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Monitoring Physical Activity with Wearable Technologies
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Monitoring Physical Activity with Wearable Technologies

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

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 5270

Special Issue Editors

Dr. Ewan Thomas

E-Mail Website
Guest Editor
Department of Psychology, Educational Science and Human Movement, University of Palermo, Palermo, Italy
Interests: physical activity; injury prevention; human movement; resistance training; stretching, osteopathy.
Special Issues, Collections and Topics in MDPI journals
Dr. Abbey Thomas

E-Mail Website
Guest Editor
Department of Applied Physiology, Health, and Clinical Sciences, Univerity of North Carolina at Charlotte, Charlotte, NC, USA
Interests: knee injury; osteoarthritis; anterior cruciate ligament (ACL) injury; biomechanics; TMS

Special Issue Information

Dear Colleagues,

Wearable technologies have increased in popularity, becoming an integrated aspect of training in professional and non-professional environments. This has also been confirmed by the annual American College of Sports Science (ACSM) Fitness Trends, with wearable technologies being the number one trending topic in 2022. Wearable technologies include fitness trackers, smartwatches, heart rate monitors and GPS tracking devices. The applications of these devices may include, but are not limited to, measuring everyday life levels of physical activity, monitoring sleep performance, monitoring sport and physical activity in real-life settings, providing personalized feedback to users and coaches and detecting possible postural or biomechanical alterations which may allow the prevention of injuries. Wearable technologies also have the ability to provide feedback to mobile phones or laptops which allow further integration of the biomechanical and physiological parameters collected.

Advancements in artificial intelligence and machine learning could also help the development of software that may enable the early detection or diagnosis of more severe conditions through the everyday use of these devices. Innovations may also include HRV monitoring, oxygen saturation or virus identification.

Despite the increasing interest in wearable technologies, studies still need to be implemented in either sports performance, everyday physical activity or injury prevention.  

This Special Issue is interested in all types of wearable sensors and mobile technologies dedicated to physical activity monitoring in the domains of sport, health, prevention and rehabilitation.

Topics of Interest:

  • Physical Activity
  • Accelerometers
  • GPS
  • Performance
  • Injury Prevention

Dr. Ewan Thomas
Dr. Abbey Thomas
Guest Editors

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.

Keywords

  • sports medicine
  • human movement
  • injury prevention
  • performance monitoring
  • activity tracking
  • levels of activity
  • energy expenditure
  • inertial sensors
  • rehabilitation

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Published Papers (2 papers)

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Research

17 pages, 1016 KiB  
Article
Correlates of Person-Specific Rates of Change in Sensor-Derived Physical Activity Metrics of Daily Living in the Rush Memory and Aging Project
by Aron S. Buchman, Tianhao Wang, Shahram Oveisgharan, Andrea R. Zammit, Lei Yu, Peng Li, Kun Hu, Jeffrey M. Hausdorff, Andrew S. P. Lim and David A. Bennett
Sensors 2023, 23(8), 4152; https://doi.org/10.3390/s23084152 - 21 Apr 2023
Cited by 4 | Viewed by 2014
Abstract
This study characterized person-specific rates of change of total daily physical activity (TDPA) and identified correlates of this change. TDPA metrics were extracted from multiday wrist-sensor recordings from 1083 older adults (average age 81 years; 76% female). Thirty-two covariates were collected at baseline. [...] Read more.
This study characterized person-specific rates of change of total daily physical activity (TDPA) and identified correlates of this change. TDPA metrics were extracted from multiday wrist-sensor recordings from 1083 older adults (average age 81 years; 76% female). Thirty-two covariates were collected at baseline. A series of linear mixed-effect models were used to identify covariates independently associated with the level and annual rate of change of TDPA. Though, person-specific rates of change varied during a mean follow-up of 5 years, 1079 of 1083 showed declining TDPA. The average decline was 16%/year, with a 4% increased rate of decline for every 10 years of age older at baseline. Following variable selection using multivariate modeling with forward and then backward elimination, age, sex, education, and 3 of 27 non-demographic covariates including motor abilities, a fractal metric, and IADL disability remained significantly associated with declining TDPA accounting for 21% of its variance (9% non-demographic and 12% demographics covariates). These results show that declining TDPA occurs in many very old adults. Few covariates remained correlated with this decline and the majority of its variance remained unexplained. Further work is needed to elucidate the biology underlying TDPA and to identify other factors that account for its decline. Full article
(This article belongs to the Special Issue Monitoring Physical Activity with Wearable Technologies)
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20 pages, 1716 KiB  
Article
Low-Cost Portable System for Measurement and Representation of 3D Kinematic Parameters in Sport Monitoring: Discus Throwing as a Case Study
by Juan Francisco Navarro-Iribarne, David Moreno-Salinas and José Sánchez-Moreno
Sensors 2022, 22(23), 9408; https://doi.org/10.3390/s22239408 - 2 Dec 2022
Cited by 1 | Viewed by 2175
Abstract
Monitoring of sports practice has become an almost essential tool in high-level professional training. The knowledge of the exact movements performed by an athlete provides a great advantage over conventional training, since the best performance can be theoretically known in advance and the [...] Read more.
Monitoring of sports practice has become an almost essential tool in high-level professional training. The knowledge of the exact movements performed by an athlete provides a great advantage over conventional training, since the best performance can be theoretically known in advance and the trainer will expect the real athlete’s movements to approximate it. Following this trend, this article deals with the design and development of a low-cost wearable biofeedback system for the measurement and representation of kinematic parameters in 3D. To capture the athlete’s movements, an inertial measurement unit (IMU) is used, whose data are processed in an microcontroller-based architecture. The kinematic parameters of the athlete’s movement are sent via Bluetooth to a smart phone, where they are displayed graphically. Experimental examples show the effectiveness of the device developed and illustrate the key results derived. Full article
(This article belongs to the Special Issue Monitoring Physical Activity with Wearable Technologies)
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