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Wearable Sensors for Health and Physiological Monitoring

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

Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 54013

Special Issue Editors


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Guest Editor
Hochgebirgsklinik Davos, Medicine Campus Davos, Davos, Switzerland
Interests: preventive medicine; preventive cardiology; exercise training; physical activity; cardiac rehabilitation; sports cardiology; sports medicine; cardiovascular risk factors; healthy mobility; athlete’s health

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Guest Editor
1. Department of Geoinformatics, University of Salzburg, 5020 Salzburg, Austria
2. Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA
Interests: human-centred geoinformatics; geospatial machine learning; urban geoinformatics; fusion of human and technical sensors; people as sensors and collective sensing (VGI); real-time and smart cities; crowdsourcing; digital health
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Special Issue Information

Dear colleagues,

With great pleasure, we invite you to contribute to this Special Issue entitled “Wearable Sensors for Health and Physiological Monitoring” for Sensors.

Wearable biosensors for humans are an emerging field in a large number of scientific disciplines like biomedical research, mobility research, biomechanics, geoinformatics, sports science, urban planning or psychology. Besides, in everyday living these wearable biosensors are also of increased relevance as the “quantified self” movement is rapidly gaining momentum. Many people use wearable devices like fitness-watches, fitness trackers, step-counters, or medical-purpose wearables. In addition, smartphone based applications like eDiary apps offer a broad variety of possibilities and are essentially smartphone-based biosensors. Smart tissues offer enormous possibilities to measure sweat loss, fluid balance, stress level and even electrocardiographic changes in athletes, patients, and citizens alike. In recreational and professional sports especially, injury prevention, training periodization, assessment of regeneration, training stimulus or fatigue and estimation of return-to-play after medical incidents are possible applications of biosensors.

Equipping sports gear such as helmets, ski boots, shoes, or bikes with biosensors may give useful insights for training purposes and injury prevention. The data derived from biosensors have even been used to change sporting rules in the past, and these data are of emerging importance in many official sporting bodies. Medical devices such as cardiac pacemakers, prostheses, or brain stimulators offer new perspectives to equip these devices with sensors or use the integrated sensors for advanced purposes such as disease monitoring, injury prevention, fitness tracking, emergency functions or interaction between patients and health care professionals. Emerging applications like biosensors in cars to detect sleepiness, medical emergencies, or stress are meanwhile under thorough scientific investigation with promising results in practical application.

Coupled with established location technology like GPS trackers, measurements from wearable sensors do not only allow drawing far-reaching conclusions about individuals and their physical conditions, but also enable the performance of collective studies. For instance, analysing physiological data of larger cohorts of test persons and citizens generates new insights into urban systems, mobility infrastructures, workplace wellbeing, or urban stress and relaxation. The geospatial and temporal correlation with real-world environmental covariates (demographic statistical data, characteristics of the urban environment like traffic, greenness, tourist density, etc.) helps in revealing previously unseen patterns, supporting urban management and planning or health system management.

In this Special Issue, we want to build a bridge between different scientific disciplines and offer highly innovative researchers in various fields a platform to exchange research in this exciting and emerging field: wearable sensors for health and physiological monitoring.

We, the guest editors of this Special Issue, represent research backgrounds in geographic information science, mobility research, and medicine with a focus on cardiovascular medicine and sports science. We herewith stand for the highly interdisciplinary approach that is essential in research in this emerging scientific field and highly anticipate submissions from a broad range of specialities to this Special Issue.

Kind regards,
Dr. David Niederseer
Dr. Bernd Resch
Guest Editors

Manuscript Submission Information

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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

  • GPS-tracking
  • wearable sensors
  • smart tissue
  • cardiac devices
  • pacemaker
  • implantable biosensor
  • objective stress measurement
  • mobility research
  • sports science
  • sports gear
  • athletic training
  • smart car
  • geospatial analysis
  • eDiary apps
  • biomechanics

Published Papers (15 papers)

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Research

Jump to: Review

13 pages, 1600 KiB  
Article
An Investigation of Surface EMG Shorts-Derived Training Load during Treadmill Running
by Kurtis Ashcroft, Tony Robinson, Joan Condell, Victoria Penpraze, Andrew White and Stephen P. Bird
Sensors 2023, 23(15), 6998; https://doi.org/10.3390/s23156998 - 07 Aug 2023
Viewed by 976
Abstract
The purpose of this study was two-fold: (1) to determine the sensitivity of the sEMG shorts-derived training load (sEMG-TL) during different running speeds; and (2) to investigate the relationship between the oxygen consumption, heart rate (HR), rating of perceived exertion (RPE), accelerometry-based PlayerLoad [...] Read more.
The purpose of this study was two-fold: (1) to determine the sensitivity of the sEMG shorts-derived training load (sEMG-TL) during different running speeds; and (2) to investigate the relationship between the oxygen consumption, heart rate (HR), rating of perceived exertion (RPE), accelerometry-based PlayerLoadTM (PL), and sEMG-TL during a running maximum oxygen uptake (V˙O2max) test. The study investigated ten healthy participants. On day one, participants performed a three-speed treadmill test at 8, 10, and 12 km·h−1 for 2 min at each speed. On day two, participants performed a V˙O2max test. Analysis of variance found significant differences in sEMG-TL at all three speeds (p < 0.05). A significantly weak positive relationship between sEMG-TL and %V˙O2max (r = 0.31, p < 0.05) was established, while significantly strong relationships for 8 out of 10 participants at the individual level (r = 0.72–0.97, p < 0.05) were found. Meanwhile, the accelerometry PL was not significantly related to %V˙O2max (p > 0.05) and only demonstrated significant correlations in 3 out of 10 participants at the individual level. Therefore, the sEMG shorts-derived training load was sensitive in detecting a work rate difference of at least 2 km·h−1. sEMG-TL may be an acceptable metric for the measurement of internal loads and could potentially be used as a surrogate for oxygen consumption. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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23 pages, 1890 KiB  
Article
A Multifunctional Network with Uncertainty Estimation and Attention-Based Knowledge Distillation to Address Practical Challenges in Respiration Rate Estimation
by Kapil Singh Rathore, Sricharan Vijayarangan, Preejith SP and Mohanasankar Sivaprakasam
Sensors 2023, 23(3), 1599; https://doi.org/10.3390/s23031599 - 01 Feb 2023
Cited by 1 | Viewed by 1617
Abstract
Respiration rate is a vital parameter to indicate good health, wellbeing, and performance. As the estimation through classical measurement modes are limited only to rest or during slow movements, respiration rate is commonly estimated through physiological signals such as electrocardiogram and photoplethysmography due [...] Read more.
Respiration rate is a vital parameter to indicate good health, wellbeing, and performance. As the estimation through classical measurement modes are limited only to rest or during slow movements, respiration rate is commonly estimated through physiological signals such as electrocardiogram and photoplethysmography due to the unobtrusive nature of wearable devices. Deep learning methodologies have gained much traction in the recent past to enhance accuracy during activities involving a lot of movement. However, these methods pose challenges, including model interpretability, uncertainty estimation in the context of respiration rate estimation, and model compactness in terms of deployment in wearable platforms. In this direction, we propose a multifunctional framework, which includes the combination of an attention mechanism, an uncertainty estimation functionality, and a knowledge distillation framework. We evaluated the performance of our framework on two datasets containing ambulatory movement. The attention mechanism visually and quantitatively improved instantaneous respiration rate estimation. Using Monte Carlo dropouts to embed the network with inferential uncertainty estimation resulted in the rejection of 3.7% of windows with high uncertainty, which consequently resulted in an overall reduction of 7.99% in the mean absolute error. The attention-aware knowledge distillation mechanism reduced the model’s parameter count and inference time by 49.5% and 38.09%, respectively, without any increase in error rates. Through experimentation, ablation, and visualization, we demonstrated the efficacy of the proposed framework in addressing practical challenges, thus taking a step towards deployment in wearable edge devices. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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15 pages, 1834 KiB  
Article
An eDiary App Approach for Collecting Physiological Sensor Data from Wearables together with Subjective Observations and Emotions
by Andreas Petutschnig, Steffen Reichel, Kristýna Měchurová and Bernd Resch
Sensors 2022, 22(16), 6120; https://doi.org/10.3390/s22166120 - 16 Aug 2022
Cited by 3 | Viewed by 1885
Abstract
Field measurement campaigns with traffic participants using wearable sensors and questionnaires can be challenging to carry out because of inconsistent interfaces across manufacturers for accessing sensor data and campaign-specific questionnaire contents bear large potential for errors. We present an app able to consolidate [...] Read more.
Field measurement campaigns with traffic participants using wearable sensors and questionnaires can be challenging to carry out because of inconsistent interfaces across manufacturers for accessing sensor data and campaign-specific questionnaire contents bear large potential for errors. We present an app able to consolidate data from multiple technical sensors and questionnaires. The functionality includes providing feedback for correct sensor platform mounting, accessing and storing all sensor and questionnaire data in a uniform data structure. To do this, the app implements a sensor data bus class that unifies data from technical sensors and questionnaires. The app can also be extended to accommodate other sensor platforms provided they have a suitable API. We also describe a database structure holding the data from multiple campaigns and test subjects in a privacy preserving fashion. Finally, we identify some potential issues and hints that practitioners may encounter when conducting a measurement campaign. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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20 pages, 1203 KiB  
Article
A Conditional GAN for Generating Time Series Data for Stress Detection in Wearable Physiological Sensor Data
by Maximilian Ehrhart, Bernd Resch, Clemens Havas and David Niederseer
Sensors 2022, 22(16), 5969; https://doi.org/10.3390/s22165969 - 10 Aug 2022
Cited by 9 | Viewed by 4246
Abstract
Human-centered applications using wearable sensors in combination with machine learning have received a great deal of attention in the last couple of years. At the same time, wearable sensors have also evolved and are now able to accurately measure physiological signals and are, [...] Read more.
Human-centered applications using wearable sensors in combination with machine learning have received a great deal of attention in the last couple of years. At the same time, wearable sensors have also evolved and are now able to accurately measure physiological signals and are, therefore, suitable for detecting body reactions to stress. The field of machine learning, or more precisely, deep learning, has been able to produce outstanding results. However, in order to produce these good results, large amounts of labeled data are needed, which, in the context of physiological data related to stress detection, are a great challenge to collect, as they usually require costly experiments or expert knowledge. This usually results in an imbalanced and small dataset, which makes it difficult to train a deep learning algorithm. In recent studies, this problem is tackled with data augmentation via a Generative Adversarial Network (GAN). Conditional GANs (cGAN) are particularly suitable for this as they provide the opportunity to feed auxiliary information such as a class label into the training process to generate labeled data. However, it has been found that during the training process of GANs, different problems usually occur, such as mode collapse or vanishing gradients. To tackle the problems mentioned above, we propose a Long Short-Term Memory (LSTM) network, combined with a Fully Convolutional Network (FCN) cGAN architecture, with an additional diversity term to generate synthetic physiological data, which are used to augment the training dataset to improve the performance of a binary classifier for stress detection. We evaluated the methodology on our collected physiological measurement dataset, and we were able to show that using the method, the performance of an LSTM and an FCN classifier could be improved. Further, we showed that the generated data could not be distinguished from the real data any longer. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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11 pages, 2574 KiB  
Article
Development and Characterization of Novel Conductive Sensing Fibers for In Vivo Nerve Stimulation
by Bertram Richter, Zachary Mace, Megan E. Hays, Santosh Adhikari, Huy Q. Pham, Robert J. Sclabassi, Benedict Kolber, Saigopalakrishna S. Yerneni, Phil Campbell, Boyle Cheng, Nestor Tomycz, Donald M. Whiting, Trung Q. Le, Toby L. Nelson and Saadyah Averick
Sensors 2021, 21(22), 7581; https://doi.org/10.3390/s21227581 - 15 Nov 2021
Cited by 1 | Viewed by 2052
Abstract
Advancements in electrode technologies to both stimulate and record the central nervous system’s electrical activities are enabling significant improvements in both the understanding and treatment of different neurological diseases. However, the current neural recording and stimulating electrodes are metallic, requiring invasive and damaging [...] Read more.
Advancements in electrode technologies to both stimulate and record the central nervous system’s electrical activities are enabling significant improvements in both the understanding and treatment of different neurological diseases. However, the current neural recording and stimulating electrodes are metallic, requiring invasive and damaging methods to interface with neural tissue. These electrodes may also degrade, resulting in additional invasive procedures. Furthermore, metal electrodes may cause nerve damage due to their inherent rigidity. This paper demonstrates that novel electrically conductive organic fibers (ECFs) can be used for direct nerve stimulation. The ECFs were prepared using a standard polyester material as the structural base, with a carbon nanotube ink applied to the surface as the electrical conductor. We report on three experiments: the first one to characterize the conductive properties of the ECFs; the second one to investigate the fiber cytotoxic properties in vitro; and the third one to demonstrate the utility of the ECF for direct nerve stimulation in an in vivo rodent model. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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11 pages, 2153 KiB  
Article
Wearable Cardioverter–Defibrillator-Measured Step Count for the Surveillance of Physical Fitness during Cardiac Rehabilitation
by Boldizsar Kovacs, Flavia Müller, David Niederseer, Nazmi Krasniqi, Ardan M. Saguner, Firat Duru and Matthias Hermann
Sensors 2021, 21(21), 7054; https://doi.org/10.3390/s21217054 - 25 Oct 2021
Cited by 1 | Viewed by 2076
Abstract
Background: The wearable cardioverter–defibrillator (WCD) has a built-in accelerometer, which allows tracking of patients’ physical activity by remote monitoring. It is unclear whether WCD-measured physical activity, step count, and heart rate correlate with established tools for the assessment of cardiopulmonary fitness such as [...] Read more.
Background: The wearable cardioverter–defibrillator (WCD) has a built-in accelerometer, which allows tracking of patients’ physical activity by remote monitoring. It is unclear whether WCD-measured physical activity, step count, and heart rate correlate with established tools for the assessment of cardiopulmonary fitness such as the 6-min walk test (6MWT). Objective: To correlate measurements of patient physical activity through the WCD with a supervised 6MWT during in-patient cardiac rehabilitation (CR) and to allow their use as surrogate parameters of cardiopulmonary fitness in an out-patient setting. Methods: Consecutive patients with a history of WCD use treated at our center and an in-patient CR following an index hospitalization were included. Baseline characteristics, measurements of WCD accelerometer (median daily step count, median daily activity level), median daily heart rate, and clinically supervised 6MWT at admission and discharge of CR were obtained. Results: Forty-one patients with a mean age of 55.5 (±11.5) years were included. Thirty-five patients (85.4%) were male and 28 patients (68%) had a primary prophylactic WCD-indication. The most common underlying heart diseases were ischemic heart disease (24 patients 58.6%) and dilated cardiomyopathy (13 patients, 31.7%). Median CR duration was 20 (IQR 19.75–26.25) days. 6MWT distance increased from a mean of 329 m (±107) to 470 m (±116) during CR (p < 0.0001). The median daily step count and activity level increased significantly, from 5542 steps (IQR 3718–7055) to 8778 (IQR 6229–12,920, p < 0.0001) and median 117 × 106 (IQR 96 × 106–142 × 106) threshold value exceedance (TVE) to 146 × 106 TVE (IQR 110 × 106–169 × 106, p < 0.0001), respectively. The median heart rate was 74.9 bpm (IQR 65.8–84.5) and 70.2 (IQR 64.1–77.3, p = 0.09) at admission and discharge, respectively. Of all three parameters, median daily step count showed the best correlation to the results of the 6MWT at admission and discharge (r = 0.32, p = 0.04 and 0.37, p = 0.02, respectively). Conclusions: Remote monitoring of median daily step count as assessed by the WCD’s accelerometer showed positive correlation with the 6MWT and could serve as a surrogate for cardiopulmonary exercise capacity. Assessment of daily step count and activity level measured remotely by the WCD could help to tailor optimal exercise instruction for patients not attending CR. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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11 pages, 1125 KiB  
Communication
Validity of Peripheral Oxygen Saturation Measurements with the Garmin Fēnix® 5X Plus Wearable Device at 4559 m
by Lisa M. Schiefer, Gunnar Treff, Franziska Treff, Peter Schmidt, Larissa Schäfer, Josef Niebauer, Kai E. Swenson, Erik R. Swenson, Marc M. Berger and Mahdi Sareban
Sensors 2021, 21(19), 6363; https://doi.org/10.3390/s21196363 - 23 Sep 2021
Cited by 9 | Viewed by 3619
Abstract
Decreased oxygen saturation (SO2) at high altitude is associated with potentially life-threatening diseases, e.g., high-altitude pulmonary edema. Wearable devices that allow continuous monitoring of peripheral oxygen saturation (SpO2), such as the Garmin Fēnix® 5X Plus (GAR), might provide [...] Read more.
Decreased oxygen saturation (SO2) at high altitude is associated with potentially life-threatening diseases, e.g., high-altitude pulmonary edema. Wearable devices that allow continuous monitoring of peripheral oxygen saturation (SpO2), such as the Garmin Fēnix® 5X Plus (GAR), might provide early detection to prevent hypoxia-induced diseases. We therefore aimed to validate GAR-derived SpO2 readings at 4559 m. SpO2 was measured with GAR and the medically certified Covidien Nellcor SpO2 monitor (COV) at six time points in 13 healthy lowlanders after a rapid ascent from 1130 m to 4559 m. Arterial blood gas (ABG) analysis served as the criterion measure and was conducted at four of the six time points with the Radiometer ABL 90 Flex. Validity was assessed by intraclass correlation coefficients (ICCs), mean absolute percentage error (MAPE), and Bland–Altman plots. Mean (±SD) SO2, including all time points at 4559 m, was 85.2 ± 6.2% with GAR, 81.0 ± 9.4% with COV, and 75.0 ± 9.5% with ABG. Validity of GAR was low, as indicated by the ICC (0.549), the MAPE (9.77%), the mean SO2 difference (7.0%), and the wide limits of agreement (−6.5; 20.5%) vs. ABG. Validity of COV was good, as indicated by the ICC (0.883), the MAPE (6.15%), and the mean SO2 difference (0.1%) vs. ABG. The GAR device demonstrated poor validity and cannot be recommended for monitoring SpO2 at high altitude. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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19 pages, 2827 KiB  
Article
An Integrated Individual Environmental Exposure Assessment System for Real-Time Mobile Sensing in Environmental Health Studies
by Jue Wang, Lirong Kou, Mei-Po Kwan, Rebecca Marie Shakespeare, Kangjae Lee and Yoo Min Park
Sensors 2021, 21(12), 4039; https://doi.org/10.3390/s21124039 - 11 Jun 2021
Cited by 14 | Viewed by 4413
Abstract
The effects of environmental exposure on human health have been widely explored by scholars in health geography for decades. However, recent advances in geospatial technologies, especially the development of mobile approaches to collecting real-time and high-resolution individual data, have enabled sophisticated methods for [...] Read more.
The effects of environmental exposure on human health have been widely explored by scholars in health geography for decades. However, recent advances in geospatial technologies, especially the development of mobile approaches to collecting real-time and high-resolution individual data, have enabled sophisticated methods for assessing people’s environmental exposure. This study proposes an individual environmental exposure assessment system (IEEAS) that integrates objective real-time monitoring devices and subjective sensing tools to provide a composite way for individual-based environmental exposure data collection. With field test data collected in Chicago and Beijing, we illustrate and discuss the advantages of the proposed IEEAS and the composite analysis that could be applied. Data collected with the proposed IEEAS yield relatively accurate measurements of individual exposure in a composite way, and offer new opportunities for developing more sophisticated ways to measure individual environmental exposure. With the capability to consider both the variations in environmental risks and human mobility in high spatial and temporal resolutions, the IEEAS also helps mitigate some uncertainties in environmental exposure assessment and thus enables a better understanding of the relationship between individual environmental exposure and health outcomes. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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18 pages, 2030 KiB  
Article
Evaluation of a Low-Cost Commercial Actigraph and Its Potential Use in Detecting Cultural Variations in Physical Activity and Sleep
by Pavlos Topalidis, Cristina Florea, Esther-Sevil Eigl, Anton Kurapov, Carlos Alberto Beltran Leon and Manuel Schabus
Sensors 2021, 21(11), 3774; https://doi.org/10.3390/s21113774 - 29 May 2021
Cited by 20 | Viewed by 4440
Abstract
The purpose of the present study was to evaluate the performance of a low-cost commercial smartwatch, the Xiaomi Mi Band (MB), in extracting physical activity and sleep-related measures and show its potential use in addressing questions that require large-scale real-time data and/or intercultural [...] Read more.
The purpose of the present study was to evaluate the performance of a low-cost commercial smartwatch, the Xiaomi Mi Band (MB), in extracting physical activity and sleep-related measures and show its potential use in addressing questions that require large-scale real-time data and/or intercultural data including low-income countries. We evaluated physical activity and sleep-related measures and discussed the potential application of such devices for large-scale step and sleep data acquisition. To that end, we conducted two separate studies. In Study 1, we evaluated the performance of MB by comparing it to the GT3X (ActiGraph, wGT3X-BT), a scientific actigraph used in research, as well as subjective sleep reports. In Study 2, we distributed the MB across four countries (Austria, Germany, Cuba, and Ukraine) and investigated physical activity and sleep among these countries. The results of Study 1 indicated that MB step counts correlated highly with the scientific GT3X device, but did display biases. In addition, the MB-derived wake-up and total-sleep-times showed high agreement with subjective reports, but partly deviated from GT3X predictions. Study 2 revealed similar MB step counts across countries, but significant later wake-up and bedtimes for Ukraine than the other countries. We hope that our studies will stimulate future large-scale sensor-based physical activity and sleep research studies, including various cultures. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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21 pages, 1586 KiB  
Article
The Cardiovascular Response to Interval Exercise Is Modified by the Contraction Type and Training in Proportion to Metabolic Stress of Recruited Muscle Groups
by Benedikt Gasser, Daniel Fitze, Martino Franchi, Annika Frei, David Niederseer, Christian M. Schmied, Silvio Catuogno, Walter Frey and Martin Flück
Sensors 2021, 21(1), 173; https://doi.org/10.3390/s21010173 - 29 Dec 2020
Cited by 3 | Viewed by 2704
Abstract
Background: Conventional forms of endurance training based on shortening contractions improve aerobic capacity but elicit a detriment of muscle strength. We hypothesized that eccentric interval training, loading muscle during the lengthening phase of contraction, overcome this interference and potentially adverse cardiovascular reactions, enhancing [...] Read more.
Background: Conventional forms of endurance training based on shortening contractions improve aerobic capacity but elicit a detriment of muscle strength. We hypothesized that eccentric interval training, loading muscle during the lengthening phase of contraction, overcome this interference and potentially adverse cardiovascular reactions, enhancing both muscle metabolism and strength, in association with the stress experienced during exercise. Methods: Twelve healthy participants completed an eight-week program of work-matched progressive interval-type pedaling exercise on a soft robot under predominately concentric or eccentric load. Results: Eccentric interval training specifically enhanced the peak power of positive anaerobic contractions (+28%), mitigated the strain on muscle’s aerobic metabolism, and lowered hemodynamic stress during interval exercise, concomitant with a lowered contribution of positive work to the target output. Concentric training alone lowered blood glucose concentration during interval exercise and mitigated heart rate and blood lactate concentration during ramp exercise. Training-induced adjustments for lactate and positive peak power were independently correlated (p < 0.05, |r| > 0.7) with indices of metabolic and mechanical muscle stress during exercise. Discussion: Task-specific improvements in strength and muscle’s metabolic capacity were induced with eccentric interval exercise lowering cardiovascular risk factors, except for blood glucose concentration, possibly through altered neuromuscular coordination. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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12 pages, 1489 KiB  
Article
Minimally Invasive Electrochemical Patch-Based Sensor System for Monitoring Glucose and Lactate in the Human Body—A Survey-Based Analysis of the End-User’s Perspective
by Roman Holzer, Wilhelm Bloch and Christian Brinkmann
Sensors 2020, 20(20), 5761; https://doi.org/10.3390/s20205761 - 11 Oct 2020
Cited by 12 | Viewed by 3278
Abstract
Background: Wearable electrochemical sensors that detect human biomarkers allow a comprehensive analysis of a person’s health condition. The “electronic smart patch system for wireless monitoring of molecular biomarkers for health care and well-being” (ELSAH) project aims to develop a minimally invasive sensor system [...] Read more.
Background: Wearable electrochemical sensors that detect human biomarkers allow a comprehensive analysis of a person’s health condition. The “electronic smart patch system for wireless monitoring of molecular biomarkers for health care and well-being” (ELSAH) project aims to develop a minimally invasive sensor system that is capable of continuously monitoring glucose and lactate in the dermal interstitial fluid in real time. It is the objective of the present study to compare the intended ELSAH-patch specifications with the expectations and requirements of potential end-users at an early stage during the development phase. Methods: A questionnaire addressing different aspects of the ELSAH-patch was filled out by 383 respondents. Results: The participants stated a high general demand for such a system, and they would use the ELSAH-patch in different health care and physical fitness applications. The preferred terminal device for communication with the sensor would be the smartphone. An operating time of 24 hours would be sufficient for 55.8% of the users (95%-CI: 50.3–61.3%), while 43.5% of them (95%-CI: 38.0–48.9%) would prefer a lifetime of several days or more. The software should have a warning function, especially for critical health conditions. Since the measured personal data would be highly sensitive, the participants called for high standards for data security and privacy. Conclusion: In general, the participants’ responses on their expectations and requirements were well in line with the intended specifications of the ELSAH-patch system. However, certain technical aspects such as the lifetime, data security and accuracy require special attention during its development. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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Review

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18 pages, 3675 KiB  
Review
Multiparameter Monitoring with a Wearable Cardioverter Defibrillator
by Ursula Rohrer, Martin Manninger, Andreas Zirlik and Daniel Scherr
Sensors 2022, 22(1), 22; https://doi.org/10.3390/s22010022 - 21 Dec 2021
Cited by 6 | Viewed by 4599
Abstract
A wearable cardioverter-defibrillator (WCD) is a temporary treatment option for patients at high risk for sudden cardiac death (SCD) and for patients who are temporarily not candidates for an implantable cardioverter defibrillator (ICD). In addition, the need for telemedical concepts in the detection [...] Read more.
A wearable cardioverter-defibrillator (WCD) is a temporary treatment option for patients at high risk for sudden cardiac death (SCD) and for patients who are temporarily not candidates for an implantable cardioverter defibrillator (ICD). In addition, the need for telemedical concepts in the detection and treatment of heart failure (HF) and its arrhythmias is growing. The WCD has evolved from a shock device detecting malignant ventricular arrhythmias (VA) and treating them with shocks to a heart-failure-monitoring device that captures physical activity and cardioacoustic biomarkers as surrogate parameters for HF to help the treating physician surveil and guide the HF therapy of each individual patient. In addition to its important role in preventing SCD, the WCD could become an important tool in heart failure treatment by helping prevent HF events by detecting imminent decompensation via remote monitoring and monitoring therapy success. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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21 pages, 667 KiB  
Review
Assessing the Tidal Volume through Wearables: A Scoping Review
by Vito Monaco and Cesare Stefanini
Sensors 2021, 21(12), 4124; https://doi.org/10.3390/s21124124 - 16 Jun 2021
Cited by 15 | Viewed by 2700
Abstract
The assessment of respiratory activity based on wearable devices is becoming an area of growing interest due to the wide range of available sensors. Accordingly, this scoping review aims to identify research evidence supporting the use of wearable devices to monitor the tidal [...] Read more.
The assessment of respiratory activity based on wearable devices is becoming an area of growing interest due to the wide range of available sensors. Accordingly, this scoping review aims to identify research evidence supporting the use of wearable devices to monitor the tidal volume during both daily activities and clinical settings. A screening of the literature (Pubmed, Scopus, and Web of Science) was carried out in December 2020 to collect studies: i. comparing one or more methodological approaches for the assessment of tidal volume with the outcome of a state-of-the-art measurement device (i.e., spirometry or optoelectronic plethysmography); ii. dealing with technological solutions designed to be exploited in wearable devices. From the initial 1031 documents, only 36 citations met the eligibility criteria. These studies highlighted that the tidal volume can be estimated by using different technologies ranging from IMUs to strain sensors (e.g., resistive, capacitive, inductive, electromagnetic, and optical) or acoustic sensors. Noticeably, the relative volumetric error of these solutions during quasi-static tasks (e.g., resting and sitting) is typically ≥10% but it deteriorates during dynamic motor tasks (e.g., walking). As such, additional efforts are required to improve the performance of these devices and to identify possible applications based on their accuracy and reliability. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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20 pages, 1905 KiB  
Review
The Use of Pulse Oximetry in the Assessment of Acclimatization to High Altitude
by Tobias Dünnwald, Roland Kienast, David Niederseer and Martin Burtscher
Sensors 2021, 21(4), 1263; https://doi.org/10.3390/s21041263 - 10 Feb 2021
Cited by 29 | Viewed by 7294
Abstract
Background: Finger pulse oximeters are widely used to monitor physiological responses to high-altitude exposure, the progress of acclimatization, and/or the potential development of high-altitude related diseases. Although there is increasing evidence for its invaluable support at high altitude, some controversy remains, largely [...] Read more.
Background: Finger pulse oximeters are widely used to monitor physiological responses to high-altitude exposure, the progress of acclimatization, and/or the potential development of high-altitude related diseases. Although there is increasing evidence for its invaluable support at high altitude, some controversy remains, largely due to differences in individual preconditions, evaluation purposes, measurement methods, the use of different devices, and the lacking ability to interpret data correctly. Therefore, this review is aimed at providing information on the functioning of pulse oximeters, appropriate measurement methods and published time courses of pulse oximetry data (peripheral oxygen saturation, (SpO2) and heart rate (HR), recorded at rest and submaximal exercise during exposure to various altitudes. Results: The presented findings from the literature review confirm rather large variations of pulse oximetry measures (SpO2 and HR) during acute exposure and acclimatization to high altitude, related to the varying conditions between studies mentioned above. It turned out that particularly SpO2 levels decrease with acute altitude/hypoxia exposure and partly recover during acclimatization, with an opposite trend of HR. Moreover, the development of acute mountain sickness (AMS) was consistently associated with lower SpO2 values compared to individuals free from AMS. Conclusions: The use of finger pulse oximetry at high altitude is considered as a valuable tool in the evaluation of individual acclimatization to high altitude but also to monitor AMS progression and treatment efficacy. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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17 pages, 1023 KiB  
Review
Mobile Technologies to Promote Physical Activity during Cardiac Rehabilitation: A Scoping Review
by Florian Meinhart, Thomas Stütz, Mahdi Sareban, Stefan Tino Kulnik and Josef Niebauer
Sensors 2021, 21(1), 65; https://doi.org/10.3390/s21010065 - 24 Dec 2020
Cited by 23 | Viewed by 5146
Abstract
Promoting regular physical activity (PA) and improving exercise capacity are the primary goals of cardiac rehabilitation (CR). Mobile technologies (mTechs) like smartphones, smartwatches, and fitness trackers might help patients in reaching these goals. This review aimed to scope current scientific literature on mTechs [...] Read more.
Promoting regular physical activity (PA) and improving exercise capacity are the primary goals of cardiac rehabilitation (CR). Mobile technologies (mTechs) like smartphones, smartwatches, and fitness trackers might help patients in reaching these goals. This review aimed to scope current scientific literature on mTechs in CR to assess the impact on patients’ exercise capacity and to identify gaps and future directions for research. PubMed, CENTRAL, and CDSR were systematically searched for randomized controlled trials (RCTs). These RCTs had to utilize mTechs to objectively monitor and promote PA of patients during or following CR, aim at improvements in exercise capacity, and be published between December 2014 and December 2019. A total of 964 publications were identified, and 13 studies met all inclusion criteria. Home-based CR with mTechs vs. outpatient CR without mTechs and outpatient CR with mTechs vs. outpatient CR without mTechs did not lead to statistically significant differences in exercise capacity. In contrast, outpatient CR followed by home-based CR with mTechs led to significant improvement in exercise capacity as compared to outpatient CR without further formal CR. Supplying patients with mTechs may improve exercise capacity. To ensure that usage of and compliance with mTechs is optimal, a concentrated effort of CR staff has to be achieved. The COVID-19 pandemic has led to an unprecedented lack of patient support while away from institutional CR. Even though mTechs lend themselves as suitable assistants, evidence is lacking that they can fill this gap. Full article
(This article belongs to the Special Issue Wearable Sensors for Health and Physiological Monitoring)
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