Sensors

Research

Jump to: Review

16 pages, 3492 KiB

Open AccessArticle

Wearable EMG Measurement Device Using Polyurethane Foam for Motion Artifact Suppression

by Takuma Takagi, Naoto Tomita, Suguru Sato, Michitaka Yamamoto, Seiichi Takamatsu and Toshihiro Itoh

Sensors 2024, 24(10), 2985; https://doi.org/10.3390/s24102985 - 8 May 2024

Viewed by 300

Abstract

We propose the use of a specially designed polyurethane foam with a plateau region in its mechanical characteristics—where stress remains nearly constant during deformation—between the electromyography (EMG) electrode and clothing to suppress motion artifacts in EMG measurement. Wearable EMG devices are receiving attention [...] Read more.

We propose the use of a specially designed polyurethane foam with a plateau region in its mechanical characteristics—where stress remains nearly constant during deformation—between the electromyography (EMG) electrode and clothing to suppress motion artifacts in EMG measurement. Wearable EMG devices are receiving attention for monitoring muscle weakening due to aging. However, daily EMG measurement has been challenging due to motion artifacts caused by changes in the contact pressure between the bioelectrode and the skin. Therefore, this study aims to measure EMG signals in daily movement environments by controlling the contact pressure using polyurethane foam between the bioelectrode on the clothing and the skin. Through mechanical calculations and finite element method simulations of the polyurethane foam’s effect, we clarified that the characteristics of the polyurethane foam significantly influence contact pressure control and that the contact pressure is adjustable through the polyurethane foam thickness. The optimization of the design successfully controlled the contact pressure between the bioelectrode and skin from 1.0 kPa to 2.0 kPa, effectively suppressing the motion artifact in EMG measurement. Full article

(This article belongs to the Special Issue Human Health and Performance Monitoring Sensors)

► Show Figures

Figure 1

15 pages, 4049 KiB

Open AccessArticle

Identification of the Biomechanical Response of the Muscles That Contract the Most during Disfluencies in Stuttered Speech

by Edu Marin, Nicole Unsihuay, Victoria E. Abarca and Dante A. Elias

Sensors 2024, 24(8), 2629; https://doi.org/10.3390/s24082629 - 20 Apr 2024

Viewed by 745

Abstract

Stuttering, affecting approximately 1% of the global population, is a complex speech disorder significantly impacting individuals’ quality of life. Prior studies using electromyography (EMG) to examine orofacial muscle activity in stuttering have presented mixed results, highlighting the variability in neuromuscular responses during stuttering [...] Read more.

Stuttering, affecting approximately 1% of the global population, is a complex speech disorder significantly impacting individuals’ quality of life. Prior studies using electromyography (EMG) to examine orofacial muscle activity in stuttering have presented mixed results, highlighting the variability in neuromuscular responses during stuttering episodes. Fifty-five participants with stuttering and 30 individuals without stuttering, aged between 18 and 40, participated in the study. EMG signals from five facial and cervical muscles were recorded during speech tasks and analyzed for mean amplitude and frequency activity in the 5–15 Hz range to identify significant differences. Upon analysis of the 5–15 Hz frequency range, a higher average amplitude was observed in the zygomaticus major muscle for participants while stuttering (p < 0.05). Additionally, when assessing the overall EMG signal amplitude, a higher average amplitude was observed in samples obtained from disfluencies in participants who did not stutter, particularly in the depressor anguli oris muscle (p < 0.05). Significant differences in muscle activity were observed between the two groups, particularly in the depressor anguli oris and zygomaticus major muscles. These results suggest that the underlying neuromuscular mechanisms of stuttering might involve subtle aspects of timing and coordination in muscle activation. Therefore, these findings may contribute to the field of biosensors by providing valuable perspectives on neuromuscular mechanisms and the relevance of electromyography in stuttering research. Further research in this area has the potential to advance the development of biosensor technology for language-related applications and therapeutic interventions in stuttering. Full article

(This article belongs to the Special Issue Human Health and Performance Monitoring Sensors)

► Show Figures

Figure 1

12 pages, 1353 KiB

Open AccessArticle

Impaired Lumbar Extensor Force Control Is Associated with Increased Lifting Knee Velocity in People with Chronic Low-Back Pain

by Adrian Pranata, Joshua Farragher, Luke Perraton, Doa El-Ansary, Ross Clark, Denny Meyer, Jia Han, Benjamin Mentiplay and Adam L. Bryant

Sensors 2023, 23(21), 8855; https://doi.org/10.3390/s23218855 - 31 Oct 2023

Viewed by 966

Abstract

The ability of the lumbar extensor muscles to accurately control static and dynamic forces is important during daily activities such as lifting. Lumbar extensor force control is impaired in low-back pain patients and may therefore explain the variances in lifting kinematics. Thirty-three chronic [...] Read more.

The ability of the lumbar extensor muscles to accurately control static and dynamic forces is important during daily activities such as lifting. Lumbar extensor force control is impaired in low-back pain patients and may therefore explain the variances in lifting kinematics. Thirty-three chronic low-back pain participants were instructed to lift weight using a self-selected technique. Participants also performed an isometric lumbar extension task where they increased and decreased their lumbar extensor force output to match a variable target force within 20–50% lumbar extensor maximal voluntary contraction. Lifting trunk and lower limb range of motion and angular velocity variables derived from phase plane analysis in all planes were calculated. Lumbar extensor force control was analyzed by calculating the Root-Mean-Square Error (RMSE) between the participants’ force and the target force during the increasing (RMSE_A), decreasing (RMSE_D) force portions and for the overall force error (RMSE_T) of the test. The relationship between lifting kinematics and RMSE variables was analyzed using multiple linear regression. Knee angular velocity in the sagittal and coronal planes were positively associated with RMSE_A (R² = 0.10, β = 0.35, p = 0.046 and R² = 0.21, β = 0.48, p = 0.004, respectively). Impaired lumbar extensor force control is associated with increased multiplanar knee movement velocity during lifting. The study findings suggest a potential relationship between lumbar and lower limb neuromuscular function in people with chronic low-back pain. Full article

(This article belongs to the Special Issue Human Health and Performance Monitoring Sensors)

► Show Figures

Figure 1

24 pages, 7551 KiB

Open AccessArticle

Best Practices for Body Temperature Measurement with Infrared Thermography: External Factors Affecting Accuracy

by Siavash Mazdeyasna, Pejman Ghassemi and Quanzeng Wang

Sensors 2023, 23(18), 8011; https://doi.org/10.3390/s23188011 - 21 Sep 2023

Cited by 2 | Viewed by 2244

Abstract

Infrared thermographs (IRTs) are commonly used during disease pandemics to screen individuals with elevated body temperature (EBT). To address the limited research on external factors affecting IRT accuracy, we conducted benchtop measurements and computer simulations with two IRTs, with or without an external [...] Read more.

Infrared thermographs (IRTs) are commonly used during disease pandemics to screen individuals with elevated body temperature (EBT). To address the limited research on external factors affecting IRT accuracy, we conducted benchtop measurements and computer simulations with two IRTs, with or without an external temperature reference source (ETRS) for temperature compensation. The combination of an IRT and an ETRS forms a screening thermograph (ST). We investigated the effects of viewing angle (θ, 0–75°), ETRS set temperature (

T_{E T R S}

, 30–40 °C), ambient temperature (

T_{a t m}

, 18–32 °C), relative humidity (RH, 15–80%), and working distance (d, 0.4–2.8 m). We discovered that STs exhibited higher accuracy compared to IRTs alone. Across the tested ranges of

T_{a t m}

and RH, both IRTs exhibited absolute measurement errors of less than 0.97 °C, while both STs maintained absolute measurement errors of less than 0.12 °C. The optimal

T_{E T R S}

for EBT detection was 36–37 °C. When θ was below 30°, the two STs underestimated calibration source (CS) temperature (

T_{C S}

) of less than 0.05 °C. The computer simulations showed absolute temperature differences of up to 0.28 °C and 0.04 °C between estimated and theoretical temperatures for IRTs and STs, respectively, considering d of 0.2–3.0 m,

T_{a t m}

of 15–35 °C, and RH of 5–95%. The results highlight the importance of precise calibration and environmental control for reliable temperature readings and suggest proper ranges for these factors, aiming to enhance current standard documents and best practice guidelines. These insights enhance our understanding of IRT performance and their sensitivity to various factors, thereby facilitating the development of best practices for accurate EBT measurement. Full article

(This article belongs to the Special Issue Human Health and Performance Monitoring Sensors)

► Show Figures

Figure 1

10 pages, 307 KiB

Open AccessArticle

What Is the Most Sensitive Test to Identify Fatigue through the Analysis of Neuromuscular Status in Male Elite Futsal Players?

by Adrián Moreno-Villanueva, Markel Rico-González, Carlos D. Gómez-Carmona, Miguel Á. Gómez-Ruano, Nuno Silva and José Pino-Ortega

Sensors 2022, 22(20), 7702; https://doi.org/10.3390/s22207702 - 11 Oct 2022

Cited by 1 | Viewed by 1452

Abstract

The present study aimed to determine which of the neuromuscular status (NMS) monitoring tests (1: Counter-movement jump, CMJ; 2: back squat with additional load) is the most sensitive and effective for evaluating the state of fatigue in futsal players during the preseason. Seventeen [...] Read more.

The present study aimed to determine which of the neuromuscular status (NMS) monitoring tests (1: Counter-movement jump, CMJ; 2: back squat with additional load) is the most sensitive and effective for evaluating the state of fatigue in futsal players during the preseason. Seventeen professional futsal players were recruited for this study (age: 23.07 ± 6.76 years; height: 1.75 ± 0.06 m; body mass: 75.47 ± 7.47 kg; playing experience in elite: 5.38 ± 2.03 years). All of them were evaluated during the preseason phase in two tests (CMJ and back squat with additional load) before and after each training session (pre- vs. post-test). A jump platform was used to extract jump height during CMJ, while a linear position transducer was used to extract mean velocity (MV) and mean propulsive velocity (MPV) during the back squat exercise. Significant differences were obtained for intra-subject analysis for MV and MPV in loaded back squat exercise (p < 0.001), finding lower values during the post-test. In conclusion, the monitoring of NMS through the back squat provides greater sensitivity and objectivity in comparison with CMJ, due to a more direct neuromuscular extrapolation to the physical demands of futsal. Full article

(This article belongs to the Special Issue Human Health and Performance Monitoring Sensors)

11 pages, 3136 KiB

Open AccessArticle

Microfluidic Thermal Flowmeters for Drug Injection Monitoring

by Il Doh, Daniel Sim and Steve S. Kim

Sensors 2022, 22(9), 3151; https://doi.org/10.3390/s22093151 - 20 Apr 2022

Cited by 6 | Viewed by 2276

Abstract

This paper presents a microfluidic thermal flowmeter for monitoring injection pumps, which is essential to ensure proper patient treatment and reduce medication errors that can lead to severe injury or death. The standard gravimetric method for flow-rate monitoring requires a great deal of [...] Read more.

This paper presents a microfluidic thermal flowmeter for monitoring injection pumps, which is essential to ensure proper patient treatment and reduce medication errors that can lead to severe injury or death. The standard gravimetric method for flow-rate monitoring requires a great deal of preparation and laboratory equipment and is impractical in clinics. Therefore, an alternative to the standard method suitable for remote, small-scale, and frequent infusion-pump monitoring is in great demand. Here, we propose a miniaturized thermal flowmeter consisting of a silicon substrate, a platinum heater layer on a silicon dioxide thin-membrane, and a polymer microchannel to provide accurate flow-rate measurement. The present thermal flowmeter is fabricated by the micromachining and micromolding process and exhibits sensitivity, linearity, and uncertainty of 0.722 mW/(g/h), 98.7%, and (2.36 ± 0.80)%, respectively, in the flow-rate range of 0.5–2.5 g/h when the flowmeter is operated in the constant temperature mode with the channel width of 0.5 mm. The measurement range of flow rate can be easily adjusted by changing the cross-sectional microchannel dimension. The present miniaturized thermal flowmeter shows a high potential for infusion-pump calibration in clinical settings. Full article

(This article belongs to the Special Issue Human Health and Performance Monitoring Sensors)

► Show Figures

Figure 1

Review

Jump to: Research

43 pages, 13674 KiB

Open AccessReview

Wearable Biosensor Technology in Education: A Systematic Review

by María A. Hernández-Mustieles, Yoshua E. Lima-Carmona, Maxine A. Pacheco-Ramírez, Axel A. Mendoza-Armenta, José Esteban Romero-Gómez, César F. Cruz-Gómez, Diana C. Rodríguez-Alvarado, Alejandro Arceo, Jesús G. Cruz-Garza, Mauricio A. Ramírez-Moreno and Jorge de J. Lozoya-Santos

Sensors 2024, 24(8), 2437; https://doi.org/10.3390/s24082437 - 11 Apr 2024

Viewed by 984

Abstract

Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012–2022), highlighting the evolution of this field to [...] Read more.

Wearable Biosensor Technology (WBT) has emerged as a transformative tool in the educational system over the past decade. This systematic review encompasses a comprehensive analysis of WBT utilization in educational settings over a 10-year span (2012–2022), highlighting the evolution of this field to address challenges in education by integrating technology to solve specific educational challenges, such as enhancing student engagement, monitoring stress and cognitive load, improving learning experiences, and providing real-time feedback for both students and educators. By exploring these aspects, this review sheds light on the potential implications of WBT on the future of learning. A rigorous and systematic search of major academic databases, including Google Scholar and Scopus, was conducted in accordance with the PRISMA guidelines. Relevant studies were selected based on predefined inclusion and exclusion criteria. The articles selected were assessed for methodological quality and bias using established tools. The process of data extraction and synthesis followed a structured framework. Key findings include the shift from theoretical exploration to practical implementation, with EEG being the predominant measurement, aiming to explore mental states, physiological constructs, and teaching effectiveness. Wearable biosensors are significantly impacting the educational field, serving as an important resource for educators and a tool for students. Their application has the potential to transform and optimize academic practices through sensors that capture biometric data, enabling the implementation of metrics and models to understand the development and performance of students and professors in an academic environment, as well as to gain insights into the learning process. Full article

(This article belongs to the Special Issue Human Health and Performance Monitoring Sensors)

► Show Figures

Figure 1

30 pages, 2233 KiB

Open AccessReview

Microsoft HoloLens 2 in Medical and Healthcare Context: State of the Art and Future Prospects

by Arrigo Palumbo

Sensors 2022, 22(20), 7709; https://doi.org/10.3390/s22207709 - 11 Oct 2022

Cited by 43 | Viewed by 7357

Abstract

In the world reference context, although virtual reality, augmented reality and mixed reality have been emerging methodologies for several years, only today technological and scientific advances have made them suitable to revolutionize clinical care and medical contexts through the provision of enhanced functionalities [...] Read more.

In the world reference context, although virtual reality, augmented reality and mixed reality have been emerging methodologies for several years, only today technological and scientific advances have made them suitable to revolutionize clinical care and medical contexts through the provision of enhanced functionalities and improved health services. This systematic review provides the state-of-the-art applications of the Microsoft^® HoloLens 2 in a medical and healthcare context. Focusing on the potential that this technology has in providing digitally supported clinical care, also but not only in relation to the COVID-19 pandemic, studies that proved the applicability and feasibility of HoloLens 2 in a medical and healthcare scenario were considered. The review presents a thorough examination of the different studies conducted since 2019, focusing on HoloLens 2 medical sub-field applications, device functionalities provided to users, software/platform/framework used, as well as the study validation. The results provided in this paper could highlight the potential and limitations of the HoloLens 2-based innovative solutions and bring focus to emerging research topics, such as telemedicine, remote control and motor rehabilitation. Full article

(This article belongs to the Special Issue Human Health and Performance Monitoring Sensors)

► Show Figures