Load in Professional Padel Players Using Inertial Devices
by Ricardo Miralles, José F. Guzmán, Jesús Ramón-Llin and Rafael Martínez-Gallego
Sensors 2025, 25(3), 800; https://doi.org/10.3390/s25030800 - 29 Jan 2025
Cited by 1 | Viewed by 783
Abstract
Padel is a racket sport that has grown internationally, both in the number of players and in the number of competitions. Inertial measurement devices enable a comprehensive analysis of competitive load in padel by providing kinematic variables that enhance players’ performance in this [...] Read more.
Padel is a racket sport that has grown internationally, both in the number of players and in the number of competitions. Inertial measurement devices enable a comprehensive analysis of competitive load in padel by providing kinematic variables that enhance players’ performance in this discipline. This study aimed to analyse the external load variables recorded with an inertial device in elite padel players, comparing metrics based on the players’ positions (left and right sides of the court). A total of 83 players were monitored during 23 matches of the professional circuit. The results revealed specific load metrics, including distance covered, frequency of accelerations and decelerations per hour, maximum speeds reached, and acceleration profiles relative to distance covered, which were all measured using the Wimu Pro™ device. Left-side players showed more frequent accelerations and decelerations per hour compared to right-side players. The results of this study will, on one hand, enable the adjustment of new specific parameters for professional padel training, such as acceleration and deceleration profiles, player load, and distances covered at explosive speeds. On the other hand, the results will provide a more objective evaluation of padel players’ performance based on their positions. Full article
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