Bioelectronics and Medical Devices

From Materials to Devices - Fabrication, Applications and Reliability

Kunal Pal,Heinz-Bernhard Kraatz,Anwesha Khasnobish,Sandip Bag,Indranil Banerjee,Usha Kuruganti

• Verlag: Woodhead Publishing
• Jahr: 2019
• ISBN:
  9780081024218
• Thema: Technology & Engineering
• Thema: Materials Science

Bioelectronics and Medical Devices: From Materials to Devices-Fabrication, Applications and Reliability reviews the latest research on electronic devices used in the healthcare sector, from materials, to applications, including biosensors, rehabilitation devices, drug delivery devices, and devices based on wireless technology. This information is presented from the unique interdisciplinary perspective of the editors and contributors, all with materials science, biomedical engineering, physics, and chemistry backgrounds. Each applicable chapter includes a discussion of these devices, from materials and fabrication, to reliability and technology applications. Case studies, future research directions and recommendations for additional readings are also included.

The book addresses hot topics, such as the latest, state-of the-art biosensing devices that have the ability for early detection of life-threatening diseases, such as tuberculosis, HIV and cancer. It covers rehabilitation devices and advancements, such as the devices that could be utilized by advanced-stage ALS patients to improve their interactions with the environment. In addition, electronic controlled delivery systems are reviewed, including those that are based on artificial intelligences.

• Presents the latest topics, including MEMS-based fabrication of biomedical sensors, Internet of Things, certification of medical and drug delivery devices, and electrical safety considerations
• Presents the interdisciplinary perspective of materials scientists, biomedical engineers, physicists and chemists on biomedical electronic devices
• Features systematic coverage in each chapter, including recent advancements in the field, case studies, future research directions, and recommendations for additional readings

1

Light-fidelity based biosignal transmission

Pratyush K. Patnaik¹, Suraj K. Nayak¹, Ashirbad Pradhan¹, Amrutha V¹, Champak Bhattacharya², Sirsendu S. Ray¹ and Kunal Pal¹, ¹Department of Biotechnology and Medical engineering, National Institute of Technology, Rourkela, India, ²Health Center, National Institute of Technology, Rourkela, India

Abstract

The flickering of the light in the light emitting diode at a very high frequency is not perceived by the human eye. The phenomenon can be exploited for wirelessly transmitting data. In this regard, light-fidelity (Li-Fi) based wireless transmission has been proposed. The Li-Fi-based systems can transmit data at a rate of, as high as, 500 Mbits/s. Though it has shown a great potential in transmitting data packets in communication systems, it has not been explored to a great extent for transmitting biomedical signals in hospital environments. The Li-Fi-based wireless communication systems can offer several advantages over the conventional radio frequency (RF) wave-based communication systems. In this chapter, we discuss details about the Li-Fi-based communication systems over the RF-based communication systems with regards to human health. Further, we discuss the designing aspects of a simple Li-Fi-based electrocardiogram signal transmitter.

Keywords

Li-Fi communication system; RF communication system; biomedical signals; electrocardiogram; human health

Introduction

The use of electronic devices in current-day life has become indispensable. This is also true for the healthcare sector (Boyce, 2011; Free et al., 2010; Koivunen, Niemi, & Hupli, 2015). The use of electronic devices in the hospitals and diagnostic centers is rising (Raatikainen et al., 2015). This has helped in significantly reducing the workload on healthcare givers. This is important because of the low healthcare giver to patient ratio across the globe (Callaghan, Ford, & Schneider, 2010; Matthias & Benjamin, 2005). Electronic health-monitoring devices allow monitoring of the patient health conditions (Chiauzzi, Rodarte, & DasMahapatra, 2015; Such et al., 2007). Unfortunately, most of the devices, which help in the monitoring of the vital signs, are wired devices. Hence, the physiological signals have to be transferred to the monitoring station via wires, which are usually laid across the hospital. In this regard, many researchers and medical equipment companies have proposed transmission of biomedical signals via wireless technologies (Fan, Zhang, Liao, & Ren, 2018; Honda, Harada, Arie, Akita, & Takei, 2014; Varshney, 2007). This has been made possible due to the extensive advancements made in the field of both telecommunication and healthcare technologies. This type of biomedical signal transmission is categorized as telemedicine (Costello et al., 2017; Flodgren, Rachas, Farmer, Inzitari, & Shepperd, 2015).

There has been extensive research in the field of telemedicine in the last two decades (Kvedar, Coye, & Everett, 2014). Telemedicine focuses on the application of the electronic communication technologies in transferring the medical data of patients from one location to another location for improving their clinical health status (De La Torre-Díez, López-Coronado, Vaca, Aguado, & de Castro, 2015), and it has become an essential component in the healthcare delivery system (Wilson & Maeder, 2015). This has helped in the delivery of healthcare services in remote locations, thereby aiding to the vision of the World Health Organization (WHO) to provide adequate and equal access to healthcare services to every person across the globe (AlDossary, Martin-Khan, Bradford, & Smith, 2017).

Unfortunately, many of the current telemedicine technologies use electromagnetic (EM) radiation induced from Wi-Fi and mobiles for the transmission of the biomedical signals (Azizi et al., 2016; Nikolayev, Zhadobov, Karban, & Sauleau, 2018). EM radiations induced from Wi-Fi and mobiles have been reported to cause adverse physiological effect. In this regard, a recent study by Nazıroğlu and Akman (2014) has reported that such EM radiations can increase the oxidative stress in the brain with corresponding decrease in the natural antioxidants present in the brain. This neurophysiological alteration is detrimental to human health (Nazıroğlu & Akman, 2014). The same group further reported that these EM radiations also increase oxidative stress in the human reproductive system. Additionally, a change in the reproductive signaling pathway was also reported (Nazıroğlu, Yüksel, Köse, & Özkaya, 2013). Further, Avendano, Mata, Sarmiento, and Doncel (2012) reported that EM radiations from Wi-Fi can significantly reduce human sperm motility. The authors also reported that the EM radiations (from Wi-Fi) induce DNA fragmentation by a nonthermal effect (Avendano et al., 2012). A combination of the aforementioned reasons can reduce male fertility to a great extent (Avendano et al., 2012). Similarly, the detrimental effect of EM radiation exposure on the other vital organs (e.g., kidney and heart) has also been reported by various authors (Özorak et al., 2013). Hence, many researchers have proposed the need to find an alternative way of transmitting medical data without creating any health hazard.

In this regard, light fidelity (Li-Fi) protocol can be explored for telemedicine applications. The term Li-Fi was first coined by Harald Haas in 2011 (Haas, 2013). The purpose of the use of light is to use the vast amount of unused EM spectrum in the visible light region for wireless communication (Haas, Yin, Wang, & Chen, 2016). The Li-Fi protocol is a type of visible light communication (VLC), which uses a light emitting diode (LED) and a photodetector (e.g., P–I–N photodiode and Avalanche photodiode) for the transmission of the signals (Haas, 2013). As LED-based home lighting systems are now commonly used, Dr. Haas has proposed that the Li-Fi system can not only be used for illuminating the enclosed areas (rooms) but also can be used for data communication purposes (Haas, 2013). In a recent study, Dhatchayeny, Sewaiwar, Tiwari, and Chung (2015) demonstrated the transmission of the electroencephalogram (EEG) signals using Li-Fi technology. Taking an inspiration from the earlier detailed study, in this study, we propose to develop a low-cost electrocardiogram (ECG) signal wireless transmission system using Li-Fi technology. Initially, the testing of the developed device was done using the ECG simulator. Thereafter, the ECG signal from healthy human volunteers was transmitted using the developed device.

Literature review

VLC has been used for a long time (Arnon, 2015). Before the advent of the radio technology, Morse code using visible light was employed for communication (Yang, 2000). Pang, Kwan, Chan, and Liu (1999) reported the use of visible light for electronic data transmission. The current fed to the LEDs was used to modulate an audio signal and transmitted via light. An oscillator was used to modulate the audio signal. The optical receiver demodulated the signal and extracted the original audio signal to be played. The term Li-Fi was not yet coined. Komine and Nakagawa (2004) first used the idea of LED for the purpose of VLC (Komine & Nakagawa, 2004). An in-depth analysis of optical channel of sender and receiver was performed. One of the biggest sources of noise was reflection from the walls and the intersymbol interference. This suggested that the VLC using LED can reach the potential of 10 Gbps. Le Minh et al. (2008) suggested the use of 16 LEDs for designing a VLC system, which worked at the speed of 40 Mbps. The device consisted of 16 LEDs, each attached with a diffusing lens. The LEDs were modulated using high-speed buffers and were also provided with a current bias. The 16 LED panel was used to test the VLC line-of-sight link over the distance of 2 m. The LED was chosen because it provided the illumination required for typical office conditions (Le Minh et al., 2008).

In a study by O’Brien et al. (2008), VLC was used to achieve a data rate of 100 Mbps. Various techniques were used to increase the data rate, bandwidth, and signal noise ratio (SNR). The transmission mechanism involved combining the blue LED with a coating of phosphor, resulting in the emission of yellow light. The blue light mixed with yellow light resulted in a single-source white light. Transmitter and receiver equalization was used to achieve higher bandwidth and SNR. Optical filtering of the slow-emitting phosphor light also helped in improving the bandwidth. Multiple-input multiple-output was used, involving an array of LEDs, thus enhancing the data rate. Data rate higher than 100 Mbps, bandwidth of as high as 90 MHz, and SNR of 40 dB could be achieved with the modified techniques (O’Brien et al., 2008). Similar observations have been encountered by Le Minh et al. (2009), who have tried to model the functioning of the intensity of the white LED. Using the model, the speed of signal transmission was improved. Based on the results, the authors suggested that the white LED consists of a blue component of the LED and the overall yellow component of the phosphor. After analyzing the LED, they found that the yellow light responded until 2.5 MHz, whereas the blue light responded until 14 MHz. To increase the speed of data transmission, a blue filter was used to get a faster switching response from the ...

Inhaltsverzeichnis

• Cover image
• Title page
• Table of Contents
• Copyright
• List of contributors
• 1. Light-fidelity based biosignal transmission
• 2. Development of a low-cost color sensor for biomedical applications
• 3. Development of a voice-controlled home automation system for the differently-abled
• 4. Lab-on-a-chip sensing devices for biomedical applications
• 5. Impedance-based biosensors
• 6. Acoustophoresis-based biomedical device applications
• 7. Electroencephalography and near-infrared spectroscopy-based hybrid biomarker for brain imaging
• 8. Micro-electro-mechanical system–based drug delivery devices
• 9. Enzyme-based biosensors
• 10. Ultrasound-based drug delivery systems
• 11. Electroencephalogram-controlled assistive devices
• 12. Electromyogram-controlled assistive devices
• 13. Electrical safety
• 14. Biomedical metrology
• 15. Bone-implantable devices for drug delivery applications
• 16. Iontophoretic drug delivery systems
• 17. Microneedle platform for biomedical applications
• 18. Trends in point-of-care microscopy
• 19. Development of spectroscopy-based medical devices for disease diagnosis in low resource point-of-care setting
• 20. Dielectrophoresis-based devices for cell patterning
• 21. Multichannel surface electromyography
• 22. Sensors for monitoring workplace health
• 23. Advances in enzyme-based electrochemical sensors: current trends, benefits, and constraints
• 24. Electrocardiogram signal processing-based diagnostics: applications of wavelet transform
• 25. Sensor fusion and control techniques for biorehabilitation
• 26. Biofunctional interfaces for cell culture in microfluidic devices
• 27. Microsystems technology for high-throughput single-cell sorting
• 28. Microfluidic devices for DNA amplification
• 29. Optimizing glucose sensing for diabetes monitoring
• 30. Brain–computer interface–functional electrical stimulation: from control to neurofeedback in rehabilitation
• 31. Motor imagery classification enhancement with concurrent implementation of spatial filtration and modified stockwell transform
• 32. A hybrid wireless electroencephalography network based on the IEEE 802.11 and IEEE 802.15.4 standards
• 33. Deep learning in medical and surgical instruments
• 34. Electroencephalogram-based brain–computer interface systems for controlling rehabilitative devices
• 35. A system for automatic cardiac arrhythmia recognition using electrocardiogram signal
• 36. Designing of a biopotential amplifier for the acquisition and processing of subvocal electromyography signals
• Index