Research

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9 pages, 1345 KiB

Open AccessArticle

The Effect of Breathing Laterality on Hip Roll Kinematics in Submaximal Front Crawl Swimming

by John M. Barden and Mike V. Barber

Sensors 2022, 22(6), 2324; https://0-doi-org.brum.beds.ac.uk/10.3390/s22062324 - 17 Mar 2022

Cited by 1 | Viewed by 1801

The purpose of this study was to determine the effect of breathing laterality on hip roll kinematics in submaximal front crawl swimming. Eighteen elite competitive swimmers performed three 100 m front crawl trials at a consistent sub-maximal speed (70% of seasonal best time) [...] Read more.

The purpose of this study was to determine the effect of breathing laterality on hip roll kinematics in submaximal front crawl swimming. Eighteen elite competitive swimmers performed three 100 m front crawl trials at a consistent sub-maximal speed (70% of seasonal best time) in a 25 m pool. Each trial was performed with one of three different breathing conditions: (1) unilateral breathing (preferred side), (2) bilateral breathing (alternating left/right-side every 3 strokes) and (3) simulated non-breathing using a swim snorkel. A waist-mounted triaxial accelerometer was used to determine continuous hip roll angle throughout the trial, from which peak hip roll angles (Ө) and average angular velocities (ω) were calculated. Two-way repeated measures ANOVAs were used to identify significant main effects for laterality (preferred vs. non-preferred breathing sides) and condition (unilateral, bilateral and snorkel breathing) for both Ө and ω. Peak hip roll to the preferred side was significantly greater (p < 0.001) in the unilateral condition, while ω to the non-preferred side was significantly greater in the unilateral (p < 0.01) and bilateral (p < 0.04) conditions. Significant same-side differences were also found between the different breathing conditions. The results demonstrate that breathing laterality affects hip roll kinematics at submaximal speeds, and that unilateral and snorkel breathing are associated with the least and most symmetric hip roll kinematics, respectively. The findings show that a snorkel effectively balances and controls bilateral hip rotation at submaximal speeds that are consistent with training, which may help to minimize and/or correct roll asymmetries that are the result of unilateral breathing. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomechanical Monitoring in Sport)

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14 pages, 1731 KiB

Open AccessArticle

Influence of Turn Cycle Structure on Performance of Elite Alpine Skiers Assessed through an IMU in Different Slalom Course Settings

by Carla Pérez-Chirinos Buxadé, Josep Maria Padullés Riu, Dani Gavaldà Castet, Michela Trabucchi, Bruno Fernández-Valdés, Sílvia Tuyà Viñas and Gerard Moras Feliu

Sensors 2022, 22(3), 902; https://0-doi-org.brum.beds.ac.uk/10.3390/s22030902 - 25 Jan 2022

Cited by 3 | Viewed by 3454

Abstract

Small differences in turn cycle structure, invisible to the naked eye, could be decisive in improving descent performance. The aim of this study was to assess the influence of turn cycle structure on the performance of elite alpine skiers using an inertial measurement [...] Read more.

Small differences in turn cycle structure, invisible to the naked eye, could be decisive in improving descent performance. The aim of this study was to assess the influence of turn cycle structure on the performance of elite alpine skiers using an inertial measurement unit (IMU) in different slalom (SL) course settings. Four SL courses were set: a flat-turned (FT), a steep-turned (ST), a flat-straighter (FS) and a steep-straighter (SS). Five elite alpine skiers (21.2 ± 3.3 years, 180.2 ± 5.6 cm, 72.8 ± 6.6 kg) completed several runs at maximum speed for each SL course. A total of 77 runs were obtained. Fast total times correlate with a longer initiation (INI) time in FT, a shorter steering time out of the turn (STE_OUT) in the FT and FS and a shorter total steering time (STE_IN+OUT) in the FT and SS courses. The linear mixed model used for the analysis revealed that in the FT-course for each second increase in the INI time, the total time is reduced by 0.45 s, and for every one-second increase in the STE_OUT and STE_IN+OUT times, the total time increases by 0.48 s and 0.31 s, respectively. Thus, to enhance descent performance, the skier should lengthen the INI time and shorten the STE_OUT and STE_IN+OUT time. Future studies could use an IMU to detect turn phases and analyze them using the other built-in sensors. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomechanical Monitoring in Sport)

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11 pages, 1184 KiB

Open AccessArticle

Quantification of Head Acceleration Events in Rugby League: An Instrumented Mouthguard and Video Analysis Pilot Study

by James Tooby, Dan Weaving, Marwan Al-Dawoud and Gregory Tierney

Sensors 2022, 22(2), 584; https://0-doi-org.brum.beds.ac.uk/10.3390/s22020584 - 13 Jan 2022

Cited by 18 | Viewed by 3323

Abstract

Instrumented mouthguards (iMG) were used to collect head acceleration events (HAE) in men’s professional rugby league matches. Peak linear acceleration (PLA), peak angular acceleration (PAA) and peak change in angular velocity (ΔPAV) were collected using custom-fit iMG set with a 5 g single [...] Read more.

Instrumented mouthguards (iMG) were used to collect head acceleration events (HAE) in men’s professional rugby league matches. Peak linear acceleration (PLA), peak angular acceleration (PAA) and peak change in angular velocity (ΔPAV) were collected using custom-fit iMG set with a 5 g single iMG-axis recording threshold. iMG were fitted to ten male Super League players for thirty-one player matches. Video analysis was conducted on HAE to identify the contact event; impacted player; tackle stage and head loading type. A total of 1622 video-verified HAE were recorded. Approximately three-quarters of HAE (75.7%) occurred below 10 g. Most (98.2%) HAE occurred during tackles (59.3% to tackler; 40.7% to ball carrier) and the initial collision stage of the tackle (43.9%). The initial collision stage resulted in significantly greater PAA and ΔPAV than secondary contact and play the ball tackle stages (p < 0.001). Indirect HAE accounted for 29.8% of HAE and resulted in significantly greater ΔPAV (p < 0.001) than direct HAE, but significantly lower PLA (p < 0.001). Almost all HAE were sustained in the tackle, with the majority occurring during the initial collision stage, making it an area of focus for the development of player protection strategies for both ball carriers and tacklers. League-wide and community-level implementation of iMG could enable a greater understanding of head acceleration exposure between playing positions, cohorts, and levels of play. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomechanical Monitoring in Sport)

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15 pages, 3862 KiB

Open AccessArticle

Kinematic Determination of the Aerial Phase in Ski Jumping

by Ola Elfmark, Gertjan Ettema, Petter Jølstad and Matthias Gilgien

Sensors 2022, 22(2), 540; https://0-doi-org.brum.beds.ac.uk/10.3390/s22020540 - 11 Jan 2022

Cited by 8 | Viewed by 2057

Abstract

The purpose of this study was to find a generic method to determine the aerial phase of ski jumping in which the athlete is in a steady gliding condition, commonly known as the ‘stable flight’ phase. The aerial phase of ski jumping was [...] Read more.

The purpose of this study was to find a generic method to determine the aerial phase of ski jumping in which the athlete is in a steady gliding condition, commonly known as the ‘stable flight’ phase. The aerial phase of ski jumping was investigated from a physical point mass, rather than an athlete–action-centered perspective. An extensive data collection using a differential Global Navigation Satellite System (dGNSS) was carried out in four different hill sizes. A total of 93 jumps performed by 19 athletes of performance level, ranging from junior to World Cup, were measured. Based on our analysis, we propose a generic algorithm that identifies the stable flight based on steady glide aerodynamic conditions, independent of hill size and the performance level of the athletes. The steady gliding is defined as the condition in which the rate-of-change in the lift-to-drag-ratio (

L D

-ratio) varies within a narrow band-width described by a threshold

τ

. For this study using dGNSS,

τ

amounted to

0.01

s

⁻¹, regardless of hill size and performance level. While the absolute value of

τ

may vary when measuring with other sensors, we argue that the methodology and algorithm proposed to find the start and end of a steady glide (stable flight) could be used in future studies as a generic definition and help clarify the communication of results and enable more precise comparisons between studies. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomechanical Monitoring in Sport)

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11 pages, 1164 KiB

Open AccessArticle

Continuous Tracking of Foot Strike Pattern during a Maximal 800-Meter Run

by Kathryn A. Farina, Alan R. Needle and Herman van Werkhoven

Sensors 2021, 21(17), 5782; https://0-doi-org.brum.beds.ac.uk/10.3390/s21175782 - 27 Aug 2021

Cited by 2 | Viewed by 1878

Abstract

(1) Background: Research into foot strike patterns (FSP) has increased due to its potential influence on performance and injury reduction. The purpose of this study was to evaluate changes in FSP throughout a maximal 800-m run using a conformable inertial measurement unit attached [...] Read more.

(1) Background: Research into foot strike patterns (FSP) has increased due to its potential influence on performance and injury reduction. The purpose of this study was to evaluate changes in FSP throughout a maximal 800-m run using a conformable inertial measurement unit attached to the foot; (2) Methods: Twenty-one subjects (14 female, 7 male; 23.86 ± 4.25 y) completed a maximal 800-m run while foot strike characteristics were continually assessed. Two measures were assessed across 100-m intervals: the percentage of rearfoot strikes (FSP_%RF), and foot strike angle (FSA). The level of significance was set to p ≤ 0.05; (3) Results: There were no differences in FSP_%RF throughout the run. Significant differences were seen between curve and straight intervals for FSA_AVE (F [1, 20] = 18.663, p < 0.001, η_p² = 0.483); (4) Conclusions: Participants displayed decreased FSA, likely indicating increased plantarflexion, on the curve compared to straight intervals. The analyses of continuous variables, such as FSA, allow for the detection of subtle changes in foot strike characteristics, which is not possible with discrete classifiers, such as FSP_%RF. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomechanical Monitoring in Sport)

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13 pages, 1309 KiB

Open AccessArticle

Validity of a Magnet-Based Timing System Using the Magnetometer Built into an IMU

by Carla Pérez-Chirinos Buxadé, Bruno Fernández-Valdés, Mónica Morral-Yepes, Sílvia Tuyà Viñas, Josep Maria Padullés Riu and Gerard Moras Feliu

Sensors 2021, 21(17), 5773; https://0-doi-org.brum.beds.ac.uk/10.3390/s21175773 - 27 Aug 2021

Cited by 9 | Viewed by 2609

Abstract

Inertial measurement units (IMUs) represent a technology that is booming in sports right now. The aim of this study was to evaluate the validity of a new application on the use of these wearable sensors, specifically to evaluate a magnet-based timing system (M-BTS) [...] Read more.

Inertial measurement units (IMUs) represent a technology that is booming in sports right now. The aim of this study was to evaluate the validity of a new application on the use of these wearable sensors, specifically to evaluate a magnet-based timing system (M-BTS) for timing short-duration sports actions using the magnetometer built into an IMU in different sporting contexts. Forty-eight athletes (22.7 ± 3.3 years, 72.2 ± 10.3 kg, 176.9 ± 8.5 cm) and eight skiers (17.4 ± 0.8 years, 176.4 ± 4.9 cm, 67.7 ± 2.0 kg) performed a 60-m linear sprint running test and a ski slalom, respectively. The M-BTS consisted of placing several magnets along the course in both contexts. The magnetometer built into the IMU detected the peak-shaped magnetic field when passing near the magnets at a certain speed. The time between peaks was calculated. The system was validated with photocells. The 95% error intervals for the total times were less than 0.077 s for the running test and 0.050 s for the ski slalom. With the M-BTS, future studies could select and cut the signals belonging to the other sensors that are integrated in the IMU, such as the accelerometer and the gyroscope. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomechanical Monitoring in Sport)

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14 pages, 2951 KiB

Open AccessArticle

Moving the Lab into the Mountains: A Pilot Study of Human Activity Recognition in Unstructured Environments

by Brian Russell, Andrew McDaid, William Toscano and Patria Hume

Sensors 2021, 21(2), 654; https://0-doi-org.brum.beds.ac.uk/10.3390/s21020654 - 19 Jan 2021

Cited by 13 | Viewed by 2807

Abstract

Goal: To develop and validate a field-based data collection and assessment method for human activity recognition in the mountains with variations in terrain and fatigue using a single accelerometer and a deep learning model. Methods: The protocol generated an unsupervised labelled dataset of [...] Read more.

Goal: To develop and validate a field-based data collection and assessment method for human activity recognition in the mountains with variations in terrain and fatigue using a single accelerometer and a deep learning model. Methods: The protocol generated an unsupervised labelled dataset of various long-term field-based activities including run, walk, stand, lay and obstacle climb. Activity was voluntary so transitions could not be determined a priori. Terrain variations included slope, crossing rivers, obstacles and surfaces including road, gravel, clay, mud, long grass and rough track. Fatigue levels were modulated between rested to physical exhaustion. The dataset was used to train a deep learning convolutional neural network (CNN) capable of being deployed on battery powered devices. The human activity recognition results were compared to a lab-based dataset with 1,098,204 samples and six features, uniform smooth surfaces, non-fatigued supervised participants and activity labelling defined by the protocol. Results: The trail run dataset had 3,829,759 samples with five features. The repetitive activities and single instance activities required hyper parameter tuning to reach an overall accuracy 0.978 with a minimum class precision for the one-off activity (climbing gate) of 0.802. Conclusion: The experimental results showed that the CNN deep learning model performed well with terrain and fatigue variations compared to the lab equivalents (accuracy 97.8% vs. 97.7% for trail vs. lab). Significance: To the authors knowledge this study demonstrated the first successful human activity recognition (HAR) in a mountain environment. A robust and repeatable protocol was developed to generate a validated trail running dataset when there were no observers present and activity types changed on a voluntary basis across variations in terrain surface and both cognitive and physical fatigue levels. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomechanical Monitoring in Sport)

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Review

Jump to: Research

20 pages, 534 KiB

Open AccessReview

Mechanical Power in Endurance Running: A Scoping Review on Sensors for Power Output Estimation during Running

by Diego Jaén-Carrillo, Luis E. Roche-Seruendo, Antonio Cartón-Llorente, Rodrigo Ramírez-Campillo and Felipe García-Pinillos

Sensors 2020, 20(22), 6482; https://0-doi-org.brum.beds.ac.uk/10.3390/s20226482 - 13 Nov 2020

Cited by 19 | Viewed by 4429

Abstract

Mechanical power may act as a key indicator for physiological and mechanical changes during running. In this scoping review, we examine the current evidences about the use of power output (PW) during endurance running and the different commercially available wearable sensors to assess [...] Read more.

Mechanical power may act as a key indicator for physiological and mechanical changes during running. In this scoping review, we examine the current evidences about the use of power output (PW) during endurance running and the different commercially available wearable sensors to assess PW. The Boolean phrases endurance OR submaximal NOT sprint AND running OR runner AND power OR power meter, were searched in PubMed, MEDLINE, and SCOPUS. Nineteen studies were finally selected for analysis. The current evidence about critical power and both power-time and power-duration relationships in running allow to provide coaches and practitioners a new promising setting for PW quantification with the use of wearable sensors. Some studies have assessed the validity and reliability of different available wearables for both kinematics parameters and PW when running but running power meters need further research before a definitive conclusion regarding its validity and reliability. Full article

(This article belongs to the Special Issue Wearable Sensors for Biomechanical Monitoring in Sport)

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