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Technologies
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Wearable Technologies III
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Wearable Technologies III

A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Assistive Technologies".

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 20351

Special Issue Editor

Dr. James Navalta

E-Mail Website
Guest Editor
Department of Kinesiology and Nutrition Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
Interests: wearable technology/fitness tracker validation; exercise in an outdoor environment; exercise immunology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The editors of Technologies enthusiastically announce an upcoming issue dedicated to wearable technology in exercise and sport applications. Of specific interest are manuscripts that detail the validity of physiological variables in relation to accepted criterion measures, investigations reporting the reliability of wearable devices, and the use of wearable technologies in a wide array of sporting environments. Other manuscripts related to the topic of wearable technology and physical activity will be considered.

Dr. James Navalta
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. Technologies is an international peer-reviewed open access monthly 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 1600 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 technology
  • fitness trackers
  • exercise, sport, physical activity

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Related Special Issues

Published Papers (6 papers)

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Editorial

Jump to: Research, Other

4 pages, 157 KiB  
Editorial
Summary Editorial on Wearable Technology in Exercise and Sport Applications
by James W. Navalta
Technologies 2024, 12(11), 223; https://doi.org/10.3390/technologies12110223 - 7 Nov 2024
Viewed by 791
Abstract
We recently closed the second of two Special Issues centered around wearable technology use in exercise and sport applications [...] Full article
(This article belongs to the Special Issue Wearable Technologies III)

Research

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10 pages, 1571 KiB  
Article
Validation of Aerobic Capacity (VO2max) and Lactate Threshold in Wearable Technology for Athletic Populations
by Bryson Carrier, Macy M. Helm, Kyle Cruz, Brenna Barrios and James W. Navalta
Technologies 2023, 11(3), 71; https://doi.org/10.3390/technologies11030071 - 26 May 2023
Cited by 3 | Viewed by 5839
Abstract
As wearable technology (WT) has evolved, devices have developed the ability to track a range of physiological variables. These include maximal aerobic capacity (VO2max) and lactate threshold (LT). With WT quickly growing in popularity, independent evaluation of these devices is important [...] Read more.
As wearable technology (WT) has evolved, devices have developed the ability to track a range of physiological variables. These include maximal aerobic capacity (VO2max) and lactate threshold (LT). With WT quickly growing in popularity, independent evaluation of these devices is important to determine the appropriate use-cases for the devices. Therefore, the purpose of this study was to determine the validity of WT in producing estimates of VO2max and LT in athletic populations. METHODS: 21 participants completed laboratory LT and VO2max testing, as well as an outdoor testing session guided by the WT being tested (Garmin fēnix 6® watch and accompanying heart rate monitor). Statistical analysis was completed, using hypothesis testing (ANOVA, t-test), correlation analysis (Pearson’s r, Lin’s Concordance Correlation [CCC]), error analysis (mean absolute percentage error [MAPE]), equivalence testing (TOST test), and bias assessment (Bland–Altman analysis). RESULTS: The Garmin watch was found to have acceptable agreement for VO2max when compared to the 1 min averaged values (MAPE = 6.85%, CCC = 0.7) and for LT and the onset of blood lactate accumulation (OBLA), (MAPE = 7.52%, CCC = 0.79; MAPE = 8.20%, CCC = 0.74, respectively). Therefore, the Garmin fēnix 6® produces accurate measurements of VO2max and LT in athletic populations and can be used to make training decisions among athletes. Full article
(This article belongs to the Special Issue Wearable Technologies III)
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17 pages, 1314 KiB  
Article
A Novel Methodology for Human Kinematics Motion Detection Based on Smartphones Sensor Data Using Artificial Intelligence
by Ali Raza, Mohammad Rustom Al Nasar, Essam Said Hanandeh, Raed Abu Zitar, Ahmad Yacoub Nasereddin and Laith Abualigah
Technologies 2023, 11(2), 55; https://doi.org/10.3390/technologies11020055 - 11 Apr 2023
Cited by 16 | Viewed by 4019
Abstract
Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily life monitoring, assisting workers during industry manufacturing, caring for the [...] Read more.
Kinematic motion detection aims to determine a person’s actions based on activity data. Human kinematic motion detection has many valuable applications in health care, such as health monitoring, preventing obesity, virtual reality, daily life monitoring, assisting workers during industry manufacturing, caring for the elderly. Computer vision-based activity recognition is challenging due to problems such as partial occlusion, background clutter, appearance, lighting, viewpoint, and changes in scale. Our research aims to detect human kinematic motions such as walking or running using smartphones’ sensor data within a high-performance framework. An existing dataset based on smartphones’ gyroscope and accelerometer sensor values is utilized for the experiments in our study. Sensor exploratory data analysis was conducted in order to identify valuable patterns and insights from sensor values. The six hyperparameters, tunned artificial indigence-based machine learning, and deep learning techniques were applied for comparison. Extensive experimentation showed that the ensemble learning-based novel ERD (ensemble random forest decision tree) method outperformed other state-of-the-art studies with high-performance accuracy scores. The proposed ERD method combines the random forest and decision tree models, which achieved a 99% classification accuracy score. The proposed method was successfully validated with the k-fold cross-validation approach. Full article
(This article belongs to the Special Issue Wearable Technologies III)
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11 pages, 278 KiB  
Article
Validity of Wearable Monitors and Smartphone Applications for Measuring Steps in Semi-Structured and Free-Living Settings
by Manolis Adamakis
Technologies 2023, 11(1), 29; https://doi.org/10.3390/technologies11010029 - 13 Feb 2023
Viewed by 2177
Abstract
Wearable technologies have become powerful tools for health and fitness and are indispensable everyday tools for many individuals; however, significant limitations exist related to the validity of the metrics these monitors purport to measure. Thus, the purpose of the present study was to [...] Read more.
Wearable technologies have become powerful tools for health and fitness and are indispensable everyday tools for many individuals; however, significant limitations exist related to the validity of the metrics these monitors purport to measure. Thus, the purpose of the present study was to validate the step count of three wearable monitors (i.e., Yamax 3D Power-Walker, Garmin Vivofit 3 and Medisana Vifit), as well as two Android apps (i.e., Accupedo Pedometer and Pedometer 2.0), in a sample of healthy adults. These monitors and apps were evaluated in a lab-based semi-structured study and a 3-day field study under habitual free-living conditions. A convenience sample of 24 healthy adults (14 males and 10 females; 32.6 ± 2.5 years) participated in both studies. Direct step observation and Actigraph served as the criterion methods and validity was evaluated by comparing each monitor and app with the criterion measure using mean absolute percentage errors (MAPE), Bland–Altman plots, and Intraclass Correlation Coefficients. The results revealed high validity for the three wearable monitors during the semi-structured study, with MAPE values approximately 5% for Yamax and Vifit and well below 5% for Vivofit, while the two apps showed high MAPE values over 20%. In the free-living study all monitors and apps had high MAPE, over 10%. The lowest error was observed for Yamax, Vifit and Pedometer app, while Accupedo app had the highest error, overestimating steps by 32%. The present findings cannot support the value of wearable monitors and apps as acceptable measures of PA and step count in free-living contexts. Wearable monitors and apps that might be valid in one context, might not be valid in different contexts and vice versa, and researchers should be aware of this limitation. Full article
(This article belongs to the Special Issue Wearable Technologies III)

Other

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15 pages, 864 KiB  
Systematic Review
Training Impulse and Its Impact on Load Management in Collegiate and Professional Soccer Players
by Clinton Gardner, James W. Navalta, Bryson Carrier, Charli Aguilar and Jorge Perdomo Rodriguez
Technologies 2023, 11(3), 79; https://doi.org/10.3390/technologies11030079 - 17 Jun 2023
Cited by 4 | Viewed by 3437
Abstract
Methods: Training impulse (TRIMP) is obtained through wearable technology and plays a direct role on the load management of soccer players. It is important to understand TRIMP to best prepare athletes for competition. A systematic search for articles was conducted using Google Scholar, [...] Read more.
Methods: Training impulse (TRIMP) is obtained through wearable technology and plays a direct role on the load management of soccer players. It is important to understand TRIMP to best prepare athletes for competition. A systematic search for articles was conducted using Google Scholar, with papers screened and extracted by five reviewers. The inclusion criteria were: the study was focused on collegiate or professional soccer, the use of training impulse (TRIMP), and the use of wearable technology to measure TRIMP. Of 10,100 papers, 10,090 articles were excluded through the systematic review process. Ten papers were selected for final review and grouped based on (1) training vs. match (N = 8/10), (2) preseason vs. in-season (N = 3/10), and (3) positional comparison (N = 3/10). Wearable technologies mainly track physical metrics (N = 10/10). Higher TRIMP data were noted in starters than reserves throughout the season in matches and slightly lower TRIMP for starters vs. reserves during training. TRIMP data change throughout the season, being higher in preseason phases compared to early-season, mid-season, and late-season phases. These findings help highlight the benefits of TRIMP in managing internal player load in soccer. Future research should focus on utilizing wearable-derived TRIMP and the impact on player performance metrics, and how TRIMP data vary across different positions in soccer. Full article
(This article belongs to the Special Issue Wearable Technologies III)
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7 pages, 460 KiB  
Brief Report
A Deeper Look into Exercise Intensity Tracking through Mobile Applications: A Brief Report
by Alexie Elder, Gabriel Guillen, Rebecca Isip, Ruben Zepeda and Zakkoyya H. Lewis
Technologies 2023, 11(3), 66; https://doi.org/10.3390/technologies11030066 - 1 May 2023
Cited by 1 | Viewed by 3355
Abstract
Mobile fitness applications (apps) allow for time-efficient opportunities for physical activity. Current research suggests that fitness apps do not accurately comply with the frequency, intensity, time, and type (FITT) principle. FITT is an important principle in exercise prescription as it applies scientific evidence [...] Read more.
Mobile fitness applications (apps) allow for time-efficient opportunities for physical activity. Current research suggests that fitness apps do not accurately comply with the frequency, intensity, time, and type (FITT) principle. FITT is an important principle in exercise prescription as it applies scientific evidence to improve the quality of exercise. Based on app assessment using the Fitness Apps Scoring Instrument, most fitness apps adequately address FITT in their exercise plans. In particular, fitness apps do not adequately adhere to the FITT intensity guidelines. Many apps allow the users to track their heart rate as a method of assessing their exercise intensity, but few use that information to provide real-time feedback on the intensity of the workout. For app users, awareness and education of intensity standards should be put forth in coordination with exercise professionals, rather than relying on apps alone. Full article
(This article belongs to the Special Issue Wearable Technologies III)
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