Communication and Signal Transmission for In-body Cardiac Sensor Networks

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Communication and Signal Transmission for In-body Cardiac Sensor Networks

Pritam Bose

Doctoral Dissertation

Submitted to The Faculty of Medicine

at the University of Oslo for the degree of Philosophiae Doctor (PhD)

August, 2019

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© Pritam Bose, 2019

Series of dissertations submitted to the Faculty of Medicine, University of Oslo

ISBN 978-82-8377-521-1

reproduced or transmitted, in any form or by any means, without permission.

Cover: Hanne Baadsgaard Utigard.

Print production: Reprosentralen, University of Oslo.

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To Maa, Baba, Bhai and Rima

For their unconditional love and support

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Preface

This thesis has been submitted to the Faculty of Medicine at the University of Oslo (UiO) in partial fulfilment of the requirements for the degree of Philosophiae Doctor (Ph.D.).

The work was carried out at the Interventional Centre (IVS), Oslo University Hospital in Norway under the supervision of Prof. Ilangko Balasingham, Dr. Ali Khaleghi, Dr. Jacob Bergsland, Prof. Erik Fosse and Prof. Kimmo Kansanen.

Besides the research activities, the Ph.D. work also included compulsory course studies conducted at the University of Oslo and Norwegian University of Science and Technology (NTNU).

The research was funded by the European Union’s H2020: MSCA: ITN program for the “Wireless In-body Environment Communication—WiBEC” project under Grant 675353.

The structure of this thesis is in the form of a collection of papers published in peer- reviewed journals (one publication under review) and preceded by an overview.

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Acknowledgements

While I sit to write this section, I am not only lost for words, but also, there is not enough words in any literature to acknowledge and convey my utmost gratitude to all the people involved directly and indirectly behind this thesis. Moreover, it is an impossible task to list all of them. I will try to name a few of you below. But those, I have not mentioned, there is no reason to believe that you are forgotten. All of you are close to my heart and will always be.

First, I want to thank all the readers of this thesis. It is because of you I have been motivated even on a gloomy Norwegian winter day to push the boundaries of my knowledge a bit further to be able to complete my PhD studies and write this thesis.

I want to acknowledge my PhD supervisors- Prof. Ilangko Balasingham, Dr. Jacob Bergsland and Dr. Ali Khaleghi. Ilangko’s dedication, Jacob’s curiosity and Ali’s passion for his work have always motivated me. I can list down 101 more reasons to thank them, but I would rather refrain from doing that. I would just say that they have been my local guardians in Norway.

My colleagues at office – Pengfei, Mohammad, Mladen, Noha, Andrea, Davide, Hemin, Yulia, Egis, Ali and the list goes on and on – I want to thank you all. In the last three years, I have spent more time with you guys than even my wife. So, what better reason does someone need to be grateful. I am in debt for providing me life- long memories and making my PhD journey a wonderful experience.

I wish to thank everyone in the Intervention centre – Erik, Marianne, Ole-Jacob, Rahul, Steiner, Rafael, Karl and here also the list goes on and on. This is a wonderful centre and you guys are doing an excellent job to make it better every day. I also owe my thanks to all the clinicians, nurses and staff in the centre who have actively assisted us in conducting the experiments and helped us in every possible way.

I owe my sincere gratitude to the Oslo University Hospital for providing me the opportunity and space to conduct my research and to the University of Oslo for accepting me as a PhD student. I owe my greatest acknowledgment to European Commission for providing us the funding to conduct the research.

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This project has given me a new family “The WiBEC family”. I have been very lucky to meet you guys. The quality time we have spent together in so many places and the experiences we have gathered together both academically and socially have made me a better and knowledgeable person. I want to thank you all from the bottom of my heart.

Then, comes my friends in Oslo and in India. The illogical discussions, the Friday parties, mega trips, my worst singing, guitar strumming, hours of card games, the football matches, hourlong WhatsApp calls- I thank you for all of these. Don’t be mistaken, these are the stressbusters that have helped me to finish my PhD.

Last but not the least, I want to thank my family. My father, my brother, my beautiful mom and my gorgeous wife- You are the real heroes of my life.

ধন্যবাদ (Thank you All), Pritam Bose

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List of Papers

Paper I

P. Bose, A. Khaleghi, M. Albatat, J. Bergsland & I. Balasingham, “RF Channel Modeling for Implant-to-Implant Communication and Implant to Subcutaneous Implant Communication for Future Leadless Cardiac Pacemakers.” IEEE Transactions on Biomedical Engineering, vol. 65, no. 12, pp. 2798–2807, Dec.

2018, doi:10.1109/tbme.2018.2817690.

Paper II

P. Bose, A. Khaleghi & I. Balasingham, “Wireless Channel Modeling for Leadless Cardiac Pacemaker: Effects of Ventricular Blood Volume.” 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3746-3749, Jul. 2018, doi:10.1109/embc.2018.8513099.

Paper III

P. Bose, A. Khaleghi & I. Balasingham, “In-Body and Off-Body Channel Modeling for Future Leadless Cardiac Pacemakers Based on Phantom and Animal Experiments.” IEEE Antennas and Wireless Propagation Letters, vol. 17, no. 12, pp. 2484–2488, Dec. 2018, doi:10.1109/lawp.2018.2878950.

Paper IV

P. Bose, A. Khaleghi, S. Mahmood, M. Albatat, J. Bergsland & I. Balasingham,

“Evaluation of Data Telemetry for Multi-node Leadless Cardiac Pacemaker.“

IEEE Access, June 2019 (under review).

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List of Figures

Fig. 1 Schematic of a WBAN .……….18

Fig. 2 Schematic of a bi-ventricular pacemaker ..………36

Fig 3. Schematic of a leadless pacemaker capsule ………...37

Fig. 4 Schematic of a three-node leadless capsule pacemaker .………38

Fig. 5 Muscle block model .……….42

Fig. 6 Donna model ...………43

Fig. 7 HUGO model .……….45

Fig. 8 Ventricular blood volume change in HUGO model ..……….46

Fig. 9 Transmitter capsule architecture and components .………47

Fig. 10 Transmitter antenna ……….48

Fig. 11 Heart phantom solution ...……….49

Fig. 12 Schematic of the communication scheme……….50

Fig. 13 Schematic of the phantom experimental setup ……….51

Fig. 14 Experimental setup for the animal experiment .……….52

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List of Abbreviations

BER - Bit Error Rate

CST - Computer Simulation Technology ECC - Electronic Communications Committee FCC - Federal Communications Commission GFSK - Gaussian Frequency Shift Keying IBC - Intra-Body Communication

ICD - Implantable Cardioverter Defibrillator ICT - Information and Communication Technology ISM - Industrial, Scientific and Medical

LCP - Leadless Cardiac Pacemaker

MICS - Medical Implant Communications Systems PCB - Printed Circuit Board

PER – Packet Error Rate RF - Radio Frequency

SAR - Specific Absorption Rate TPS - Transcatheter Pacing System UWB – Ultra-Wide Band

VCO - Voltage-Controlled Oscillator WBAN - Wireless Body Area Network WLAN- Wireless Local Area Network

WMTS - Wireless Medical Telemetry Service WPT - Wireless Power Transfer

WSN – Wireless Sensor Network

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Abstract

This thesis explores the communication and signal transmission for the in-body cardiac sensor networks, termed as multi-node leadless capsule pacemakers for cardiac resynchronisation therapy. The commonly used cardiac pacemaker technology requires intravascular leads which results in lead-related complications and infections. The only commercially available leadless pacemaker- Micra provided by Medtronic addresses the above-mentioned complications.

Nonetheless, Micra offers single-chamber stimulations which is not effective for the patients who requires multi-chamber pacing. The optimum solution is to have leadless pacemakers in the form of small capsules. They will be implanted in multiple chambers of the heart to form a multi-node pacemaker system to provide multi-chamber pacing. The thesis has primarily contributed towards development of the novel multi-node leadless capsule pacemaker communication system.

The first part of this thesis has investigated the radio frequency (RF) cardiac channel modelling for a wide frequency range to find optimum frequency of operation of such a system. The modelling was done through computational simulations in different highly detailed human voxel models followed by the design of electronics and miniaturised antennas for practical experiments in liquid phantom solutions and living animals.

The results showed that industrial, scientific and medical (ISM) band of 2.4 to 2.5 GHz is the optimal frequency of operation based on the size constraints of the capsules. The analysis showed that outer wall of the abdomen is the optimum position for placement of the subcutaneous implant which will act as hub for capsule synchronisation and data storage. We also found out that end-systole is the optimal time-period for communication between the intracardiac capsules. The final work of this thesis concluded that Gaussian frequency shift-keying (GFSK) is the optimum modulation scheme for the communication framework of the multi- node pacemaker system based on the total transmitted power required for reliable communication.

This thesis has laid the foundation and contributed towards the initial development of the multi-node leadless cardiac pacemaker system. The work will be carried forward to develop the complete prototype which can contribute to improve and save lives of millions of patients suffering from cardiovascular diseases. Such wireless in-body sensor networks are close to become a reality, which will further lead to the ‘Internet-of Implants’, thereby adding new functions and services.

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Chapter 1 1. Introduction

The medical field has been dominated by technological advancements in recent years and thus, the demand for medical devices is increasing at a high rate across the globe. The number of people suffering from chronic non-communicable diseases is increasing worldwide posing a huge social and economic burden on national economies. Over 3.5 million people are affected every year by chronic diseases like congestive heart failure as reported by the European Heart Failure Association in 2013. Thus, there is an urgent need to develop appropriate technologies that can provide early diagnosis of such diseases and contribute towards effective treatment in order to prolong and/or save lives of millions of people. Moreover, due to the ageing population, the burden on the healthcare system to provide treatment increases. The increasing life span and the fact that chronic disease is more common in the elderly will drive towards the development of new technical solutions and re-organisation of the healthcare system. One of the solutions would be to provide healthcare outside the clinical settings. Such treatment could be provided by multiple miniaturised wireless devices termed as wireless sensor networks (WSNs) which will make the need for automated, sensor- based monitoring an important object for research and development.

The rapid advancements in wireless communications and electronics technology have resulted in the development of WSNs which have been one of the most promising technologies in recent years. These sensors are miniaturised, low-cost and battery-operated devices having sensing capabilities that enable them to gather information about the surroundings. Normally, a sensor node consists of four main components: a sensing module for data collection; microcontroller unit for data processing and storage; a communication unit for data transmission and communication with other nodes; and a battery for powering the sensor node.

WSNs have come a long way from its introduction and found its application in a lot of domains. Starting from environmental monitoring and industrial applications, it has found its application in object tracking, agricultural sector and health monitoring. WSNs used in the healthcare systems have received significant attention from the scientific community due to their usefulness.

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Wireless human body sensors have become increasingly popular over the years due to the advancements of electronics technology resulting in miniaturisation and decrease in energy requirements. In addition to the ability to sense physiological parameters, these sensors are provided with artificial intelligence and data processing capabilities for detection and diagnosis of clinical symptoms. As a result, these wireless sensors have provided us the opportunity for continuous and remote monitoring of patients with critical illness. These sensors can also provide the opportunity for early detection and prevention of diseases. This will in-turn lead to specialised healthcare and major improvements in quality of life.

1.1 Background

1.1.1 Wireless Body Area Network

Wireless body area network (WBAN) is defined as a wireless sensor network in and around the human body that involves the combination of medical and communication technologies [1-4]. It has evolved as an emerging technology due to its possibility for use in medical and non-medical applications [5-8]. It consists of miniaturized sensor nodes for monitoring health, physical activity and emergency situations (see Fig. 1) and acts as a bridge between the physical and the electronics worlds. WBAN provides a number of advantages over traditional monitoring systems. Firstly, it allows mobility of the patients due to use of portable physiological monitoring devices. Secondly, it allows continuous monitoring of the patients. The collected data could be sent to remote servers for storage and analysis.

WBAN consists of a hub or gateway node to communicate with the outside world through communication networks such as standard telephone network, mobile phone network, dedicated networks, Wi-Fi, Bluetooth or public wireless local area networks (WLANs). WBAN is in the process of using 5G networks to securely transmit the patients’ data [9, 10]. Information and communication technology (ICT) researchers are integral participants in the development of WBAN as the communication systems need to be further developed to achieve the full potential of WBAN. The IEEE 802.15.6 task group (TG6) [11, 12] had been established to provide an international standard for BANs.

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The medical devices in WBAN can be classified into three broad categories- wearable, ingestible and implantable. Wearable devices are worn by the patients to monitor the physiological conditions of the patients. They have sensors that can for example monitor the glucose level [13], temperature [14], heart rate [15] or other biochemical parameters of the patients [16]. The data can be stored in such devices or communicated to an external hub. The communication for wearable devices is simpler as the device is worn outside the human body and the battery of the device can be easily replaced when necessary. The common applications of wearable devices are glucose monitoring for diabetic patients [13], artificial limb movements [17, 18] and heart rate monitoring for patients with cardiac irregularities [15].

Fig. 1 Schematic of a WBAN. The off-body access points could be a hospital access point, mobile phones or computers that could be used for data access and storage

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Ingestible devices are swallowed by patients and normally used for monitoring and diagnosis of the gastro-intestinal tract [19, 20]. While passing through the gastrointestinal tract, they can collect images, transmit real time video, sense physiological parameters and even deliver drugs. They are provided with batteries and normally have a lifetime of 24 hours or less. Capsule endoscopy [21] is a smart application of ingestible device. Communication of information is less complex for ingestible devices as they are normally deployed in the patients under monitored circumstances. Dedicated network and infrastructure are provided for collection of data.

Implantable devices are placed inside the human body using surgical operations or catheter-based procedures. They normally have three functional units; sensors for data collection, stimulators for performing certain activities when required, and communication unit for data transfer [22]. The communication aspects of implantable devices are challenging as these devices need to communicate from inside the lossy human body and are constrained by the battery power. Thus, this thesis focuses on the communication aspects of the in-body sensor networks.

1.1.2 Implantable Electronic Medical Devices

Implantable electronic devices are used by increasing number of people around the world for medical support. This has led to improved diagnosis and better treatment for various medical conditions. Implantable devices have in many cases outperformed their non-implantable counterparts. An implantable insulin pump placed close to the pancreas of the patient have shown more effective infusion of insulin than traditional insulin injections [23]. The implantation position of these devices depends on their functionalities. Some of these devices are implanted close to the target organ while some are implanted superficially. Superficial implantation simplifies the implantation procedure and provides easy access to the implant when required. The most common types of implants presently in research and development are as follows:

• Neurostimulators- These devices are normally placed on the skull to provide stimulations to different parts of the brain. They transmit low amplitude electrical signals to provide therapies for different neurological

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diseases like Parkinson’s [24], epilepsy and chronic depression. They have shown significant results over the medications [25, 26]. They are also able to provide therapies to very specific parts of the brain.

• Cochlear implants- Cochlear implants are used to provide aid to deaf people or people with poor hearing. It is one of the most successful neural prothesis developed till date that can allow the acquisition of spoken languages in children born deaf [27]. They replace the functionalities of the damaged parts of the ear and convey the acoustic signals directly to the hearing nerves of the brain.

• Retinal implants- Retinal implants are intended to provide partial vision to blind people who are blinded by the degeneration of photoreceptor cells in the eye [28]. The retinal implants consist of microelectronics and micro- electrodes implanted in the retina. They stimulate the retinal nerve cells to give the perception of vision by the brain.

• Biosensors and drug delivery systems- Biosensors are being developed for implantation under the skin for continuous monitoring of physiological conditions and biochemical properties in the patients. Glucose monitor can sense the blood glucose level and an insulin injector can inject insulin when required. The implantable systems can also be used for targeted drug delivery [29]. This will allow lowering of the dosage of the medication and possible reduction of the side-effects.

• Cardiac implants- Cardiac implants are the most widely used categories of implantable medical devices. They include pacemakers and implantable cardioverter defibrillator (ICD) [30]. These devices monitor the cardiac rhythm by measuring the cardiac electrical activity. They stimulate the heart by providing electrical pulses at the required intensities and positions of the heart when necessary. They are equipped with different sensors like impedance sensor and accelerometer to continuously measure the conditions of the heart.

Currently, a number of other implantable medical devices are in various phases of development. Gastric pacemakers for example may be implanted in the abdomen

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to send mild electrical pulses to treat patients with obesity and patients suffering from gastroparesis [31]. The focus of this thesis is on cardiac pacemakers which is elaborated in the Chapter 3.

1.2 Aims of the Thesis

The primary aim of the thesis is to study the communication and signal transmission for in-body sensor networks. The multi-node leadless cardiac pacemaker is used as a case study for this purpose. The specific aims are listed below:

1. To study the optimum frequency of operation for communication between the multi-node leadless pacemakers (Paper I)

2. To study the optimum position for placement of the subcutaneous implant that communicates with the intra-cardiac capsules (Paper I)

3. To study the effects of intracardiac blood volume change during the cardiac cycle on RF channel characteristics (Paper II)

4. To study the in-body, on-body and off-body path loss models for the cardiac channels (Paper III)

5. To evaluate data telemetry for the multi-node pacemaker system (Paper IV)

6. To find the optimum modulation scheme for data telemetry for the pacemaker system (Paper IV)

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1.3 Contribution of the Thesis

The overall contribution of this thesis has been towards the development of the multi-node leadless pacemaker system. The research done as a part of thesis has provided a rational base to develop such a system in the near future.

The main contributions of this thesis are:

1. The proposed architecture of the multi-node leadless pacemaker system in which the three pacemaker capsules are placed in the right atrium, right and left ventricles respectively with an additional subcutaneous implant placed under the skin which acts as the master hub. (Paper I)

2. The optimum frequency of operation for this system is the industrial, scientific and medical (ISM) band of 2.4 GHz to 2.5 GHz based on the size constraints of the capsules. (Paper I)

3. The outer wall of the abdomen is the optimum position for the placement of the subcutaneous implant compared to the shoulder and the lateral side of the thorax. (Paper I)

4. The path-loss increases with increase in ventricular blood volume and the end-systole is the optimal time-period for communication between the intracardiac capsules. (Paper II)

5. For the in-body to in-body link, coupling between the implants decreases linearly with the increase in distance between them and decreases logarithmically for the in-body to off-body link. (Paper III)

6. Design of a simple prototype for the leadless pacemaker system by fabrication of miniaturized antennas and printed circuit boards (PCBs).

(Paper III)

7. Gaussian frequency shift keying (GFSK) is the optimal modulation scheme for the leadless pacemaker system based on the total transmitter power

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consumption required for reliable communication based on the threshold levels of bit error rate and packet error rate (Paper IV).

8. Validation of theoretical and mathematical models by liquid phantom experiments and living animal experiments to provide a methodological framework for conducting biomedical research for developing new medical implant technologies (Papers I, II, III, IV)

1.4 Structure of the Thesis

The thesis is primarily organised into eight broad sections. The first section has focused on providing the background information behind the thesis. It has focused on the aims and objectives of the thesis. It has also listed out the key contributions of this thesis. The next seven sections are as follows:

• Chapter 2 emphasizes implant communication technology and reviews different communication technologies described in the literature. It also outlines the advantages and disadvantages of each of the communication technologies.

• Chapter 3 focuses on the cardiac pacemakers. It discusses about the conventional pacemakers and the single-chamber leadless pacemakers.

Finally, it introduces our proposed architecture of the multi-node leadless pacemaker technology.

• Chapter 4 provides a short overview of the materials and methods used for this thesis. It has been subdivided into three broad sections- computational modelling, phantom experiments and living animal experiments.

• Chapter 5 gives the summary of the results for this thesis. The section is organised as a short summary of the papers included in this thesis. The chapter has focused mainly on the most important results to provide a clear understanding.

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• Chapter 6 provides a discussion about the methods and the observed results. It evaluates the different methods used for the studies and discusses its usefulness.

• Chapter 7 concludes the thesis by summarizing the major findings and contributions of the research.

• Chapter 8 gives a brief description of the proposed future developments. It also discusses the application of this work to other domains.

The last part of the thesis contains the bibliography and appendix with the list of papers published as a part of this thesis.

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Chapter 2 - Implant Communication Technologies

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Chapter 2 2. Implant Communication Technologies

Implantable devices need to communicate with outer peripheral devices for data transfer and device monitoring. The device monitoring helps in analysing the battery health and assessing the remaining lifetime of the device. Moreover, the data transfer is required for analysis and monitoring the health of the patients by clinicians responsible for patients’ care. In some cases, configuration changes need to be done after analysis of the data. The data transfer also helps in erasing the stored data from the implant memory. This frees up the space from the implant memory to allow further storage and analysis.

Implantable devices also need to communicate with each other for synchronised operations. The synchronisation between them increases the efficacy of the implantable system. Moreover, they can share data and benefit from the parasitic data. Sensor data from different implants can help in better diagnosis of the conditions and provide effective treatment of diseases. This in-turn will provide personalised treatment for the patients and a better purpose for the multi-implant system in the body.

Implant communication system comes with numerous challenges. They are listed below:

• Frequency spectrum regulations- The requirement for the medical frequency spectrum has been increasing over the years. The currently available frequency bands- medical implant communications systems (MICS) band, the wireless medical telemetry service (WMTS) bands, the industrial, scientific, and medical (ISM) bands, and the ultrawide band (UWB) are not enough [42]. The ever-increasing number of medical devices is causing interference resulting in disruption of critical medical services. Since ISM band is an unlicensed band, it can be used for other non-medical purposes as well which will lead to more interference.

• Power consumption- The lifetime of the implantable devices is restricted by the available battery power. Since it is quite difficult to replace the

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batteries of implantable devices, reduced power consumption for communication is necessary. Wireless power transfer (WPT) for recharging the batteries is an alternative, but WPT has not yet developed to that extent necessary to efficiently recharge the batteries of deep-tissue implants [43].

Moreover, WPT is also restricted by the threshold values of specific absorption rates (SAR) for human body. Power exceeding the SAR values is not permitted as it might damage the human tissues due to heating.

• Data rates- The communication systems are also limited by the data rates.

For capsule video endoscopy, high data rates are required for seamless transmission of videos of the gastrointestinal tract to an external device.

UWB can be used for this purpose but the propagation loss is very high in this frequency band. So, the communication system needs to establish a trade-off between the data rate and the frequency of operation.

• Security- The security and privacy are one of the most important necessities of the biomedical devices. The communication systems need to be ultra- secure to prevent eavesdropping. Most of the countries have strong laws and regulations to ensure the protection of patient information. Moreover, if the eavesdropper can hack a medical device, it could be detrimental for the patient.

The thesis primarily focuses on the multi-node implantable system. So, communication between the different nodes is one of the primary purposes of the device. The devices need to work in synchrony for an effective treatment. The synchronous beating of the heart can only be provided if the timings of the pacing by each implant node is co-ordinated. Moreover, the information collected by the sensor present in each node should be shared for analysis and decision making.

In the section below, we will discuss about existing and emerging communication technologies for biomedical implants. We will evaluate the advantages and disadvantages of each of the communication technologies.

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Table I. Performance comparison of different implant communication technologies

Communication Technology

Method of

Propagation Frequency Power

consumption Path loss Data rate

Communication

distance Standard Research status

Inductive coupling

Magnetic

field <50 MHz Low High <1

Mbps < 5 cm none Established Technology

Intra body Electric field <20 MHz Moderate Low <100

kbps < 10 cm IEEE Standard 802.15.6

Near Future Technology

Optical Infrared 300 GHz -

430 THz High Very

High

<100

Mbps < 1 cm none Established Technology

Ultrasound Ultrasonic <3 MHz High High <250

kbps < 10 cm none Established technology

Molecular Action

potential < 1 KHz Ultra-low Ultra- High

<10

bps < 0.1 cm none Future Technology

Radio

frequency Radio waves

MICS band (402 – 405

MHz), ISM band

(433.1–

434.8 MHz, 868–

868.6 MHz, 902.8–928

MHz, and 2400–2500

MHz)

High Moderate < 2

Mbps < 20 cm MICS, ISM

Established Technology

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2.1 Inductive Coupling Communication

Inductive coupling is one of the simplest forms of communication in which both data and energy can be transferred by the mutual coupling between the primary and secondary coils [44]. Communication is mostly achieved by narrow-band low frequency inductive coupling since at low frequency, the magnetic flux is more penetrable [45]. Current in the primary coil of the transmitter implant creates a magnetic field which in turn induces a current in the coil of the receiver implant.

The main advantage of inductive coupling is that the size of the implants could be made very small as there is no requirements of antennas. The battery capacity could be reduced due to inductive power transfer. The inductive coupling is only suitable for short distance communication between the implants as the magnetic field strength falls significantly over distance inside the human body [46]. Moreover, the coupling is highly diminished even if there is small misalignment between the coils.

Thus, this inductive coupling communication is not suitable for deep implants and for implants in which the alignments of the implants inside the human body cannot be guaranteed. Mostly, inductive coupling offers a small bandwidth and as a result, is not suitable for high data rate applications. There have been recent studies [47]

to increase the data rate by using graphene nano-coils but further research needs to be conducted to prove its feasibility and its effects on human body, when operated in terahertz (THz) frequency band. In case of inductive coupling, magnetic field strength and frequency of operation are key parameters that need to be selected, based on the admissible SAR values for safety of the patients.

Inductive coupling has been used for a wide range of implantable devices like cochlear implants, retinal implants and neural implants. They are not suitable for the multi-node leadless pacemaker system as the implants would be embedded quite deep inside the human body. Moreover, the cardiac movements would cause displacement of the implants resulting in misalignment of the inductor coils. This will in turn result in degradation of the communication link.

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2.2 Intra Body Communication

Intra-body communication (IBC) was first introduced by Zimmerman in 1996 [48]

which is based on the propagation of electric fields through body tissues for communication. A pair of electrodes is used to generate a current at the transmitter side and the electric field propagates through the tissues. Another pair of electrodes is used at the receiver side to collect the transmitted signal. This method uses the lossy dielectric nature of the conductive human tissues for communication. Mostly, this form of communication operates in low frequency range from tens of kilohertz (kHz) to tens of mega-hertz (MHz). IBC also uses low-power signals and the skin acts a non-conductive layer. This prevents the leakage of signals outside of the body. Thus, IBC is highly robust to security breaches which improves the data privacy and security of the implantable system.

IBC can be classified into two types based on the signal coupling method used for transmission inside the human body environment- capacitive coupling and galvanic coupling. In capacitive coupling, the signal is coupled via the signal electrode of the transmitter and the receiver [49]. The return path is established outside the human body by a common ground electrode. This was the original technique of IBC proposed by Zimmerman. In galvanic coupling, a pair of electrodes is present at both the transmitter and receiver sides [50]. The current flows through a direct path between the transmitter and the receiver electrodes. The current density decreases with the increase in distance between the transmitter (Tx) and receiver (Rx) electrodes.

Capacitive coupling is suitable for on-body to on-body application and not for implant to implant communication as the return path of the current is established outside the body, whereas the galvanic coupling is more suitable for in-body to in- body implant communication, as the signals are confined within the human body, so the effects of environmental noise are minimum.

Despite the relatively high potential of IBC, not much advances have been made in this domain. The design specifications of the IBC prototypes are also not well- established. Moreover, the techniques lack significant experimental validation in in-vivo models. IBC measurements have high complexity and there are discrepancies over the data reported by the different authors. Therefore, till now there have been no well-established standards and regulations on the application of

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IBC. Thus, the promising nature of IBC needs to be further explored in the future to establish its foothold as an effective form of implant communication.

2.3 Optical Communication

Optical communication has made lot of progress in the recent years but the use of optical communication for implants is not common [51]. Optical communication happens by the transmission of infrared waves (IR) between the transmitter and receiver. The laser diode at the transmitter side converts the electrical signal to IR signal. This form of communication is low power consumption which can increase the lifetime of the implants.

The major disadvantage of optical communication is that it requires line-of-sight communication. The movement of human body and cardiac movements could cause non line-of-sight conditions between the cardiac implants which will result in link loss between the implants. Moreover, the loss is so high that the communication is limited to extremely short distance. So, it is only suitable for transcutaneous implants and not for deep tissue implants like cardiac implants.

2.4 Ultrasound Communication

Ultrasound communication happens by the propagation of mechanical waves inside the human body from the transmitter to the receiver. At the receiver side, the mechanical waves are then converted to the electric signals with the help of piezoelectric transducers. G. Enrico et. al. has designed and implemented software- defined testbed for the wideband ultrasound communication and shown its feasibility for communication inside the human body [52].

The major drawback of ultrasound communication is that it suffers from very high levels of attenuation inside the human body [53]. Since a significant portion of the energy is absorbed during ultrasound communication, it will cause heating of the biological tissues. Furthermore, the data collected for the biological effects of ultrasound communication are inconsistent and controversial. But the communication can be coupled with piezoelectric energy harvesting techniques to

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provide added advantages. Currently, there have been no standards and regulations for the use of ultrasound communication for implants.

2.5 Molecular Communication

Molecular communication is inspired by nature which uses molecules to encode, transmit and receive information for in-body communication. It tries to mimic the ways the biological cells communicate. It encodes the information in the properties of the molecules such as type, concentration, ratio, time of release, etc. The major advantage of this type of communication is that it is biocompatible and enables the design of miniaturized implants even at nanoscale dimensions.

Molecular communication is suitable for nanomachines which can be used for drug delivery and sensing physiological properties of human body. It can provide communication between the nanomachines to form a nanonetwork inside the human body of nanoscale implants.

Molecular communication is a very promising direction, but the research has been mostly limited to theoretical study so far. These networks are difficult to design and realize in practical environment due to nanoscale dimensions and the stochastic nature of the biochemical reactions [54]. Moreover, the basic building blocks of a molecular communication network are very different from the conventional communication scenarios and thus require the design of novel methods and architecture [55]. The research has been mostly limited to simplified communication models, but study of more realistic models is warranted in the future.

2.6 Radio Frequency Communication

Radio frequency communication (RF) is the most well-researched implant communication technology among those discussed in this section. RF communication takes place by feeding the transmitted signal to the antenna of the transmitter which radiates the RF electromagnetic waves (EM) that are collected

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by the receiver antenna [56]. The most important parameters defining a RF communication are explained in the following sub-sections.

2.6.1 Frequency of operation

The frequency of operation is one of the most important parameters defining the RF communication for implants. The standardisation bodies have set standards for the frequency of operation, which varies based on the geographical regions. The International Telecommunications Union-Radiocommunications Recommendation SA.1346 (ITU-R, 1998), has recommended the use of 402-405 MHz for the medical implantable communication systems (MICS). The primary reason for selecting this frequency is that it shows better propagating characteristics for RF inside the human body, allows design of reasonable sized antennas and is available world-wide.

Moreover, there is not much interference in this spectrum which allows the clinicians and the medical practitioners to run the low power medical devices smoothly. The other available frequency band for the implantable technologies is the ISM band. Electronic Communications Committee (ECC) has defined the ISM bands of 433.1–434.8 MHz, 868–868.6 MHz, 902.8–928 MHz, and 2400–2500 MHz for the use of implant communication. Since the ISM band is a free unlicensed band, there are lot of devices working in this band thereby causing interference.

Despite the standardised frequency bands, the selection of the optimal frequency depends on lot of other factors like position of the implant, purpose, required antenna size, etc.

For the on-body communication, the wireless medical telemetry service (WMTS) frequency bands of 608–614, 1395–1400, and 1427–1432 MHz have been allocated by the Federal Communications Commission (FCC) in the United States. FCC has also allocated the ISM bands of 902–928 and 2400.0–2483.5 MHz for this purpose.

In Europe, the ECC has allocated ISM bands of 433.1–434.8 and 868.0–868.6 MHz for on-body communication. In addition to these frequency bands, an ultrawide band (UWB) of 3.1 – 10.6 GHz has been authorised for use. This band is suitable for high data-rate applications but shows considerable deterioration in propagation characteristics.

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2.6.2 Channel modelling

The knowledge of the propagation channel is one of the most important steps towards the design of a wireless communication system. In free space, such measurements are taken by doing physical experiments and then processing the data to find the propagation characteristics. This is quite difficult for implantable devices as it is not instructive to put probes inside the body of a patient to collect the data. Unlike free space, the human body is a high lossy medium with so many kinds of tissues and organs having different shapes and sizes. Moreover, each tissue has own unique frequency-dependent dielectric properties. The propagation channel also varies with the shape and size of the human body. For in-body channel modelling, a statistical path-loss model using mathematical formulations is the first step towards the goal. This can be further validated by in-vitro and in-vivo experiments. The generalised link power budget [57] can be expressed as:

PRx = PTx + GTx + GRx – L (1)

where PRx is the power received by Rx antenna in dBm¹, PTx is the power transmitted by the Tx antenna in dBm, GTx and GRx are the gains of the Tx and Rx antennas in dB respectively and L is the total of all the losses during transmission.

L can be further expressed as:

L = PL + PLF + MLTx + MLRx (2)

where PL is the path loss in dB, PLF is the polarization loss factor in dB due to the polarization mismatch between the Tx and Rx antennas, MLTx and MLRx are the impedance mismatch losses of the Tx and Rx respectively.

The parameters determining the pathloss will vary based on the frequency of operation and position of the implant.

1 dBm- decibel-milliwatts (dBm) is unit of level used to indicate that a power ratio is expressed in decibels (dB) with reference to one milliwatt.

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2.6.3 Antenna design

Antennas are one of the most vital components of any RF communication system.

Designing antennas for implants is a challenging task. They need to be miniaturised and have good performance as well. The resonant frequency of the antennas tends to change when placed inside the human body and the performance subsequently becomes unpredictable. So, impedance matching of the implant antennas is also very challenging. Moreover, the antennas need to be biocompatible for preventing infections and ensuring patient safety.

Mostly patch antennas are preferred for implants due to their flexibility and ease of design. Dimensions of the implant antennas need to be smaller than the traditional antennas which are normally half-wavelength (λ/2) or quarter wavelength (λ/4) size². Researchers have used intelligent techniques like the use of highly dielectric materials [58] and addition of shortening pins [59] to reduce the size of the antennas without significantly reducing the performance. Despite these efforts, the size of the implant antennas has not been significantly reduced and designing highly efficient mm-sized implant antennas remains an important research direction.

Some research has been done in the past regarding the in-body channel modelling and the design of the communication framework but is by no means exhaustive.

Although, RF communication is the most prominent form of communication for the implants, the research has been mostly focused on theoretical modelling and there have been limited practical designs and validations. Other communication technologies have shown some promises but haven’t been able yet to deliver on those promises. So, this thesis will investigate the communication based on the radio frequency for the multi-node leadless cardiac pacemaker.

2 λ = c*f, where λ is the wavelength, c is the speed of light and f is the frequency

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Chapter 3 - Cardiac Pacemakers

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Chapter 3 3. Cardiac Pacemakers

Cardiovascular diseases have been one of the leading cause of deaths worldwide in the recent years. They are mainly caused due to malfunction of the heart’s conduction system resulting in disturbance of the cardiac rhythm. These disturbances of the conduction system may cause dyssynchrony of the blood- pumping function which adversely affects the efficiency of the heart and lead to heart failure or cardiac arrest. Cardiovascular implantable electronic devices have been quite effective in providing the appropriate solutions by restoring the normal heart rhythm. The use of these devices has significantly increased over the last decade due to the expansion of their functions. They have also shown improved quality of life and increase in the survival rate.

These implants can be classified into three broad categories- 1) anti bradycardia- or tachycardia- pacemakers, 2) implantable cardioverter-defibrillators (ICD), and 3) cardiac resynchronization therapy devices (CRT) [74]. The first kind of implants are used for treating bradycardia which is slow heart rhythm usually less than 60 beats/min [75]. It continuously monitors the heart rate and if it detects a low heart rate, it starts pacing to provide the adequate heart rate to the patient. ICDs are used to treat tachycardia which is very fast heart rhythm by providing anti-tachycardia shocks to provide life-saving therapies [76]. CRTs are used to treat patients who have unsynchronised contraction of the left and right ventricles [77]. They continuously send small, undetectable electrical pulses to both ventricles to help them beat in a more coordinated or "synchronized" fashion which improves the ventricular contractility and the pumping efficiency of the heart. Though our proposed multi-node leadless pacemaker system has the possibility to include all the three modalities, but our initial aim is aim is to design a pacemaker for treating bradycardia and provide cardiac resynchronisation therapy wherever necessary.

3.1 Conventional Pacemakers

The first implantation of the cardiac pacemaker took place in Sweden and the United States and in 1960s which initially extended the lifetime of the patient by

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18 months [32]. Since then, a lot of improvements have happened in the design, implementation and implantation of the cardiac pacemaker. Currently, more than 0.75 million permanent pacemakers are implanted in patients per year in the United States alone [33]. The first pacemakers only contained a battery and timer for pacing. It had neither sensing nor data storage and communication capabilities. The current pacemakers are sophisticated devices. They not only have the above- mentioned capabilities but also multiple leads for multi-chamber pacing [34].

Fig. 2 Schematic of a bi-ventricular pacemaker. A left ventricular lead is implanted in addition to the conventional dual chamber leads in right ventricle and right atrium, to synchronize both the ventricles and prevent heart failure.

Pacemaker consists of a biocompatible metallic can that is placed in the subcutaneous pocket of the shoulder below the collarbone (see Fig. 2). This placement requires surgical operation. The can houses an electric pulse generator that contains a lithium battery and the associated electrical circuitry. The battery occupies most of the space available in the can. One to three metallic wires or so- called leads connects the can to the chambers of the heart. The tip of the leads contains sensors that can monitor the electrical activity of the heart to determine if the heart is beating irregularly or not. In case of irregular beating, electrical pulses are sent from the can via the leads to synchronise the beating of the heart. The

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pacemaker pulse generators need to be checked regularly for at least two to three times a year and must be replaced every five to ten years as the battery runs out.

While the conventional pacemakers are effective, approximately one in every eight patients shows early complications. They are related to the transvenous lead or the subcutaneous can. These complications include lead dislodgement, cardiac perforation, pneumothorax and pocket infection or hematoma [35]. Long-term complications include lead breakage, insulation failure, venous obstruction and tricuspid regurgitation. Additionally, the development of lead related endocarditis is a major concern with a high mortality rate [36, 37, 39]. It is evident that the leads are the weakest links of the current pacing systems. Thus, leadless pacemakers can help us to reduce these short-term and long-term complications.

3.2 Leadless Pacemaker

Leadless pacemaker was first conceptualised in 1970 [38]. There is currently one commercially available leadless pacing system: the Micra Transcatheter pacing system (TPS) (Medtronic plc., US) [40]. This technology offers only ventricular stimulation. The devices are implanted in the right ventricular wall using a catheter delivery system. The schematic of the leadless pacemaker is shown in Fig. 3.

Though the leadless pacemaker is a new technology, the short-term results have been promising.

Fig 3. Schematic of a leadless pacemaker capsule. The capsule is placed inside the chambers of the heart by the catheter technology. The capsule is maneuvered to place in the desired position and the screw is used to attach to the cardiac walls.

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The currently available leadless pacemakers offer only single chamber stimulation and don’t have the capability of atrioventricular synchronous pacing. Therefore, they are not suitable for patients requiring dual chamber pacing. Technology providing multi-chamber stimulations and cardiac resynchronization will be an optimum solution [41]. Thus, in this thesis we introduce the architecture of a multi- node leadless capsule pacemaker system and investigate the communication framework between the capsules to provide synchronous cardiac action.

3.3 Multi-node Leadless Pacemaker

The architecture of multi-nodal leadless pacemaker technology has been introduced in this thesis [60-63]. Each cardiac implant which will hereinafter be called capsules will be equipped with RF modules to communicate between them (see Fig. 4).

Three capsules referred to as C1, C2 and C3 will be present in the right ventricle, right atrium and left ventricle, respectively.

Fig. 4 Schematic of a three-node leadless capsule pacemaker application for cardiac resynchronization therapy. The capsules C1, C2 and C3 are placed inside the chambers of the heart and they can communicate with the subcutaneous implant S1. RA- right atrium, RV- right ventricle, LA- left atrium, LV- left ventricle, C- capsules and S- subcutaneous implant.

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Each capsule will contain three units: sensor unit, communication unit and the pacing unit. The sensor unit will contain sensors- impedance sensor and accelerometer for sensing the cardiac rhythm and collecting data. The communication unit will contain the data processing unit and the antennas for communicating between the capsules. Finally, the pacing unit will contain a battery and the electrodes for pacing. There is also a subcutaneous implant referred to as S1 that will act as the master hub for the capsules C1, C2 and C3 placed inside the heart. The data collected by the sensors present in the C1, C2 and C3 will be sent to S1 for decision making. S1 will act as the data storage unit and a relay node for communicating with the outside world. The data stored inside S1 can be downloaded wirelessly to the outer peripheral devices like phones, computers or dedicated access points for data analysis, device monitoring and configuration changes. The subcutaneous implant will contain the main processing unit and decision-making unit as this will reduce the burden on the capsules C1, C2 and C3.

This will in turn increase the longevity of the capsules as they are quite difficult to extract once implanted inside the heart. It is comparatively easier to replace the batteries of the subcutaneous implant. Moreover, wireless recharging techniques can be employed to recharge S1 as the depth of this implant is just few centimetres below the skin. The current wireless recharging technology is not so well- developed to efficiently recharge the deep tissue implants C1, C2 and C3.

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Chapter 4 - Materials and Methods

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Chapter 4 4. Materials and Methods

The communication unit is one of the most important unit of the capsules. This thesis contributes towards the design of the communication framework of the multi- node pacemaker technology. It is a very challenging task as it is quite difficult to estimate the channel conditions for the cardiac channel. The cardiac channel modelling is done using three methodologies- computational modelling, liquid phantom experiments and living animal experiments. We have estimated three common communication scenarios- in-body to in-body, in-body to on-body and in- body to off-body channel. The following sub-sections talk about the methodologies and the experimental conditions in short.

4.1 Computational Modelling

Computational modelling is our primary step for estimating the in-body channel models. They help us to get an estimate of the channel models which can be later verified using in-vivo experiments. The computational modelling mainly focuses on finding the channel model for implant to implant and implant to sub-cutaneous implant communication channels. Computer Simulation Technology (CST)³ [64]

was used to perform the simulations. It is a 3D electromagnetic software simulation tool that allows the simulations in both the time and frequency domains. The software computes the path loss by solving the Maxwell equations in a complex medium. The complex medium is represented by the voxel data sets mimicking the frequency dependent dielectric properties of human tissues. The simulations are computed in the time domain solver of the CST. Then, the results are verified in the frequency domain solver to validate the consistency of the results.

We used three biological voxel models for the work- muscle block, Donna and HUGO models. Each voxel represents a specific biological human tissue. It produces its own characteristic response when an electric filed is imposed on it.

3 www.cst.com

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The muscle block model is the simplest model while the HUGO model is the most complex one. Initially, the simple models are used as it is difficult to conduct multiple experiments on the HUGO model as it is computationally very expensive.

Each simulation takes more than 24 hours in the complex models resulting in serious delays in conducting multiple experiments.

The dielectric properties used for the tissues for each of the voxel model are obtained from the 4-Cole-Cole model provided by Gabriel [65, 66]. The dielectric properties are selected for the desired frequency range⁴ and then, curve-fitting techniques are used to find a curve that approximate the entire data-range. Since, the frequency selected for the experiments was wide-band, n^th order polynomial functions were applied for the best fit with minimum least square method error.

4.1.1 Muscle block model

We designed a simplified computational model called the Muscle block model which represents one chamber of the human heart (see Fig. 5). It is a 3D electromagnetic model having a resolution of 1mm * 1mm * 1mm. The communication models or capsules are modelled as simple dipoles of length 5mm and diameter of 2mm. We considered this as the logical size of the antennas for the capsules since the overall size of the capsules is estimated to be 10 mm in length and 5mm in diameter. The rest of the space will be occupied by battery and the electronics. The dipoles are enclosed in a vacuum tube of 1mm to prevent the direct contact with the issues. The direct contact will cause impedance mismatch resulting in high radiation loss. The capsules are placed on either side of a sphere of diameter 50 mm. The sphere is filled with blood which mimics the frequency dependent dielectric properties of human blood. The sphere is centrally placed in a cubic structure of size 500 mm * 500 mm* 500 mm. The cube mimics the frequency dependent dielectric properties of human muscle. The model is created to estimate the coupling between the two capsules when a Gaussian pulse of 1W is transmitted.

In other words, we try to estimate how much is the loss of signal or the path loss when a signal is transmitter from one capsule to another. This is calculated using

4 http://niremf.ifac.cnr.it/docs/DIELECTRIC/AppendixC.html

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the scattering parameter S21⁵. The distance is being kept constant at 50 mm. The coupling is calculated over the frequency range of 300 MHz and 3 GHz. Such a wide frequency range is selected since we wanted to explore a wider frequency space to find the best results. However, the main disadvantage of selecting such a wide frequency range is the very high computational time. We didn’t explore beyond 300 MHz as the antenna efficiency of such antennas at such low frequency is very low. We also didn’t go beyond 3 GHz as the tissue path loss tends to increase a lot beyond 3 GHz.

Fig. 5 Dipoles C1 and C2 enclosed in vacuum placed at two ends of the diameter of a sphere containing blood inside a muscle block. The resolution of each voxel is 1mm × 1mm × 1mm and the model has been simulated in CST in a frequency range of 0.3 – 3 GHz. The size of the blood volume has been reduced in this figure for better visual representation of the dipole antennas [60]

5 S21 represents the power received at port 2 relative to the input power at port 1

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4.1.2 Donna model

The Donna model is a more complex model compared to the muscle block model.

It is a biological model from the CST voxel family [67]. It is a heterogeneous human body model of an over-sized 40 years old woman having a weight of 79 kilograms.

Though it is a heterogenous model with the availability of wide range of tissues, the human heart is a represented by a homogeneous volume comprising of voxels representing the average dielectric properties of the human heart. The model has a resolution of 1.875 mm × 1.875 mm × 10 mm.

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Fig. 6 (a) Dipole antenna C1 placed inside the right ventricle close to the apex of the heart and C2 inside the right atrium in Donna voxel model, (b) Dipole antenna C1 placed inside the right ventricle close to the apex and S1 subcutaneously placed on the shoulder where the can of a pacemaker is normally placed. [60]

The communication link was established by placing two dipoles of length 5 mm and diameter 2 mm inside the heart. One of the dipoles was placed inside the right atrium and the other one inside the right ventricle close to the apex (see Fig. 6a).

The simulations only considered the upper torso of the human body between the lower base of the neck and the upper part of the abdomen. This was done to reduce the computational time as the full-body simulation is computationally more expensive. The number of mesh cells reaches around 1 billion for full-body simulations. Moreover, the full-body simulations are not required for estimation of the cardiac channel inside the heart or close to the heart.

Communication and Signal Transmission for In-body Cardiac Sensor Networks