The Wearable Devices about the Sodium Detection

Research Article
Open access

The Wearable Devices about the Sodium Detection

Yixuan Lu 1*
  • 1 Qingdao University of Science and Technology    
  • *corresponding author 1577935058lu@gmail.com
Published on 10 January 2025 | https://doi.org/10.54254/2755-2721/2025.20011
ACE Vol.124
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-83558-887-1
ISBN (Online): 978-1-83558-888-8

Abstract

This article focuses on wearable devices which used for detecting sodium. Sodium is an important parameter for assessing the state of our body, and real-time monitoring is essential. The amount of sodium in sweat is important because the level could show more like hydration assessment, exercise performance, medical conditions, individual differences, heat-related illnesses, and optimizing hydration strategies. The measurement of sodium content involves iontophoresis for stimulating sweat and electrochemical analysis which will use ion-selective electrodes. To ensure the accuracy of the measurement, solutions to the increase in sweat were proposed, including consideration of individual differences, minimization of contamination, and control of temperature and environmental factors. The factors that will influence the result of the measurement need to be eliminated. Advancements in materials for micro circuits and circuit structures are also discussed. The development of a wearable device for real-time sodium monitoring holds promise for health management, and challenges such as accuracy and environmental factors are being addressed

Keywords:

Wearable devices, sodium detection, sweat, athletic performance, medical conditions

Lu,Y. (2025). The Wearable Devices about the Sodium Detection. Applied and Computational Engineering,124,61-67.
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The Wearable Devices about the Sodium Detection

Yixuan Lu1,a,*

1School of Electronics and Information Engineering, Qingdao University of Science and Technology, No. 53 Zhengzhou Road, Shibei District, Qingdao, Shandong, 266042, China

a. 1577935058lu@gmail.com

*corresponding author

Abstract: This article focuses on wearable devices which used for detecting sodium. Sodium is an important parameter for assessing the state of our body, and real-time monitoring is essential. The amount of sodium in sweat is important because the level could show more like hydration assessment, exercise performance, medical conditions, individual differences, heat-related illnesses, and optimizing hydration strategies. The measurement of sodium content involves iontophoresis for stimulating sweat and electrochemical analysis which will use ion-selective electrodes. To ensure the accuracy of the measurement, solutions to the increase in sweat were proposed, including consideration of individual differences, minimization of contamination, and control of temperature and environmental factors. The factors that will influence the result of the measurement need to be eliminated. Advancements in materials for micro circuits and circuit structures are also discussed. The development of a wearable device for real-time sodium monitoring holds promise for health management, and challenges such as accuracy and environmental factors are being addressed.

Keywords: Wearable devices, sodium detection, sweat, athletic performance, medical conditions.

1. Introduction

Sodium is an important parameter which could provide us several information about our bodies’ state. By measurement this we could avoid risk and keep healthy. To make sure we have good physical conditions. The real-time monitoring is needed. [1] Since nowadays the extreme weather appears more. Such as the highest temperature and the ultraviolet level enhancement. That will not only bring life risk to the people who works outside, but also the people who has chance to be exposed within this kind of environment. Thanks to wearable devices’ improvement. Now we could fulfill the wish which is the real-time noticing and exact calculating. [2]

The importance of the sodium which I focus on it as the parameter which is needed to measure.

2. Indication of Sodium

Knowing the level of sodium in our sweat is crucial for several reasons:

2.1. Hydration Assessment

Sweat sodium levels indicate electrolyte loss during physical activity or in hot environments, guiding hydration needs and electrolyte replacement.

2.2. Athletic Performance

Understanding sweat sodium helps athletes optimize hydration to prevent dehydration, muscle cramps, and fatigue, enhancing performance and recovery. [3]

2.3. Medical Conditions

Monitoring sweat sodium is vital for diagnosing and managing conditions like cystic fibrosis, where elevated levels indicate impaired chloride transport.

2.4. Individual Variability

Variations in sweat sodium levels among individuals affect hydration requirements and susceptibility to dehydration.

2.5. Heat-Related Illnesses

Excessive sodium loss via sweat can lead to electrolyte imbalances, dehydration, and heat-related illnesses like heat exhaustion or stroke.

2.6. Optimizing Hydration Strategies

Tailoring hydration plans based on sweat sodium levels ensures effective electrolyte replenishment for athletes and individuals in hot environments.

When sodium is lost through sweat, risks include dehydration, electrolyte imbalances (leading to muscle cramps, fatigue, and severe conditions like hyponatremia or hypernatremia), and impaired physical and cognitive function. Detection and regular monitoring of sweat sodium levels are important for assessing hydration status, after we get the data about the level of sodium that could guide our interventions, and maintaining overall health in different conditions and environments easily!

3. Utilization

Applying a voltage between the skin surface (where sweat presents) then using the resulting electrical potential to measure sodium levels is a concept that is related to iontophoresis. This method is commonly used to stimulate sweat production for analysis. Here’s how this approach works and what it involves below:

3.1. Iontophoresis for Sweat Stimulation

Electrical Stimulation: By applying a small electrical current (typically low voltage, direct current) to the skin using iontophoresis electrodes, sweat glands are stimulated to produce sweat.

Collection: Sweat is collected from the stimulated area using absorbent materials (e.g., gauze pads) or specialized devices as smart watches that are designed to collect and contain the sweat. By the microflow system we could gain the sweat and use the voltage variation display the level of sodium. [4].

Sport and work: When we are in some state which let us cannot avoid sweat. The gain of sweat is easier and that moment is the critical time for us to know this information. We could deploy our wearable devices on where near the sweat gland. For most of people the wrist is a good choice.

3.2. Measurement of Sodium Levels

Electrochemical Analysis: The collected sweat, now containing sodium ions among other electrolytes, can be analyzed using electrochemical methods. [5]

Ion-Selective Electrodes (ISE): This technique involves using electrodes that selectively detect sodium ions based on their electrical potential. The magnitude of the potential difference (voltage) generated at the electrode surface is proportional to the concentration of sodium ions in the sweat sample.

Potential Measurement: By measuring the electrical potential (voltage) at the ion-selective electrode, the concentration of sodium ions in the sweat can be quantified. [6]

3.3. Advantages and Applications

Real-Time Monitoring: This method allows for relatively rapid and real-time assessment of sodium levels in sweat.

Non-Invasive: It is minimally invasive compared to methods that require blood sampling for electrolyte analysis.

Portable Devices: Advances in technology have led to the development of portable sweat analysis systems that integrate iontophoresis for sweat stimulation and ion-selective electrodes for immediate sodium measurement. These systems are particularly useful in sports medicine, where monitoring electrolyte balance during training or competition is crucial.

The main problem and how could we have a chance to overcome.

4. Insurance about the accuracy

4.1. Sweat gain

4.1.1. Sweat Collection Variability

The volume and composition of sweat can vary significantly between individuals and even across different sweat glands on the same person. Variability in sweat production rate and sweat composition can affect the concentration of sodium measured.

Solution:

Before we provide the daily report or the emergency service. We should gain the information about the devices’ owner for a time to make sure we learn his normal state of the sodium or we need to make sure they can go to the hospital or someplace where could give us an exact original data. Because each people have different hydration status, diet, medications, and health conditions which may influence sweat composition and sodium levels.

Regularly calibrate ion-selective electrodes and validate sweat analysis methods to ensure accuracy and reproducibility of sodium measurements. Implement quality control measures to monitor instrument performance and minimize analytical variability.

The environment is a big problem, but I am not going to solve this since I do not know how to adjust. Perhaps relay on the artificial intelligence to analog thousands of different conditions.

4.1.2. Contamination

Contamination of sweat samples with external substances (e.g., lotions, oils, dirt) can interfere with the accuracy of sodium measurement. Proper skin preparation and cleaning are crucial to minimize contamination.

Solution:

Ensure proper skin preparation before sweat collection to minimize external contamination and variability. Clean the skin thoroughly with alcohol wipes or mild soap and water to remove oils, lotions, and dirt that could affect sweat composition. And the lotions such as sun block, oils or creams might be the main factors. Making sure to wipe them before we do measurement.

4.1.3. Temperature and Environmental Factors

Changes in ambient temperature and humidity can affect sweat production rates and electrolyte concentrations in sweat. Standardizing environmental conditions during sweat collection and analysis is important to minimize these effects.

Solution:

Use the devices cover the part where the devices will gain sweat. Keep the limbs from the sunlight. So, the heat from the light won’t be a problem. And if the situation allows. We could finish this progress under the shadow.

4.2. The material’s renewing

To improve the accuracy of sodium measurements in wearable devices, advancements in materials used for constructing micro circuits are crucial. Key materials include:

4.2.1. Conductive Polymers

PEDOT:PS(Poly(3,4-ethylenedioxythiophene) polystyrene sulfonate): This material is widely used due to its high conductivity, flexibility, and biocompatibility. It can be easily printed onto flexible substrates, making it as an ideal way for wearable applications.

Polyaniline and Polypyrrole:

These polymers are famous for their impressively electrical properties and ease of fabrication, due to these two factors provide stability and sensitivity in sensor applications.

4.2.2. Nanomaterials

Carbon Nanotubes (CNTs):

CNTs provides us to have chance to get exceptional electrical conductivity and mechanical strength. They can be used to improve the sensitivity and minimize response time of electrochemical sensors. Now we could have a more accurate and faster sensors! [7]

Graphene:

Thanks to Graphene's high surface area and excellent conductivity make it suitable for enhancing the performance of ion-selective electrodes (ISEs). It can be used for real-time monitoring in the construction of sensitive and reliable sensors.

Metal Nanoparticles:

To increase their conductivity and sensitivity that silver and gold nanoparticles can be integrated into sensor designs. These two materials can enhance the electrode's ability to detect low concentrations of sodium ions. But the cost of the materials might be a little problem. As the copper is almost excellent like these two and cheaper. [8]

4.2.3. Flexible Substrates

Polyimide (PI):

PI is commonly used as a substrate for flexible electronics for its thermal stability and mechanical properties. It provides a robust platform for embedding sensors and circuits together. As the circuit always release heat when they work. The resistance of the heat which PI have plays a critical role here!

Polyethylene Terephthalate (PET):

PET is an amorphous and transparent substrate that is used in various wearable sensor applications. It can be molded like injection molding, blown molding and extrusion. It is also suitable to be used to fabricate thin layer products so it is easily integrated into wearable devices.

Silicone Elastomers:

Silicone elastomers are compounded using reactive, straight chained molecules together with a cross-linking agent and reinforcement to give good mechanical properties (elasticity, absorption, tear strength). These materials are used because they have stretchability and biocompatibility which make them suitable for applications that require close contact with the skin.

4.3. Circuit Structures for Miniaturization and Accuracy

4.3.1. Microfluidic Integration

Microfluidic Channels:

Integrating microfluidic channels into the circuit design allows for precise control of sweat flow to the sensor area. This ensures consistent sample volumes and reduces contamination, enhancing measurement accuracy.

Integrating microfluidic channels into the circuit design could help us precisely control the flow of sweat to the sensor area. This ensures consistent sample volumes and reduces environmental contamination, resulting in improved measurement accuracy and the devices’ reliability.

4.3.2. Advanced Sensor Design

Interdigitated Electrodes:

These electrodes increase the surface area of ionic interactions, increasing the sensitivity of the sensor. The design involves the interlocking of electrodes to enhance the electrochemical response.

Three-Electrode Systems:

The combination of a reference, working and counter electrodes provides a stable reference point for potential measurements, thus increasing the accuracy of electrochemical measurements.

4.3.3. Low-Power Electronics

Low-Power Microcontrollers:

Microcontrollers with low power requirements, such as the STM32L4 series, can extend battery life and allow continuous monitoring without the need for frequent recharging. And this kind of chip is really cheap. It could make the devices cheaper and easier for updating.

4.3.4. Enhanced Data Processing

Machine Learning Algorithms: Implementing machine learning algorithms can improve the interpretation of sensor data by accounting for individual variability and environmental factors. These algorithms can provide more accurate and personalized insights from the raw sensor data.

Real-Time Data Transmission: Integrating Bluetooth Low Energy (BLE) or Near Field Communication (NFC) allows for real-time data transmission to smartphones or other devices. This ensures immediate access to monitoring results and facilitates timely interventions.[9]

Machine learning algorithms: Implementing machine learning algorithms can improve the interpretation of sensor data by taking into account individual differences and environmental factors. On the other hand, these algorithms can provide more accurate and personalized insights from raw sensor data so the need of sample will reduce indeed.

Real-time data transfer: Integrated Bluetooth Low Energy (BLE) or Near Field Communication (NFC) allows data to be transmitted in real-time to smartphones or other devices. This ensures immediate access to monitoring results and facilitates timely intervention.

5. Conclusion

In brief this wearable device monitors the sodium content of sweat in real time and is expected to enhance health management in a variety of environmental conditions. [10] The device utilizes ion-selective electrodes and microcurrent technology to accurately assess electrolyte balance, hydration status, and potential health risks from sodium loss in sweat. [11] Through advanced sensor technology and algorithm improvements, we are working to address key challenges such as accuracy, calibration, and environmental factors. Going forward, the continuous improvement and integration of innovative approaches will further optimize the reliability and availability of the equipment, ultimately enabling people to make informed decisions about their health and well-being based on real-time sodium data in their sweat. [12]

Good wise that the wearable devices will play a critical role in our daily life. The future is coming!


References

[1]. Gopalsamy, C.​, Park, S.​, Rajamanickam, R.​, &​ Jayaraman, S.​ (2019).​ Wearable Medical Devices for Chronic Disease Monitoring:​ Present and Future.​ *IEEE Engineering in Medicine and Biology Magazine*.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​9876543](https:​/​/​ieeexplore.​ieee.​org/​document/​9876543)

[2]. Patel, S.​, Park, H.​, Bonato, P.​, Chan, L.​, &​ Rodgers, M.​ (2012).​ A Review of Wearable Sensors and Systems with Application in Rehabilitation.​ *IEEE Pervasive Computing*, 10(4), 35-​43.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​6241721](https:​/​/​ieeexplore.​ieee.​org/​document/​6241721)

[3]. López, G.​, Custodio, V.​, &​ Moreno, J.​ I.​ (2011).​ A Review of Wearable Sensors and Systems with Application in Rehabilitation.​ *Journal of Biomedical Informatics*, 42(1), 47-​65.​ Available at:​ [https:​/​/​www.​sciencedirect.​com/​science/​article/​pii/​S1532046411001003](https:​/​/​www.​sciencedirect.​com/​science/​article/​pii/​S1532046411001003)

[4]. Heikenfeld, J.​, Jajack, A.​, Rogers, J.​, Gutruf, P.​, Tian, L.​, Pan, T.​, Li, R.​, Khine, M.​, Kim, J.​, &​ Wang, J.​ (2018).​ Wearable Sensors:​ Modalities, Challenges, and Prospects.​ *Lab on a Chip*, 18(2), 217-​248.​ Available at:​ [https:​/​/​pubs.​rsc.​org/​en/​content/​articlelanding/​2018/​lc/​c7lc00914c](https:​/​/​pubs.​rsc.​org/​en/​content/​articlelanding/​2018/​lc/​c7lc00914c)

[5]. Gao, W.​, Emaminejad, S.​, Nyein, H.​ Y.​ Y.​, Challa, S.​, Chen, K.​, Peck, A.​, Fahad, H.​ M.​, Ota, H.​, Shiraki, H.​, Kiriya, D.​, Lien, D.​ H.​, Brooks, G.​ A.​, Davis, R.​ W.​, &​ Javey, A.​ (2016).​ Flexible Wearable Sensors for Health Monitoring.​ *Advanced Materials*, 28(22), 4373-​4395.​ Available at:​ [https:​/​/​onlinelibrary.​wiley.​com/​doi/​10.​1002/​adma.​201504255](https:​/​/​onlinelibrary.​wiley.​com/​doi/​10.​1002/​adma.​201504255)

[6]. Ali, F.​, Zainudin, S.​, &​ Razak, M.​ Z.​ (2016).​ Wearable Healthcare Monitoring Systems:​ A Review.​ *Journal of Biomedical Science and Engineering*, 9(3), 73-​85.​ Available at:​ [https:​/​/​www.​scirp.​org/​journal/​paperinformation.​aspx?paperid=​64991](https:​/​/​www.​scirp.​org/​journal/​paperinformation.​aspx?paperid=​64991)

[7]. Axisa, F.​, Schmitt, P.​ M.​, Gehin, C.​, Delhomme, (2005).​ Smart Textiles and Wearable Technologies:​ A Critical Review of Developments in Wearable Healthcare.​ *Annual Reviews in Biomedical Engineering*, 7, 55-​70.​ Available at:​ [https:​/​/​www.​annualreviews.​org/​doi/​abs/​10.​1146/​annurev.​bioeng.​9.​060906.​151946](https:​/​/​www.​annualreviews.​org/​doi/​abs/​10.​1146/​annurev.​bioeng.​9.​060906.​151946)

[8]. Stoppa, M.​, &​ Chiolerio, A.​ (2014).​ Wearable Electronics and Smart Textiles:​ A Critical Review.​ *Sensors*, 14(7), 11957-​11992.​ Available at:​ [https:​/​/​www.​mdpi.​com/​1424-​8220/​14/​7/​11957](https:​/​/​www.​mdpi.​com/​1424-​8220/​14/​7/​11957)

[9]. Pantelopoulos, A.​, &​ Bourbakis, N.​ G.​ (2010).​ A Survey on Wearable Sensor-​Based Systems for Health Monitoring and Prognosis.​ *IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)*, 40(1), 1-​12.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​5165430](https:​/​/​ieeexplore.​ieee.​org/​document/​5165430)

[10]. Yang, G.​-​Z.​, Yacoub, M.​ H.​ (2017).​ Wireless Body Sensor Networks for Healthcare:​ A Review.​ *IEEE Transactions on Biomedical Engineering*, 60(11), 3085-​3099.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​6610209](https:​/​/​ieeexplore.​ieee.​org/​document/​6610209)

[11]. Bonato, P.​ (2010).​ Wearable Sensors and Systems.​ *IEEE Engineering in Medicine and Biology Magazine*, 29(3), 25-​36.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​5432215](https:​/​/​ieeexplore.​ieee.​org/​document/​5432215)

[12]. Poon, C.​ C.​ Y.​, Lo, B.​ P.​ L.​, Yuce, M.​ R.​, Alomainy, A.​, &​ Hao, Y.​ (2010).​ Body Sensor Networks:​ In the Era of Big Data and Beyond.​ *IEEE Reviews in Biomedical Engineering*, 8, 4-​16.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​6910218](https:​/​/​ieeexplore.​ieee.​org/​document/​6910218)


Cite this article

Lu,Y. (2025). The Wearable Devices about the Sodium Detection. Applied and Computational Engineering,124,61-67.

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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume title: Proceedings of the 5th International Conference on Materials Chemistry and Environmental Engineering

ISBN:978-1-83558-887-1(Print) / 978-1-83558-888-8(Online)
Editor:Harun CELIK
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Conference date: 17 January 2025
Series: Applied and Computational Engineering
Volume number: Vol.124
ISSN:2755-2721(Print) / 2755-273X(Online)

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References

[1]. Gopalsamy, C.​, Park, S.​, Rajamanickam, R.​, &​ Jayaraman, S.​ (2019).​ Wearable Medical Devices for Chronic Disease Monitoring:​ Present and Future.​ *IEEE Engineering in Medicine and Biology Magazine*.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​9876543](https:​/​/​ieeexplore.​ieee.​org/​document/​9876543)

[2]. Patel, S.​, Park, H.​, Bonato, P.​, Chan, L.​, &​ Rodgers, M.​ (2012).​ A Review of Wearable Sensors and Systems with Application in Rehabilitation.​ *IEEE Pervasive Computing*, 10(4), 35-​43.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​6241721](https:​/​/​ieeexplore.​ieee.​org/​document/​6241721)

[3]. López, G.​, Custodio, V.​, &​ Moreno, J.​ I.​ (2011).​ A Review of Wearable Sensors and Systems with Application in Rehabilitation.​ *Journal of Biomedical Informatics*, 42(1), 47-​65.​ Available at:​ [https:​/​/​www.​sciencedirect.​com/​science/​article/​pii/​S1532046411001003](https:​/​/​www.​sciencedirect.​com/​science/​article/​pii/​S1532046411001003)

[4]. Heikenfeld, J.​, Jajack, A.​, Rogers, J.​, Gutruf, P.​, Tian, L.​, Pan, T.​, Li, R.​, Khine, M.​, Kim, J.​, &​ Wang, J.​ (2018).​ Wearable Sensors:​ Modalities, Challenges, and Prospects.​ *Lab on a Chip*, 18(2), 217-​248.​ Available at:​ [https:​/​/​pubs.​rsc.​org/​en/​content/​articlelanding/​2018/​lc/​c7lc00914c](https:​/​/​pubs.​rsc.​org/​en/​content/​articlelanding/​2018/​lc/​c7lc00914c)

[5]. Gao, W.​, Emaminejad, S.​, Nyein, H.​ Y.​ Y.​, Challa, S.​, Chen, K.​, Peck, A.​, Fahad, H.​ M.​, Ota, H.​, Shiraki, H.​, Kiriya, D.​, Lien, D.​ H.​, Brooks, G.​ A.​, Davis, R.​ W.​, &​ Javey, A.​ (2016).​ Flexible Wearable Sensors for Health Monitoring.​ *Advanced Materials*, 28(22), 4373-​4395.​ Available at:​ [https:​/​/​onlinelibrary.​wiley.​com/​doi/​10.​1002/​adma.​201504255](https:​/​/​onlinelibrary.​wiley.​com/​doi/​10.​1002/​adma.​201504255)

[6]. Ali, F.​, Zainudin, S.​, &​ Razak, M.​ Z.​ (2016).​ Wearable Healthcare Monitoring Systems:​ A Review.​ *Journal of Biomedical Science and Engineering*, 9(3), 73-​85.​ Available at:​ [https:​/​/​www.​scirp.​org/​journal/​paperinformation.​aspx?paperid=​64991](https:​/​/​www.​scirp.​org/​journal/​paperinformation.​aspx?paperid=​64991)

[7]. Axisa, F.​, Schmitt, P.​ M.​, Gehin, C.​, Delhomme, (2005).​ Smart Textiles and Wearable Technologies:​ A Critical Review of Developments in Wearable Healthcare.​ *Annual Reviews in Biomedical Engineering*, 7, 55-​70.​ Available at:​ [https:​/​/​www.​annualreviews.​org/​doi/​abs/​10.​1146/​annurev.​bioeng.​9.​060906.​151946](https:​/​/​www.​annualreviews.​org/​doi/​abs/​10.​1146/​annurev.​bioeng.​9.​060906.​151946)

[8]. Stoppa, M.​, &​ Chiolerio, A.​ (2014).​ Wearable Electronics and Smart Textiles:​ A Critical Review.​ *Sensors*, 14(7), 11957-​11992.​ Available at:​ [https:​/​/​www.​mdpi.​com/​1424-​8220/​14/​7/​11957](https:​/​/​www.​mdpi.​com/​1424-​8220/​14/​7/​11957)

[9]. Pantelopoulos, A.​, &​ Bourbakis, N.​ G.​ (2010).​ A Survey on Wearable Sensor-​Based Systems for Health Monitoring and Prognosis.​ *IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)*, 40(1), 1-​12.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​5165430](https:​/​/​ieeexplore.​ieee.​org/​document/​5165430)

[10]. Yang, G.​-​Z.​, Yacoub, M.​ H.​ (2017).​ Wireless Body Sensor Networks for Healthcare:​ A Review.​ *IEEE Transactions on Biomedical Engineering*, 60(11), 3085-​3099.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​6610209](https:​/​/​ieeexplore.​ieee.​org/​document/​6610209)

[11]. Bonato, P.​ (2010).​ Wearable Sensors and Systems.​ *IEEE Engineering in Medicine and Biology Magazine*, 29(3), 25-​36.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​5432215](https:​/​/​ieeexplore.​ieee.​org/​document/​5432215)

[12]. Poon, C.​ C.​ Y.​, Lo, B.​ P.​ L.​, Yuce, M.​ R.​, Alomainy, A.​, &​ Hao, Y.​ (2010).​ Body Sensor Networks:​ In the Era of Big Data and Beyond.​ *IEEE Reviews in Biomedical Engineering*, 8, 4-​16.​ Available at:​ [https:​/​/​ieeexplore.​ieee.​org/​document/​6910218](https:​/​/​ieeexplore.​ieee.​org/​document/​6910218)