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Wearable Sensors for Monitoring Athletic and Clinical Cohorts
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Wearable Sensors for Monitoring Athletic and Clinical Cohorts

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

Deadline for manuscript submissions: 30 November 2024 | Viewed by 6604

Special Issue Editor

Dr. Adam Leigh Bryant

E-Mail Website
Guest Editor
Centre for Health, Exercise and Sports Medicine, Department of Physiotherapy, The University of Melbourne, Melbourne, VIC 3010, Australia
Interests: life sciences and biomedicine; clinical research; sport sciences; musculoskeletal; rehabilitation; orthopedics; physical injury; biomechanics

Special Issue Information

Dear Colleagues,

Wearable monitoring systems, also known as ‘wearables’, are wireless and include a sensor or sensor suite that is worn as an accessory or embedded in footwear or clothing. In combination with analytical software, wearable sensor technology enables the continuous and non-invasive detection of physiological (biosignal) and biomechanical (kinetic, kinematic) data. For athletic cohorts, data generated by wearables can be used by individual athletes, coaches, and support staff (trainers, physiotherapists, and sports medicine physicians) to quantify real-time physical demands with the aim of informing training strategies and screening for potential causes of musculoskeletal injury/re-injury. Whilst clinical applications have received far less attention, wearables hold considerable promise for expanding a range of patient-specific measures. As such, the utilisation of wearables in healthcare environments is expected to increase over the coming years. This Special Issue aims to present original research and review articles on recent advances, technologies, applications, and challenges in the field of wearable sensors used for athletic and clinical cohorts.

Dr. Adam Leigh Bryant
Guest Editor

Manuscript Submission Information

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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

  • wearable sensors
  • athletic
  • performance
  • clinical
  • treatment

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Published Papers (5 papers)

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Research

11 pages, 3519 KiB  
Communication
The Kinematic and Electromyographic Analysis of Roller Skating at Different Speeds on a Treadmill: A Case Study
by Giulia Bongiorno, Giulio Sisti, Francesca Dal Mas, Helena Biancuzzi, Tiwana Varrecchia, Giorgia Chini, Alberto Ranavolo, Barbara Pellegrini, Lorenzo Bortolan and Luca Miceli
Sensors 2024, 24(17), 5738; https://doi.org/10.3390/s24175738 - 4 Sep 2024
Viewed by 715
Abstract
Elite athletes in speed roller skates perceive skating to be a more demanding exercise for the groin when compared to other cyclic disciplines, increasing their risk of injury. The objective of this study was to monitor the kinematic and electromyographic parameters of roller [...] Read more.
Elite athletes in speed roller skates perceive skating to be a more demanding exercise for the groin when compared to other cyclic disciplines, increasing their risk of injury. The objective of this study was to monitor the kinematic and electromyographic parameters of roller speed skaters, linearly, on a treadmill, and to compare different skating speeds, one at 20 km/h and one at 32 km/h, at a 1° inclination. The acquisition was carried out by placing an inertial sensor at the level of the first sacral vertebra, and eight surface electromyographic probes on both lower limbs. The kinematic and electromyographic analysis on the treadmill showed that a higher speed requires more muscle activation, in terms of maximum and average values and co-activation, as it not only increases the intrinsic muscle demand in the district, but also the athlete’s ability to coordinate the skating technique. The present study allows us to indicate not only how individual muscle districts are activated during skating on a surface different from the road, but also how different speeds affect the overall district load distributions concerning effective force, which is essential for the physiotherapist and kinesiologist for preventive and conditional purposes, while also considering possible variations in the skating technique in linear advancement. Full article
(This article belongs to the Special Issue Wearable Sensors for Monitoring Athletic and Clinical Cohorts)
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10 pages, 895 KiB  
Article
Precision Balance Assessment in Parkinson’s Disease: Utilizing Vision-Based 3D Pose Tracking for Pull Test Analysis
by Nina Ellrich, Kasimir Niermeyer, Daniela Peto, Julian Decker, Urban M. Fietzek, Sabrina Katzdobler, Günter U. Höglinger, Klaus Jahn, Andreas Zwergal and Max Wuehr
Sensors 2024, 24(11), 3673; https://doi.org/10.3390/s24113673 - 6 Jun 2024
Viewed by 1243
Abstract
Postural instability is a common complication in advanced Parkinson’s disease (PD) associated with recurrent falls and fall-related injuries. The test of retropulsion, consisting of a rapid balance perturbation by a pull in the backward direction, is regarded as the gold standard for evaluating [...] Read more.
Postural instability is a common complication in advanced Parkinson’s disease (PD) associated with recurrent falls and fall-related injuries. The test of retropulsion, consisting of a rapid balance perturbation by a pull in the backward direction, is regarded as the gold standard for evaluating postural instability in PD and is a key component of the neurological examination and clinical rating in PD (e.g., MDS-UPDRS). However, significant variability in test execution and interpretation contributes to a low intra- and inter-rater test reliability. Here, we explore the potential for objective, vision-based assessment of the pull test (vPull) using 3D pose tracking applied to single-sensor RGB-Depth recordings of clinical assessments. The initial results in a cohort of healthy individuals (n = 15) demonstrate overall excellent agreement of vPull-derived metrics with the gold standard marker-based motion capture. Subsequently, in a cohort of PD patients and controls (n = 15 each), we assessed the inter-rater reliability of vPull and analyzed PD-related impairments in postural response (including pull-to-step latency, number of steps, retropulsion angle). These quantitative metrics effectively distinguish healthy performance from and within varying degrees of postural impairment in PD. vPull shows promise for straightforward clinical implementation with the potential to enhance the sensitivity and specificity of postural instability assessment and fall risk prediction in PD. Full article
(This article belongs to the Special Issue Wearable Sensors for Monitoring Athletic and Clinical Cohorts)
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12 pages, 2830 KiB  
Article
The Agreement between Wearable Sensors and Force Plates for the Analysis of Stride Time Variability
by Patrick Slattery, L. Eduardo Cofré Lizama, Jon Wheat, Paul Gastin, Ben Dascombe and Kane Middleton
Sensors 2024, 24(11), 3378; https://doi.org/10.3390/s24113378 - 24 May 2024
Viewed by 1120
Abstract
The variability and regularity of stride time may help identify individuals at a greater risk of injury during military load carriage. Wearable sensors could provide a cost-effective, portable solution for recording these measures, but establishing their validity is necessary. This study aimed to [...] Read more.
The variability and regularity of stride time may help identify individuals at a greater risk of injury during military load carriage. Wearable sensors could provide a cost-effective, portable solution for recording these measures, but establishing their validity is necessary. This study aimed to determine the agreement of several measures of stride time variability across five wearable sensors (Opal APDM, Vicon Blue Trident, Axivity, Plantiga, Xsens DOT) and force plates during military load carriage. Nineteen Australian Army trainee soldiers (age: 24.8 ± 5.3 years, height: 1.77 ± 0.09 m, body mass: 79.5 ± 15.2 kg, service: 1.7 ± 1.7 years) completed three 12-min walking trials on an instrumented treadmill at 5.5 km/h, carrying 23 kg of an external load. Simultaneously, 512 stride time intervals were identified from treadmill-embedded force plates and each sensor where linear (standard deviation and coefficient of variation) and non-linear (detrended fluctuation analysis and sample entropy) measures were obtained. Sensor and force plate agreement was evaluated using Pearson’s r and intraclass correlation coefficients. All sensors had at least moderate agreement (ICC > 0.5) and a strong positive correlation (r > 0.5). These results suggest wearable devices could be employed to quantify linear and non-linear measures of stride time variability during military load carriage. Full article
(This article belongs to the Special Issue Wearable Sensors for Monitoring Athletic and Clinical Cohorts)
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12 pages, 2694 KiB  
Article
Assessment of the Smartpill, a Wireless Sensor, as a Measurement Tool for Intra-Abdominal Pressure (IAP)
by Andréa Soucasse, Arthur Jourdan, Lauriane Edin, Elise Meunier, Thierry Bege and Catherine Masson
Sensors 2024, 24(1), 54; https://doi.org/10.3390/s24010054 - 21 Dec 2023
Viewed by 1298
Abstract
Background: The SmartPill, a multisensor ingestible capsule, is marketed for intestinal motility disorders. It includes a pressure sensor, which could be used to study intra-abdominal pressure (IAP) variations. However, the validation data are lacking for this use. Material and Methods: An experimental study [...] Read more.
Background: The SmartPill, a multisensor ingestible capsule, is marketed for intestinal motility disorders. It includes a pressure sensor, which could be used to study intra-abdominal pressure (IAP) variations. However, the validation data are lacking for this use. Material and Methods: An experimental study was conducted on anesthetized pigs with stepwise variations of IAP (from 0 to 15 mmHg by 3 mmHg steps) generated by laparoscopic insufflation. A SmartPill, inserted by endoscopy, provided intragastric pressure data. These data were compensated to take into account the intrabdominal temperature. They were compared to the pressure recorded by intragastric (IG) and intraperitoneal (IP) wired sensors by statistical Spearman and Bland–Altmann analysis. Results: More than 4500 pressure values for each sensor were generated on two animals. The IG pressure values obtained with the SmartPill were correlated with the IG pressure values obtained with the wired sensor (respectively, Spearman ρ coefficients 0.90 ± 0.08 and 0.72 ± 0.25; bias of −28 ± −0.3 mmHg and −29.2 ± 0.5 mmHg for pigs 1 and 2). The intragastric SmartPill values were also correlated with the IAP measured intra-peritoneally (respectively, Spearman ρ coefficients 0.49 ± 0.18 and 0.57 ± 0.30; bias of −29 ± 1 mmHg and −31 ± 0.7 mmHg for pigs 1 and 2). Conclusions: The SmartPill is a wireless and painless sensor that appears to correctly monitor IAP variations. Full article
(This article belongs to the Special Issue Wearable Sensors for Monitoring Athletic and Clinical Cohorts)
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12 pages, 836 KiB  
Article
Can Wrist-Worn Medical Devices Correctly Identify Ovulation?
by Angela Niggli, Martina Rothenbühler, Maike Sachs and Brigitte Leeners
Sensors 2023, 23(24), 9730; https://doi.org/10.3390/s23249730 - 9 Dec 2023
Cited by 1 | Viewed by 1524
Abstract
(1) Background: Hormonal fluctuations across the menstrual cycle lead to multiple changes in physiological parameters such as body temperature, cardiovascular function, respiratory rate and perfusion. Electronic wearables analyzing those parameters might present a convenient alternative to urinary ovulation tests for predicting the fertile [...] Read more.
(1) Background: Hormonal fluctuations across the menstrual cycle lead to multiple changes in physiological parameters such as body temperature, cardiovascular function, respiratory rate and perfusion. Electronic wearables analyzing those parameters might present a convenient alternative to urinary ovulation tests for predicting the fertile window. (2) Methods: We conducted a prospective observational study including women aged 18–45 years without current hormonal therapy who used a wrist-worn medical device and urinary ovulation tests for a minimum of three cycles. We analyzed the accuracy of both the retrospective and prospective algorithms using a generalized linear mixed-effects model. The findings were compared to real-world data from bracelet users who also reported urinary ovulation tests. (3) Results: A total of 61 study participants contributing 205 cycles and 6081 real-life cycles from 3268 bracelet users were included in the analysis. The mean error in identifying ovulation with the wrist-worn medical device retrospective algorithm in the clinical study was 0.31 days (95% CI −0.13 to 0.75). The retrospective algorithm identified 75.4% of fertile days, and the prospective algorithm identified 73.8% of fertile days correctly within the pre-specified equivalence limits (±2 days). The quality of the retrospective algorithm in the clinical study could be confirmed by real-world data. (4) Conclusion: Our data indicate that wearable sensors may be used to accurately detect the periovulatory period. Full article
(This article belongs to the Special Issue Wearable Sensors for Monitoring Athletic and Clinical Cohorts)
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