Special Issue "Wearable Technologies II"

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

Deadline for manuscript submissions: closed (31 October 2021).

Special Issue Editor

Dr. James Navalta
E-Mail Website
Guest Editor
Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, NV, USA
Interests: wearable technology/fitness tracker validation; exercise in an outdoor environment; exercise immunology

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 papers will be 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 quarterly 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 1400 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

Published Papers (4 papers)

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Research

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Article
Criterion Validity of iOS and Android Applications to Measure Steps and Distance in Adults
Technologies 2021, 9(3), 55; https://doi.org/10.3390/technologies9030055 - 29 Jul 2021
Viewed by 640
Abstract
The growing popularity of physical activity (PA) applications (apps) in recent years and the vast amounts of data that they generate present attractive possibilities for surveillance. However, measurement accuracy is indispensable when tracking PA variables to provide meaningful measures of PA. The purpose [...] Read more.
The growing popularity of physical activity (PA) applications (apps) in recent years and the vast amounts of data that they generate present attractive possibilities for surveillance. However, measurement accuracy is indispensable when tracking PA variables to provide meaningful measures of PA. The purpose of this study was to examine the steps and distance criterion validity of freeware accelerometer-based PA smartphone apps, during incremental-intensity treadmill walking and jogging. Thirty healthy adults (25.9 ± 5.7 years) participated in this cross-sectional study. They were fitted with two smartphones (one with Android and one with iOS operating systems), each one simultaneously running four different apps (i.e., Runtastic Pedometer, Accupedo, Pacer, and Argus). They walked and jogged for 5 min at each of the predefined speeds of 4.8, 6.0, and 8.4 km/h on a treadmill, and two researchers counted every step taken during trials with a digital tally counter. Validity was evaluated by comparing each app with the criterion measure using repeated-measures analysis of variance (ANOVA), mean absolute percentage errors (MAPEs), and Bland–Altman plots. For step count, Android apps performed slightly more accurately that iOS apps; nevertheless, MAPEs were generally low for all apps (<5%) and accuracy increased at higher speeds. On the other hand, errors were significantly higher for distance estimation (>10%). The findings suggest that accelerometer-based apps are accurate tools for counting steps during treadmill walking and jogging and could be considered suitable for use as an outcome measure within a clinical trial. However, none of the examined apps was suitable for measuring distance. Full article
(This article belongs to the Special Issue Wearable Technologies II)
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Article
Assessing Heart Rate Using Consumer Technology Association Standards
Technologies 2021, 9(3), 46; https://doi.org/10.3390/technologies9030046 - 30 Jun 2021
Viewed by 862
Abstract
It is difficult for developers, researchers, and consumers to compare results among emerging wearable technology without using a uniform set of standards. This study evaluated the accuracy of commercially available wearable technology heart rate (HR) monitors using the Consumer Technology Association (CTA) standards. [...] Read more.
It is difficult for developers, researchers, and consumers to compare results among emerging wearable technology without using a uniform set of standards. This study evaluated the accuracy of commercially available wearable technology heart rate (HR) monitors using the Consumer Technology Association (CTA) standards. Participants (N = 23) simultaneously wore a Polar chest strap (criterion measure), Jabra Elite earbuds, Scosche Rhythm 24 armband, Apple Watch 4, and Garmin Forerunner 735 XT during sitting, activities of daily living, walking, jogging, running, and cycling, totaling 57 min of monitored activity. The Apple Watch mean bias was within ±1 bpm, and mean absolute percent error (MAPE) was <3% in all six conditions. Garmin underestimated HR in all conditions, except cycling and MAPE was >10% during sedentary, lifestyle, walk-jog, and running. The Jabra mean bias was within ±5 bpm for each condition, and MAPE exceeded 10% for walk-jog. The Scosche mean bias was within ±1 bpm and MAPE was <5% for all conditions. In conclusion, only the Apple Watch Series 4 and the Scosche Rhythm 24 displayed acceptable agreement across all conditions. By employing CTA standards, future developers, researchers, and consumers will be able to make true comparisons of accuracy among wearable devices. Full article
(This article belongs to the Special Issue Wearable Technologies II)
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Article
Analysis of the Behavioral Change and Utility Features of Electronic Activity Monitors
Technologies 2020, 8(4), 75; https://doi.org/10.3390/technologies8040075 - 05 Dec 2020
Cited by 1 | Viewed by 1100
Abstract
The aim of this study was to perform a content analysis of electronic activity monitors that also evaluates utility features, code behavior change techniques included in the monitoring systems, and align the results with intervention functions of the Behaviour Change Wheel program planning [...] Read more.
The aim of this study was to perform a content analysis of electronic activity monitors that also evaluates utility features, code behavior change techniques included in the monitoring systems, and align the results with intervention functions of the Behaviour Change Wheel program planning model to facilitate informed device selection. Devices were coded for the implemented behavior change techniques and device features. Three trained coders each wore a monitor for at least 1 week from December 2019–April 2020. Apple Watch Nike, Fitbit Versa 2, Fitbit Charge 3, Fitbit Ionic—Adidas Edition, Garmin Vivomove HR, Garmin Vivosmart 4, Amazfit Bip, Galaxy Watch Active, and Withings Steel HR were reviewed. The monitors all paired with a phone/tablet, tracked exercise sessions, and were wrist-worn. On average, the monitors implemented 27 behavior change techniques each. Fitbit devices implemented the most behavior change techniques, including techniques related to the intervention functions: education, enablement, environmental restructuring, coercion, incentivization, modeling, and persuasion. Garmin devices implemented the second highest number of behavior change techniques, including techniques related to enablement, environmental restructuring, and training. Researchers can use these results to guide selection of electronic activity monitors based on their research needs. Full article
(This article belongs to the Special Issue Wearable Technologies II)
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Review

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Review
Validity and Reliability of Physiological Data in Applied Settings Measured by Wearable Technology: A Rapid Systematic Review
Technologies 2020, 8(4), 70; https://doi.org/10.3390/technologies8040070 - 24 Nov 2020
Cited by 1 | Viewed by 1039
Abstract
The purpose of this review was to evaluate the current state of the literature and to identify the types of study designs, wearable devices, statistical tests, and exercise modes used in validation and reliability studies conducted in applied settings/outdoor environments. This was performed [...] Read more.
The purpose of this review was to evaluate the current state of the literature and to identify the types of study designs, wearable devices, statistical tests, and exercise modes used in validation and reliability studies conducted in applied settings/outdoor environments. This was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We identified nine articles that fit our inclusion criteria, eight of which tested for validity and one tested for reliability. The studies tested 28 different devices with exercise modalities of running, walking, cycling, and hiking. While there were no universally common analytical techniques used to measure accuracy or validity, correlative measures were used in 88% of studies, mean absolute percentage error (MAPE) in 75%, and Bland–Altman plots in 63%. Intra-class correlation was used to determine reliability. There were not any universally common thresholds to determine validity, however, of the studies that used MAPE and correlation, there were only five devices that had a MAPE of < 10% and a correlation value of > 0.7. Overall, the current review establishes the need for greater testing in applied settings when validating wearables. Researchers should seek to incorporate multiple intensities, populations, and modalities into their study designs while utilizing appropriate analytical techniques to measure and determine validity and reliability. Full article
(This article belongs to the Special Issue Wearable Technologies II)
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