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Technology and Methods to Monitor Resistance Training: Applications in Health, Disease and Performance in Sport

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

Deadline for manuscript submissions: closed (30 August 2023) | Viewed by 6415

Special Issue Editors

Prof. Dr. Borja Sañudo

E-Mail Website1 Website2
Guest Editor
Department of Physical Education and Sports, Faculty of Educational Sciences, Universidad de Sevilla, 41013 Seville, Spain
Interests: new technologies; fitness; rehabilitation; clinical populations; exercise; active aging
Special Issues, Collections and Topics in MDPI journals
Dr. Alejandro Muñoz-López

E-Mail Website
Guest Editor
Departament of Human Motricity and Sports Performance, University of Seville, Seville, Spain
Interests: sports sciences

Special Issue Information

Dear Colleagues,

The science behind the application and innovation of new training methods is being improved due to the development of new technology. This technology provides new insight into modern ways to analyse human performance in sports but is also recognized as one of the primary therapeutic targets interventions in older adults and clinical populations. Over the past years, different resistance training equipment and new methods have been developed, incorporating more objective and portable devices to measure physical fitness. The incorporation of these devices facilitate the use of standardized and feasible assessment protocols, allowing the identification of strength and muscle power patterns in daily practice. This Special Issue aims to provide new insights in the use of technology to understand and monitor physical performance during resistance training in different populations. Articles addressing this topic, more specifically on implementing new analysis on daily routines, are welcome.

Prof. Dr. Borja Sañudo
Dr. Alejandro Muñoz-López
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

  • Technology
  • Wearable sensors
  • Mobile applications
  • Biomechanics
  • Force–velocity profile
  • Performance Monitoring

Published Papers (2 papers)

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Research

15 pages, 1835 KiB  
Article
Effects of Resistance Training as a Behavioural Preventive Measure on Musculoskeletal Complaints, Maximum Strength and Ergonomic Risk in Dentists and Dental Assistants
by Fabian Holzgreve, Laura Fraeulin, Christian Maurer-Grubinger, Werner Betz, Christina Erbe, Tim Weis, Keno Janssen, Lisa Schulte, Amaya de Boer, Albert Nienhaus, David A. Groneberg and Daniela Ohlendorf
Sensors 2022, 22(20), 8069; https://doi.org/10.3390/s22208069 - 21 Oct 2022
Cited by 10 | Viewed by 2343
Abstract
Introduction: For dental professionals, musculoskeletal disorders (MSD) are common health hazards and resistance training programmes have been promising approaches in the quest for a reduction in the pain intensity of these professionals. Therefore, the aim of the current study was to investigate the [...] Read more.
Introduction: For dental professionals, musculoskeletal disorders (MSD) are common health hazards and resistance training programmes have been promising approaches in the quest for a reduction in the pain intensity of these professionals. Therefore, the aim of the current study was to investigate the effect of a trunk-oriented 10-week resistance training programme. Method: In total, the study was conducted with 17 dentists and dental assistants (3 m/14 f) over a course of 10 weeks, with workouts being performed 2 times a week using a 60 min intervention programme consisting of 11 resistance training exercises. The outcome values that were collected were the pain intensity (visual analogue scale (VAS) combined with a modified version of the Nordic Questionnaire), the MVIC and the rapid upper limb assessment (RULA) score (based on data from inertial motion units) during a standardised dental treatment protocol. Results: A significant reduction in pain intensity was found for each queried body region: the neck, upper back, lower back and the right and left shoulders. The maximum voluntary isometric contraction (MVIC) improved significantly in all outcome measures: flexion, extension, right and left lateral flexion and right and left rotation. Conclusions: A 10-week resistance training programme for dentists and dental assistants had significant effects on pain intensity reduction and the MVIC of the musculature of the trunk and is, therefore, suitable as a behavioural preventive measure against MSD in dental professionals. Full article
(This article belongs to the Special Issue Technology and Methods to Monitor Resistance Training: Applications in Health, Disease and Performance in Sport)
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16 pages, 2515 KiB  
Article
The Maximum Flywheel Load: A Novel Index to Monitor Loading Intensity of Flywheel Devices
by Alejandro Muñoz-López, Pablo Floría, Borja Sañudo, Javier Pecci, Jorge Carmona Pérez and Marco Pozzo
Sensors 2021, 21(23), 8124; https://doi.org/10.3390/s21238124 - 4 Dec 2021
Cited by 5 | Viewed by 3127
Abstract
Background: The main aim of this study was (1) to find an index to monitor the loading intensity of flywheel resistance training, and (2) to study the differences in the relative intensity workload spectrum between the FW-load and ISO-load. Methods: twenty-one males participated [...] Read more.
Background: The main aim of this study was (1) to find an index to monitor the loading intensity of flywheel resistance training, and (2) to study the differences in the relative intensity workload spectrum between the FW-load and ISO-load. Methods: twenty-one males participated in the study. Subjects executed an incremental loading test in the squat exercise using a Smith machine (ISO-load) or a flywheel device (FW-load). We studied different association models between speed, power, acceleration, and force, and each moment of inertia was used to find an index for FW-load. In addition, we tested the differences between relative workloads among load conditions using a two-way repeated-measures test. Results: the highest r2 was observed using a logarithmic fitting model between the mean angular acceleration and moment of inertia. The intersection with the x-axis resulted in an index (maximum flywheel load, MFL) that represents a theoretical individual maximal load that can be used. The ISO-load showed greater speed, acceleration, and power outcomes at any relative workload (%MFL vs. % maximum repetition). However, from 45% of the relative workload, FW-load showed higher vertical forces. Conclusions: MFL can be easily computed using a logarithmic model between the mean angular acceleration and moment of inertia to characterize the maximum theoretical loading intensity in the flywheel squat. Full article
(This article belongs to the Special Issue Technology and Methods to Monitor Resistance Training: Applications in Health, Disease and Performance in Sport)
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