Collection and recording of brain signals in chicken embryos

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UNIVERSITÁ DIPISA

DOTTORATO DI RICERCA ININGEGNERIA DELL’INFORMAZIONE

C

OLLECTION AND RECODING OF BRAIN SIGNALS IN

CHICKEN EMBRYOS

DOCTORALTHESIS

Author

Siriana Paonessa

Tutors

Prof. Stefano Di Pascoli Prof. Massimo Macucci

Reviewers

Prof. Carmine Ciofi Prof. Juan José Vaquero

The Coordinator of the PhD Program

Prof. Fulvio Gini

Pisa, September 2019 XXXI

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Ringraziamenti

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Lprimo ringraziamento va a mio marito Giuseppe e a mio figlio Francesco Paolo.

Ringrazio Giuseppe per avermi supportato, sopportato ed aiutato durante questi anni. Senza il suo sostegno, il suo amore, la sua comprensione e la sua presenza costante non sarei arrivata alla fine di questo percorso universitario. Nei momenti di difficoltà e di immensa felicità mi è sempre stato vicino offrendomi sempre il suo aiuto e il suo sorriso. E’ stato il mio faro nel buio e la mia roccia nelle difficoltà. Ringrazio mio figlio Francesco Paolo per aver arricchito e colorato la mia vita. Lui è stato parte integrante del mio percorso di dottorato, con il suo arrivo a metà dottorato, mi ha in-segnato a studiare e lavorare insieme a lui. Ho imparato l’importanza della pazienza, della lentezza e delle piccole cose.

Un sentito ringraziamento va ai miei genitori e mia sorella Paola, che mi hanno aiutato moralmente e concretamente con l’arrivo di Francesco Paolo. Coinciliare un lavoro di laboratorio con la nascita di un figlio non è facile, e loro con la loro presenza costante mi hanno sempre sostenuto ed aiutato, con profondo affetto e dedizione gratuita. Un grazie ai miei colleghi di laboratorio, con i quali questi anni ho trascorso parte del mio tempo, per aver arricchito le mie conoscenze e reso piacevole e leggero il lavoro. Un sentito ringraziamento va ai miei professori, il Prof. Stefano Di Pascoli, che mi ha seguito dall’inzio alla fine del mio percorso universitario, trasferendomi le sue compe-tenze e conoscenze, il Prof. Francesco Pieri, che mi ha supportato ed aiutato durante il mio intero lavoro di laboratorio, il Prof. Massimo Macucci per il suo sostegno nei ultimi anni di dottorato.

Ringrazio entrambi i coordinatori del corso di dottorato, che si sono susseguiti durante il mio percorso di studi: il Prof. Marco Luise, per avermi aiutato in ogni mia richiesta, soprattutto durante il mio periodo di astensione per maternità e di ripresa; il Prof. Ful-vio Gini per avermi aiutato negli ultimi mesi di dottorato.

Infine, ringrazio tutti i parenti e gli amici che mi sono stati vicini con il loro aiuto, le loro parole, i loro sorrisi, tutto questo mi ha aiutato a portare a termine questo percorso.

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Summary

S

LEEP is an important function of the human brain. Sleep and sleep cycles are

fundamental for sensory system development in the whole life cycle of an indi-vidual, including embryonic life, to preserve brain activity, to create long-term memory, and for learning.

The measurement of brain signals is useful to quantify different brain states, such as sleep and wake states. The origin of cycles of sleep and wake in higher vertebrate animals (birds and mammals) are currently unknown, thus it is of particular interest to combine information that reflects different aspects of brain function.

Our research has been focused on the study of neurological signals during embryo-nic life. In this thesis, chicken embryos have been chosen as animal models for many practical reasons: the ease of access to chicken embryos, the fact that early stages of development and sleep in chicken are similar to those of humans.

The developed system consists of a transmitter placed outside the eggshell and of a receiver located outside the incubator. The transmitter and the eggshell are kept inside the incubator in order to guarantee the survival of the embryo. The communication between the transmitter and the receiver is implemented via infrared signals.

Subsequently, to improve the insertion and adhesion at the brain-electrode interfa-ce, new flexible polyimide electrodes have been developed instead of the metal wires, which are commonly used to detect neurological signals. Specifically, two different types of electrodes have been developed: passive and active. The passive electrode is based on a conducting polymer (PEDOT:PSS) deposited on a flexible polyimide sub-strate, where gold has been used to define the conducting line and the pad contact area. The active electrode is based on the fabrication of an organic electrochemical transistor (OECT), for which source and drain electrodes have been made with gold, the channel has been made with a conducting polymer (PEDOT:PSS) and the gate has been made with metal. The deposition of PEDOT:PSS has been performed using the inkjet prin-ting technology. Different types of ink, based on a PEDOT:PSS aqueous solution, have been tested and electrically characterized.

Finally, in-vivo tests on chicken embryos, using standard metal electrodes, have been completed to check the performance of the developed EEG system.

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Sommario

U

NA delle funzioni fondamentali del cervello umano è il sonno. Il sonno e i cicli di sonno sono fondamentali per lo sviluppo del sistema sensoriale durante tutta la vita di una persona, a partire dalla vita embrionale, per la creazione della memoria a lungo termine e per l’apprendimento.

La misura di segnali neurologici è utile per classificare i differenti stati del cervello, come gli stati di sonno e veglia. Le origini dei cicli di sonno e veglia negli animali ver-tebrati (uccelli e mammiferi) sono ancora sconosciute, per tale motivo è di particolare interesse mettere insieme informazioni che riflettono aspetti differenti delle funzioni celebrali.

La nostra ricerca si è incentrata nello sviluppare un sistema in grado di rilevare i se-gnali neurologici generati durante la vita embrionale. Sono stati scelti embrioni di pollo come modello animale per molte ragioni pratiche: la facilità di accesso all’embrione di pollo; la breve durata dello sviluppo embrionale; gli stadi del sonno simili a quelli umani. Nella tesi è stato sviluppato un sistema di acquisizione di segnali neurologici basato su un sistema EEG/ECoG wireless. Il sistema è composto da un trasmettitore posizionato al di fuori del guscio dell’uovo posto dentro un incubatore, e un ricevito-re posizionato fuori dall’incubatoricevito-re. La comunicazione tra trasmettitoricevito-re e ricevitoricevito-re avviene tramite infrarossi.

Attualmente vengono utilizzati fili metallici per rilevare i segnali neurologici, ma al fine di migliorare l’inserimento e l’adesione all’interfaccia cervello-elettrodo, nuo-vi elettrodi flessibili, basati su materiali plimerici, sono stati snuo-viluppati in questa tesi. In particolare, due tipologie differenti di elettrodi sono stati sviluppati: passivi e atti-vi. L’elettrodo passivo è basato su un polimero conduttivo (PEDOT:PSS) depositato su un substrato polimerico flessibile; le piste di conduzione e le aree di contatto sono state definite utilizzando l’oro come metallo. L’elettrodo attivo, si basa sulla fabbrica-zione di un transistor organico elettrochimico (OECT), dove gli elettrodi di source e drain sono realizzati con piste di oro, il canale è realizzato con un polimero conduttivo (PEDOT:PSS) e il gate è realizzato con un elettrodo metallico. La deposizione di PE-DOT:PSS è stata realizzata utilizzando una stampante a getto d’inchiostro. Differenti tipi di inchiostro, tutti basati su una soluzione acquosa di PEDOT:PSS, sono stati

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te-stati e caratterizzati elettricamente. Infine, prove in-vivo su embrioni di pollo, usando classici elettrodi metallici, sono state realizzate per valutare le performance del sistema EEG sviluppato.

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List of publications

International Journals

1. Paonessa, S., Barbani, N., Rocchietti, E. C., Giachino, C., Cristallini, C. (2017). Design and development of a hybrid bioartificial water-induced shape memory polymeric material as an integral component for the anastomosis of human hollow organs. Materials Science and Engineering: C, 75, 1427-1434.

International Conferences/Workshops with Peer Review

1. Paonessa, S., Pieri, F., Di Pascoli, S. (2020).Conductivity characterization of dif-ferent, inkjet-printed PEDOT:PSS layers on plastic substrates.In 11th World Bio-materials Congress, May 2020.

2. Paonessa, S., Pieri, F., Di Pascoli, S. (2017). Flexible polyimide electrodes for ECoG in chicken embryos. In European Material Research Society Spring Meet-ing 2017. FRA

3. Paonessa, S., Di Pascoli, S., Balaban, E., Vaquero, J. J. (2016, May). Design and development of a wireless infrared EEG recorder for chicken embryos. In 2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA)(pp. 1-6). IEEE.

4. Paonessa, S., Pieri, F., Balaban, E., Vaquero, J. J., Di Pascoli, S. (2016). Design of flexible polyimide electrodes for a Wireless Infrared EEG Recorder for chicken embryos. In 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. USA.

5. Paonessa, S., Barbani, N., Bellotti, E., Rocchietti, E. C., Giachino, C., Cristallini, C. (2016) A new hybrid bioartificial shape memory hydrogel for the anastomosis of human hollow organs. In 10th World Biomaterials Congress, May 2016. 6. E. Bellotti, N. Barbani, M.G. Cascone, S. Paonessa, C. Cristallini (2016) New

folic acid-functionalized acrylate nanoparticles for an active targeting of DNA towards cancer cell, In 10th World Biomaterials Congress, May 2016

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CHAPTER

1

Introduction

1.1

Introduction

This first chapter is intended to be an introduction, from many points of view, of the work carried out for this thesis. In the section 1.2 the Electroencephalography (EEG) and Electrocorticography (ECoG) diagnostic methods are described from an engineer-ing point of view, highlightengineer-ing the main characteristics of the signals of interest and the requirements of the acquisition system.

In section 1.3, a schematic block diagram of a generic EEG machine is described, together with the description of the main building blocks.

In section 1.4, an overview of the state-of-art electrodes used to acquire the electrical signals in EEG or ECoG diagnostic tools is presented.

A detailed overview of wireless EEG and ECoG systems is analyzed in section 1.5, highlighting the advantages of such systems and the different architectures that are proposed in the literature.

And, finally, in section 1.6, an overview of functionalities and a detailed description of the used inkjet printer is described.

1.2

Brain monitoring using invasive and non-invasive recording devices

1.2.1 Electroencephalography (EEG)

The electroencephalography (EEG) is a medical non-invasive recording technique that collects the spontaneous electrical signal generated by neural cells1on the brain cortex. In fact, neuron firing produces spontaneously electrical impulses, which are oscillatory waves, with very low amplitude, typically in the order of 10 to 100µV. This signal,

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that diffuses through the head, can be detected by contact electrodes that are placed on the scalp surface. The signal that can be measured is then the sum of the activity of several neurons, since it is not possible to measure a single cell response because of poor spatial resolution.

Brief history of EEG

The first recording of bioelectrical neural signals was performed by Richard Caton in 1875, when he published experimental results conducted on different animals (mainly on rabbits and monkeys) using bare electrodes on the surface of the animal skull and a galvanometer to measure the electrical currents. Then, after him, many other scientists have performed similar experiments on different animals.

In 1924, Hans Berger was the first to measure and record electrical neural signals on humans. As first approach, he used silver wires as electrodes and placed them under the patient scalp, one at the front and one at the back. Like in the Caton experiments, also in this case, a galvanometer was used as measuring device. Then he switched to silver foil electrodes which were kept in the correct position on the patient head by a rubber bandage. The recording of the EEG results consisted of a photograph taken by an assistant, and shown in Fig.1.1.

Figure 1.1: An early EEG recording done by Berger

Using the EEG, he was the first to observe and describe the temporal patterns of dif-ferent electrical waves present in the healthy and sick brain. In particular, he identified a specific rhythm of the brain called “the Berger wave”, which has now been renamed and is known as alpha rhythm, and the absence of it, called “alpha blockade,” which is now known as beta waves.

EEG in our days

Nowadays, the EEG is commonly used as a diagnostic non-invasive and inexpensive method to analyze, study and assess various mental states, the neural activity of patients with neurological diseases2_{and sleep state disorders [1].}

In fact, the EEG is generally used to diagnose epilepsy, where the EEG readings show abnormalities, sleep disorders, coma, encephalopathies and brain death.

Furthermore, the EEG analysis is also applied in neuroscience, in cognitive science and in psychology to study specific cognitive activities associated with various brain lobes [2]. The EEG has high temporal resolution, of the order of milliseconds, but a poor spatial resolution and cannot be used to study clinical cases that require high spatial resolution.

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1.2.2 Characterization of EEG signal

The EEG signal is defined by frequency, amplitude and shape. When electrodes are placed on the scalp surface, the amplitude varies typically between 10 − 100µV, and the bandwidth varies between 1 and 50 Hz. Depending on the frequency, EEG waveforms are classified in four frequency bands, called:

• delta (δ) (0.1 − 4Hz) • theta (θ) (4 − 8Hz) • alpha (α) (8 − 13Hz) • beta (β) (13 − 30Hz)

Figure 1.2: Example of EEG waveform components [3]

The alpha waves, generally found in adults, are measured on the occipital and pari-etal region of the brain. Subjects are awake but relaxed with the eyes closed. They represent the activity of the white matter of the brain.

The beta waves are measured over the parietal and frontal lobes. They are con-nected to behavior, actions and to the five senses (what we see, touch, hear, smell and taste). These waveforms are detected during the conscious state (i.e. problem-solving, decision making).

The delta waves are detected from infant and sleeping adults in all stages of the sleep. This waveform is the largest in amplitude and the one with the lowest frequency. Delta waves are abnormal for adults in the wake state.

The theta waves are detected on children and sleeping adults and are related to sub-conscious activity [3].

The waveform shape changes with age and with the wake or sleep state, as shown in Fig. 1.3.

The sleep phase could be divided into two phases: rapid eye movement sleep (REM) and non-rapid eye movement sleep (NREM). The NREM stage could be also subdi-vided into stage I, stage II, stage III and stage IV.

During the REM phase, the subject dreams and activates eye movements, which are detected by the EEG. In deep sleep (stage III and IV of NREM state), the EEG

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Figure 1.3: Difference in the awake and sleep EEG waveform [3]

waveform is characterized by slow and wide oscillations, called delta waves, so this sleep stage is also known as slow-wave sleep (SWS). During human sleep, the NREM phase and REM phase alternate with a period of about 90min, as shown in Fig.1.4 [4].

Figure 1.4: Sleep stages in humans. Sleep in humans and in other mammals is divided into different sleep stages, mainly into slow wave sleep (SWS) which represents the deepest form of non-rapid eye movement (NREM) sleep and REM sleep [4]

1.2.3 Electrocorticography (ECoG)

Electrocorticography (ECoG) is a medical invasive recording technique that reads the electrical signal generated by neural cells (neurons) by removing the skull layer from the head. Unlike the EEG, a surgical procedure is necessary to place electrodes on the cerebral cortex. The recorded signal is detected from dura without propagation through the skin and skull layer. So, the detected signal has a better spatial resolution and higher SNR.

Since the electrodes of ECoG are placed below the skull, at a closer proximity with the cortex in the skull, ECoG electrical signals have reduced deflective effects and less

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dampening, compared with the electrical signals captured in the EEG or magnetoen-cephalography (MEG) (Fig. 1.5). Nevertheless, since the implanting of the electrodes requires a surgical procedure, this could lead to medical complications, like the possi-bility of infections, traumatic operation or risk to damage the brain cortex. The latter could also be caused by movements in the electrode-cortex interface.

The advantages of using closer proximity electrodes are higher Signal-to-Noise Ra-tio (SNR), particularly at higher frequencies, better spaRa-tiotemporal resoluRa-tion and they are less prone to artifacts. Due to those advantages, ECoG is able to record frequen-cies higher than the gamma frequency (above 30Hz), so that the ECoG provides higher accuracy and shorter training times, which are more evident when it is compared with EEG for external robotic control [2].

Furthermore, in the case of epileptic patients, the spatial precision of the ECoG recorded signal is fundamental to detect the source of the disease and to better under-stand the neural communications and links inside the brain.

Figure 1.5: Schematic diagram of electrode position for EEG and ECoG recording.

1.3

EEG and ECoG recording devices

The brain is the most complex organ of our body, 1011neurons and glial cells allow to transfer information by means of electrical signals to action potentials, and by means of chemical signals to the neurotransmitters. To understand and study the neural func-tionality, sleep states and disorders, and several problems of the brain, neuron activity can be detected and studied using different neuroimaging methods with different spa-tial and temporal resolutions (Fig.1.6): sensors without contact to the body, such as functional magnetic resonance (fMRI) or magnetoencephalography (MEG); sensors in contact with the body using electrodes on the surface of the scalp with an EEG system or on the surface of the dura with the ECoG systems.

Thanks to low cost, high temporal resolution, ease of maintenance and real-time data response, the most used devices for the investigation of the neural functionality of sleep states are the EEG and ECoG recording devices. The block diagram of a general recording system for the detection of neural activity is shown in Fig.1.7:

The EEG system has an excellent time resolution (few milliseconds) and excellent affordability. The device response is fast enough to detect high-frequency neural activ-ity. The most relevant advantages are the non-invasiveness of the measurement, because electrodes are placed on the head surface, and the easiness of use. A main disadvantage is due to poor spatial resolution, the neural response detected is generated by the

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syn-Figure 1.6: Spatiotemporal limitations of existing neurotechnologies. The horizontal and vertical solid lines represent resolution in time and space, respectively, whereas the extent of the rectangular shade represents the spatiotemporal span of each neurotechnology. ECoG, electrocorticography; EEG, electroencephalograghy; fMRI, functional MRI; LPF, local field potential; MEG, magnetoen-cephalography; PET, positron emission tomography [5].

Figure 1.7: EEG and ECoG recording device block diagram

chronous activity of thousands of cortical neurons, and in some pathological cases (e.g. epileptic patients) in which the precision of the recorded information is fundamental to better understand the neural communication inside the brain, the spatial resolution is not enough.

In this case, it is better to use an ECoG system. Unlike the EEG system, the ECoG system has an accurate spatial resolution, due to different types of electrodes used and their positioning (inside the dura matter surface), and consequently a better SNR. On the other hand, this neural analysis is invasive, and a surgical procedure is necessary to position the electrodes.

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Electrodes

In the nervous system, a large number of neurons generate and transmit the electro-physiological signal to communicate between neurons and brain regions [5]. Neurons produce an electrical activity that can be detected using electrodes placed on the brain surface or inside the brain, depending on the type of signal to be analyzed.

Electrodes are the interface between the biopotentials to be detected and the system used to acquire, analyze and display signals. Different types of electrodes are available, which typically are: disposable (Ag-Ag/Cl disks), reusable disc (gold, silver, stainless steel), headbands, electrode caps and needle electrodes.

Electrodes can be placed on the brain surface (non-invasive electrodes) or inside the brain (invasive electrodes) in order to have access to different forms of neural informa-tion. Signal amplitude detected and spatial resolution obtained is different.

Amplifiers and filters

The neural signal detected from the scalp is typically small, usually between 10 and 100µVpp(50µVppM ax for adults). To analyze the signal and to make the signal

compat-ible with devices such as displays or recorders, it is necessary to amplify and to filter it.

The input amplifiers for neurological signals and biopotentials have to satisfy some requirements [6]:

• the amplifier operation and the physiological process must develop separately, without interference;

• the signal waveform detected should not be altered;

• patients and users have to be protected from electrical shock caused by an incor-rect usage or damage of the amplifier.

The detected signal consists of the desired neural signal, undesired other physio-logical signals (interference from ocular, muscular respiratory and cardiac activity), interference caused by the power supply, interferences caused by the interface elec-trode/brain, subject movements and noise. The design of the biopotential amplifier and of the filter chain have to be such as to allow to extract and analyze in the post-processing stage only the neural signal without additional components that are not part of the original signal.

A/D converter

The A/D converter in the EEG chain is the block that converts the analog signals, com-ing from the amplifier, to digital signals that can be easily plotted and stored by means of a computer. The channels of each analog signal are continuously sampled at a fixed time interval (sampling interval) and then each sample is converted into a digital word. The number of bits of each word depends on the needed resolution. Normally, the abil-ity to resolve 0.5µV is recommended and achieve this with the usual dynamic range an A/D converter with at least 12 bits is necessary3_.

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The sampling frequency, which is the reciprocal of the sampling interval, should comply with the Nyquist theorem, so it should be at least twice the maximum frequency contained in the input signal, otherwise aliasing occurs. In practice, to avoid aliasing, the input signal is filtered with a band-pass filter, to ensure that the maximum frequency of the input signal is always lower the half of the sampling frequency, and to eliminate the DC components of the EEG signal, which gives no information. Normally, the band-pass filter has a lower cut-off frequency in the range of 0.1 − 0.7Hz.

Recording device

The recording device stores and displays the EEG pattern. In the past, a paper sheet sliding at constant speed was used, together with actuators connected to writing pens, while nowadays it is usually a digital computer.

Once the digital words that come from the A/D converter reach the computer, they are stored in the memory together with a timestamp. Then, upon request, the computer is able to plot the EEG waveforms on the display or print them on paper using the saved timestamps. Furthermore, post-processing of the acquired data can be easily performed.

Thus, using a computer instead of a paper sheet has many advantages: • It is possible to store the data for a lifetime

• The cost and the area occupation of the storage hardware is now negligible

1.4

State of the art of Electrodes for EEG/ECoG Recorder

In the nervous system, many neurons generate and transmit the electrophysiological signal to communicate between neurons and brain regions. Neural activity can be de-tected placing electrodes on the brain surface or inside the brain, according to the type of the signal to be studied and analyzed. During the years different types of electrodes have been developed, starting from metal microwires (Fig.1.8).

A different type of recording electrodes has been developed to access different forms of neural information through varying levels of invasiveness Fig.1.9.

The main difference between electrodes placed outside or inside the head is the SNR of the neural signal detected. The electrodes have a fundamental role in the performance of the neural recording device since they take signals from neural cells and feed the amplifier. The choice and the use of the correct electrodes is very important to have a good SNR and to have high-quality data for post-processing analysis.

Different types of electrodes are used [8]:

• non-invasive electrodes are primarily used to detect EEG signal from the brain surface

• invasive electrodes are used to measure EEG or ECoG signals from the cortical surface (placed under or below the dura mater surface or within the cortex).

1.4.1 Non-invasive electrodes

Neural activity is normally detected by using non-invasive electrodes connected to the EEG acquisition system. Neural recording is performed using electrodes that are placed

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Figure 1.8: Novel electrode technologies for neural recordings. On the left, conventional electrodes technologies for in vivo neural recordings are shown above the timeline, whereas key neuroscience discoveries and breakthroughs enabled by these technologies are shown below the timeline. On the right, the recent developments of neural recording electrode technologies is summarized in three categories for neural probes with high spatial integration, long-term temporal stability and multi-functional integration. ECoG, electrocorticography; LEDs, light-emitting diodes [5].

Figure 1.9: Positioning of neural recording electrodes. (A) EEG activity is recorded non-invasively with electrodes placed on the scalp. (B) ECoG electrodes are placed either outside the dura mater (epidu-ral ECoG) or under the dura mater (subdu(epidu-ral ECoG) and can record neu(epidu-ral activity on the cortical surface. (C) Intracortical microelectrodes penetrate the cortex and can record action potentials from individual or small populations of neurons within the cortex [7].

directly on the scalp surface. The non-invasive electrodes can be classified into three main types: wet, dry and non-contact.

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Wet electrodes

The wet electrodes operate interposing conductive gel between the electrode pad and the head surface in order to decrease the skin impedance.

Wet electrodes are made with different metal materials, like gold, platinum, Ag/AgCl, stainless steel or saline-based electrodes and can be disposable or reusable. To have a good signal detected, the interface electrode/gel/head has to be stable and reliable during the entire neural signal measurement. Typical values of the electrode-skin impedance are in the range of 150kΩ − 200kΩ before the gel application and in the range of 10kΩ − 50kΩ after the gel application [9].

The disposable electrodes are the cheapest, the simplest to use and they are the most used in clinical application. They are usually Ag/AgCl electrodes, and they are used to detect not only the neural signal but also other biopotentials. The disadvantage of this electrode is due to the type of pad used. The pad is usually round and adhesive, as shown in Fig.1.10, and it is not easy to place and to keep it in the correct position over the time of the measurement. The principal problem is the presence of the hair in the scalp that reduces the perfect adhesion between the interface electrode/head.

Figure 1.10: Example of a commercial round electrode used for EEG and ECG applications

The reusable electrodes are smaller than the disposable electrodes. They are usually Ag/AgCl or gold-platinum electrodes. The adhesion between the electrode and head is better because the adhesive matter used is more resistant and permits stability and long-term acquisition during the EEG exam.

The saline-based electrodes are made up of a saline sponge and an electrode housing. The sponge, placed on the head surface, should be kept wet during the whole exam. Depending on the type of exam, if it is necessary to do multi-channel recordings with a large number of electrodes, an EEG cup is used instead of single electrodes as described above. Typically, the EEG cup includes 21 different electrodes placed according to the international 10-20 system. In this way, a stable and reliable measurement can be conducted. Different cup sizes are available depending on the size of the patient’s head.

Dry electrodes

Wet electrodes have the big disadvantage of increasing interference caused by hair and adhesive matter. In recent years, to reduce this type of problem, dry electrodes have been developed. These types of electrode are based on microelectrode-mechanical sys-tems (MEMS). Wet electrodes are considered the golden standard and the operation of dry electrodes must be carefully evaluated and validated before using them [10].

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In the literature, dry electrodes are typically spiky-array, named sometimes comb-shaped. They are formed of microscale pillars and enter directly into the scalp, inside the epidermis of the head surface. Spiky-array is developed in nanometer, micrometer and millimeter-scale and they are made of different materials such as silicon, carbon nanotubes, copper titanium or conductive polymers. Some of these technologies are presented and briefly described below.

Active comb-shaped dry electrode, made of copper and placed in contact with the skin through the hair layer, is proposed by Huang et al. [11]. A picture of such elec-trodes is shown in Fig. 1.11 High copper conductivity reduces signal attenuation of biopotentials and minimizes the intrinsic noise of the electrode. These electrodes can detect EEG signals (alpha rhythm) without applying high pressure.

Figure 1.11: Dry electrode proposed by Huang et al. [11]

Flexible polymer dry electrodes made with ethylene propylene diene monomer rub-ber (EPDM) containing various additives for optimum conductivity are proposed by Chen et al. [12]. These electrodes, unlike rigid metal comb-array, offer high user com-fort, since they are made of rubber, flexibility and ease of fabrication, reducing discom-fort, pain and skin irritation.

Multiwalled carbon nanotube arrays are proposed by Ruffini et al. [13] as dry elec-trodes. These electrodes are placed in contact with the stratum corneum of the head. Due to the minuscule size of the spikes (the nanotube diameter is 50nm), these elec-trodes result in a comfortable and pain-free interface. A local amplification is imple-mented to improve the detected signal. A picture of the electrodes proposed by Ruffini et al. in [13] is shown in Fig. 1.12.

Non-contact electrodes

Non-contact dry electrodes are electrodes capacitively coupled to the skin and measure neural signals with a spacing from the head skin. These electrodes give a very small signal amplitude and are very susceptible to motion artifacts since motion changes the skin-electrode capacity. A non-contact dry electrode is proposed by Sullivan et al. [14]. They proposed an integrated low-noise system based on a sensor combining amplifica-tion, filtering and analog-to-digital conversion, and operating up to a distance of 3nm from the skin. A photo of the proposed electrode is shown in Fig. 1.13.

Another non-contact electrode is proposed by Chi et al. in [15]. Like the Sullivan system, Chi proposes a complete system where, on top of the capacitive electrodes, the

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Figure 1.12: Electrode prototype design by Ruffini et al.: a CNT array grown on a conductive substrate is in contact with the Stratum Corneum. The signals are locally amplified for downstream sampling [13].

Figure 1.13: Non-contact electrode proposed by Sullivan et al. Photograph of assembled circuit. (Left) The top side of the teo-board structure with components. (Right) The bottom side of the bottom PCB. The metal plate on the bottom is the sensing element, which is covered by solder mask [14].

analog filtering and a 16-bit ADC are integrated. A photo of this system is shown in Fig. 1.14.

Figure 1.14: Photograph of the realized wired network of non-contact sensors with daisy chain digital output proposed by Chi et al. [15]

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1.4.2 Invasive Electrodes

Invasive electrodes, which are known as implantable electrodes, are electrodes that should be surgically implanted on the surface of the dura or cortex and should penetrate the brain. In this way, it is possible to detect signals from an individual neuron or group of neurons. Invasive EEG electrodes can, in turn, be subdivided into two types of electrodes subcategories: penetrating cortical electrodes and non-penetrating cortical electrodes.

Penetrating cortical electrodes

Penetrating cortical electrodes could be divided in microwire and multi-electrode ar-rays (MEAs). Since 1950 different metal microwires are used to detect and to record neural activity [16]. Typically used metal microwires are made of platinum, iridium, stainless steel, glass-insulated platinum-iridium alloy, gold, silver and alloys of conduc-tive metals. When the metal wires are used for long-time acquisition, biocompatibility and chronic reaction have to be valued. Problems as neural tissue inflammation and brain damage can arise if the used metal is not completely biocompatible or if an exact match between the rigidity of the metal wire and the softness of the brain tissue is not present. Based on their experimental data and other results, Dymond and al. reported a classification of metal wires based on their toxicity for brain tissue [17]. Typical multi-electrode arrays are made using more metal microwires composed into multiple plates or shanks. They are used to obtain information from different brain regions and to study different properties of neural networks [18]. Thanks to the progress in pho-tolithographic technologies, the fabrication process of MEAs has been simplified over time. Actually, smaller and denser structures with precise electrodes placement could be made and evaluated. Commercially, MEAs are made of inorganic semiconductors, like silicon, with a footprint small enough to reduce neural damage and enhance bio-compatibility.

Moxon et al. introduced MEAs made using ceramic-based multisite electrodes [19] instead of silicon-based.

These ceramic-MEAs have several advantages. First, these electrodes are rigid, re-ducing the likelihood of buckling during surgical implantation. Then, the strength of the ceramic substrates is greater than similar size probes made of silicon. Finally, the tapered geometry offers an advantage over constant width arrays.

All these types of MEAs have a problem due to the rigidity of electrodes used com-pared to the softness of brain tissue. To resolve and minimize this mismatch, several soft electrodes made of polymeric material have been proposed in the literature.

Typical polymeric materials used are based on Parilene-C, polyimide (PI), poly-dimethylsiloxane (PDMS), SU-8 and liquid crystal polymer.

Non-penetrating cortical electrodes

Non-penetrating cortical electrodes are usually flat-shaped electrodes. Epicranial EEG, epidural ECoG and epicortical ECoG belong to this electrode category. Advances in micromechanical system technologies and in material science have permitted us to discover and to use new electrode materials with high biocompatibility and flexibil-ity compared to traditional electrodes made with rigid materials. Flexibles polymeric

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electrodes, flexible enough to wrap around the curvilinear shape of the brain, have been developed in recent years.

Hollenberg et al. propose [20] a microfabricate flexible electrode arrays developed on a thin Kapton substrate. The array is formed of 64 gold electrodes, each 150 µm in diameter on a 750 µm spaced 8 x 8 grid. The proposed electrode array record evoked response signal to create topographical maps of the rats cortical surface. The signal detected has execellent stability over a period of 8 h.

Toda et al. propose [21] a flexible multichannel electrode array with mesh-form based on Parilene-C and with a 6 x 6 gold electrode array with 1mm interval. This electrode-mesh was placed for 2 weeks on the dura surface of rats without having any signal degradation.

Chou et al. propose [22] a different flexible multichannel electrode array based on Parilene-C. In his work, an array of 4 x 4 electrodes with a pitch of 750µm is presented and tested. A picture of this electrode array is shown in Fig. 1.15.

Figure 1.15: Photograph of parilene-c based non-penetrating cortical electrodes proposed by Chou et al. [22]

1.5

State of the art of Wireless EEG/ECoG Recorders

Most of the EEG/ECoG systems used to investigate brain function in clinical or diag-nostic applications have a wired connection for communication between electrodes/ac-quisition systems and data transmission/signal processing.

The wired systems are generally heavy and bulky, and they can be used only by medical personnel. Usually, these devices are not portable, restricting their use only for short analysis and in specific environments, preventing the use by the patient in ordinary working or living environments.

The development of miniaturized and portable wireless EEG/ECoG systems is de-sirable if it is necessary and important to evaluate the brain function not only during a diagnostic exam, but for long-term acquisition or in daily operational environments (for example at work or at home) or in the research field. [23].

Wireless transmission technology includes different type of protocols, as Bluetooth [24], custom radio frequency (RF) or infrared link.

The use of a wireless neural system has some advantages that must be considered when choosing how to monitor and to collect neuron activity. A wireless neural system can reduce installation complexity, bulk wires, EEG system size and weight. Moreover, it can provide users with more freedom of posture and movement, so that they can

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perform their routine tasks. Finally, it is designed to have a low-power consumption, miniature signal acquisition and conditioning circuits, in order to maximize portability and to make possible long-term field operations.

In the literature, several wireless EEG/ECoG systems that use single or more chan-nels have been described and some of them will be proposed below.

Lapray et al. have developed a telemetric EEG recorder used to detect brain states (wakefulness, slow-wave sleep and under isoflurane anesthesia) and tested it on the brain of rats [25].

The proposed system is shown in Fig. 1.16 and is based on an implantable transmit-ter which communicates via radio link with a receiver.

Figure 1.16: Schematic illustration of the main components of the telemetric system proposed by Lapray et al. The recording electrodes are implanted on the cortical surface and connected to a transmitter placed in the abdominal cavity of the rat. The transmitter is switched ON/OFF by the receiver. The recorded signal is amplified and digitized by the transmitter. The data are transferred from the receiver to a computer via a USB connection and can be visualized on-line with the software. The animal behavior is synchronously recorded with a video camera and movies are stored on the PC [25].

The receiver is connected to a laptop via the USB interface and the data are pro-cessed and displayed on the laptop. The main advantages of this system are the follow-ing: it is inexpensive, portable and reusable, it acquires and sends data to the laptop for 4-5 weeks and it works up to a distance of 3 meters.

The electrodes used by Lapray are three stainless-steel screws placed on the skull. Those electrodes are soldered to the leads and slipped under the skin from the head to the belly, where the transmitter is placed. To detect the EEG signal, this system uses only 3 electrodes: the recording electrode placed above the somatosensory cortex, the ground and the reference electrodes placed above the cerebellum. After 2 weeks, the transmitter can be extracted from the rat skull and reused several times. A photo of the transmitter is shown in Fig. 1.17.

Chang et al. described an implantable EEG system that can monitor neural activity in rats for 8 weeks based on radio-frequency (RF) transmission. This system permits long-term and continuous monitoring of the EEG signals. The target of his work was to study epilepsy in freely moving animals [26].

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Figure 1.17: Photograph of the telemetric device proposed by Lapray et al. [25]

The system, shown in Fig. 1.18, is composed by a transmitter implanted beneath the animal’s skin, containing the transmitting antenna (made of a loop of stranded stainless steel wire encased in a silicone tube), two metal electrodes (made by two stainless steel springs coated with silicone), a battery and the needed electronic components.

Figure 1.18: Schematic of the main components of the telemetric system proposed by Chang et al. Four Faraday cages are connected via an antenna combiner to the data receiver and then to a LWDAQ driver which connects via the Internet to a computer [26].

The rat is placed in a Faraday cage. To read data from the transmitter, a receiving antenna is placed inside the cage. The transmission is based on a radio link communi-cation in the 905 − 915MHz band. A data receiver collects the data and sends them to a computer over the internet.

Xie et al. describe a wireless and portable ECoG system used to treat epileptic pa-tients, using flexible electrodes to detect neural signals [27]. In detail, the proposed

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system, shown in Fig. 1.19, is composed of an array of 32 flexible microelectrodes, a transmitter with a Bluetooth Low Energy (BLE) enabled microcontroller and a cell phone with Bluetooth capability which acts as the receiver. The electrodes are made

Figure 1.19: Block diagram of the ECoG system proposed by Xie et al. The red block is the ECoG electrode device with an array of 32 flexible microelectrodes, which are used to record ECoG signals of the brain or apply stimulation electrical signals to suppress epilepsy; the yellow block represents the electronic circuits which acquire and process ECoG signals; the blue block represents the mi-crocontroller unit which manages the ECoG system and communicates via a cell phone with a cloud system for data processing [27].

with gold stripes over a polyimide substrate and they are implanted to cover the left pri-mary sensory cortex of the rat brain. They are connected by means of a ZIF connector to the ECoG transmitter, which is a PCB with the analog front-end, the microcontroller and the BLE antenna. The display and the data storage are made by a cellphone and a Cloud system, who receives data through Bluetooth protocol. Using a cell phone and a cloud system, medical doctors will analyze the ECoG signals and make decisions about epilepsy treatment.

Di Pascoli et al. propose a wireless EEG/EMG recorder to detect neurological sig-nals from chicken embryos [28]. An overview of the proposed system is shown in Fig. 1.19.

The system is composed of a battery-powered transmitter which collects neural sig-nals by means of metal wire electrodes in contact with the chicken embryos brain. A radio frequency (RF) communication with a 4 MHz carrier is used to transfer data from the transmitter to a receiver. On the transmitter side, a loop antenna is integrated into one of the internal layers of the PCB, while, on the receiver side, two loop antennas are used to collect the modulated RF signal. The receiver is connected by means of a USB link to a computer to transfer data for storage and post-processing analysis.

The system is designed to acquire signals for a few days and, in order to preserve the battery energy, the transmitter can be turned off by applying an external magnetic

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Figure 1.20: Overview of the complete telemetry system, composed of the transmitter placed inside the egg, the antennas, a receiver connected by means of a USB link to a computer [28].

static field. The system has been tested in the lab with a sinusoidal signal test and on the field with a real chicken embryo.

1.6

Inkjet printer technology

Inkjet printing is one of the most employed material deposition techniques used in the fabrication of organic electronics. It is based on the ejection of a fixed quantity of ink from a chamber through a small hole, called nozzle. An electric field squeezes an ink droplet from the cartridge nozzle that fall on the target substrate below the hole and, by moving the hole or the substrate, it is possible to form various patterns [29].

Since ink is liquid, after printing is over an annealing process is necessary to make the solvent evaporate completely and to obtain a solid layer on the substrate.

1.6.1 Inkjet printer classification

The ejection of the ink droplet can be generated by various transducers and in different ways, as described in detail in several papers [30–33], but they can be grouped into 2 main groups:

• Continuous Inkjet Printing

• Drop-on-Demand Inkjet Printing (DoD)

Continuous Inkjet Printing

In the continuous inkjet printing technique, the ink, which comes from the tank, is continuously pumped into the nozzle as drops. The drop passes through a system of charging plates and high voltage deflection plates. As a result, the drop is electrically charged and then deflected to the proper direction on the substrate, forming the desired pattern on it. The more the droplet is charged, the more it is deflected. When a droplet is not necessary, it is not charged and it is collected by a recirculation system.

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A basic block diagram of the Continuous Inkjet Printing is shown in Fig. 1.21.

Pump Drop Generator

Ink supply Reservoir High Pressure Ink

Low Pressure Ink

Filter

Drop Charge Electrodes

High Voltage Deﬂec�on Electrodes Print Plane Print Drops Nozzle Print Data Drop Synchronizing Signal

Figure 1.21: Block diagram of a continuous inkjet printer

The main advantages of this technique are the high printing frequency (up to 80Hz) and jet velocity (up to 20m/s), while the main disadvantage is the spatial resolution since a resolution of maximum 100µm can be achieved. Furthermore, because of the recirculation process, the ink can be degraded because of the high contamination prob-ability.

Due to those advantages and disadvantages, this technique is mainly used in high-speed textile printing [30].

Drop-on-Demand Inkjet Printing

On the contrary, in the drop-on-demand inkjet printing, the drop ejection is not con-tinuous but occurs only when necessary. Therefore all the droplets ejected are directly deposited on the target substrate and form the desired pattern, without the need of charging plates, deflection plates and without recirculation system, so that the risk of ink contamination is reduced.

A basic block diagram of the functionality of a DoD printer is shown in Fig. 1.22 In the DoD Inkjet Printing, the droplet can be generated using or the temperature, known as Thermal DoD and based on the Joule effect, or using the piezoelectric effect, known as Piezoelectric DoD.

In the Thermal DoD, the transducer is simply a heater placed in the drop chamber. When the heater is activated, its temperature increases rapidly due to the Joule effect and, if the ink solvent is volatile, the ink starts to vaporize. A vapor bubble is generated, causing an abrupt pressure increase and the ink is forced through the nozzle. When the heater is deactivated, the temperature decreases and the vapor bubble vanishes: the ink forced outside is detached from the nozzle and a droplet is formed.

In the Piezoelectric DoD, the transducer is a piezoelectric crystal biased with a volt-age waveform. The crystal is kept slightly depressed in the standby phase, then, when the droplet has to be formed, it goes quickly in the neutral position (forming a depres-sion that draws ink from the ink tank) and then to its maximum deflection (increasing the pressure and ejecting the droplet from the nozzle).

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Print Plane Drop Generator

Nozzle Transducer

Piezo or Heater

Ink supply Reservoir Print Data

Figure 1.22: Block diagram of a Drop-on-Demand inkjet printer

In both cases, the type of printer and the nozzle size influence the ink requirements regarding its chemical and physical properties.

1.6.2 Inkjet printer components and parameters

Almost any inkjet printer used for material deposition can be seen as composed of 4 main parts (Fig. 1.23):

Print Carriage It is the carriage where the cartridge with the ink is inserted. It is the most important component of the inkjet printer since the fine control of its movement is a key factor that impacts the accuracy of the printing. Furthermore, it holds the nozzles and all the actuators that are needed to eject the ink. The ink container could have different shapes and sizes, depending on the available area on the print carriage. In some inkjet printers, the print carriage could include a camera that could be used to monitor and control the status of the printing and to do fine alignments using markers on the platen or on the substrate.

Drop Watcher It consists of a small pad and a camera. Here the ejected drops can be viewed before starting the real printing on the substrate, in order to optimize the printing parameters and improve the final result. This is a fundamental step that should be done every time before starting the printing, since every ink requires a fine calibration of the printing parameters.

Platen It is a movable metallic plane on which the substrate is placed. The substrate is held in the correct position by a vacuum system with several holes on the platen. If the substrate is too thick, an additional adhesive tape could be required to en-sure that it stays firmly in the correct position. The platen normally includes a temperature-controlled heater. It could be used to heat the substrate to a defined and controlled temperature to improve and optimize the printing process.

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Cleaning Station It consists of a cleaning pad and a small pressure tube. They are used to clean the nozzles, removing all the solid material or the residual ink which could obstruct nozzles, before starting the printing process and it could be required to redo it during the printing to ensure that all the nozzles are operating correctly with no obstructions.

1.6.3 DMS-2850 printer main features

The Inkjet printer used in this thesis is the Dimatix Materials Printer DMP-2850, a piezoelectric Drop-on-Demand printer from FUJIFILM Dimatix [34], shown in Fig. 1.23.

Figure 1.23: Fujifilm Dimatix Material Printer DMP-2850.

Below the main functionalities of this printer are described. The DMP-2850 printer is a Drop-on-Demand printer where the nozzle is activated by a piezoelectric actuator. The Print Cartridge includes 16 nozzles, placed on a single row, and the ink container. The parts making up the print cartridge are shown in Fig. 1.24. The ink container has a rectangular shape and can contain up to 1.5ml of ink and it is one-time user-fillable.

Figure 1.24: DMP-2850 cartridge components

On the Print Carriage of the DMP-2850 a camera is included. This camera could be used to control the status of the printing in real-time and to do alignments with existing structures when needed. In the datasheet, it is called fiducial camera.

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Furthermore, the fiducial camera could be used to perform also measurements on the printed structures.

The platen of the DMS-2850 allows the use of 8x11in or A4 size substrate. The maximum thickness of the substrate is 25mm. Moreover, the platen integrates a heater to heat the substrate, which allows to set its temperature between room temperature and 60◦C.

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CHAPTER

2

Wireless Infrared EEG/ECoG recorder for chicken

embryos

2.1

Introduction

The description and the interpretation of the sleep disorders is the major subject of sleep studies. The diagnostic method commonly used to study sleep stages and problems of sleep is based on the detection of brain activity using an EEG or ECoG recorder.

In this chapter, a wireless EEG/ECoG recorder to detect neurological signals from chicken embryos is presented. The recorder we have developed uses an InfraRed data link to communicate between the transmitter and the receiver and it was designed to detect biopotentials for chicken embryos starting from the 16th days of embryonic life. In section 2.2, both the developed transmitter and receiver, which are the compo-nents of the recorder, are described in detail. In section 2.2.1 the block diagram and a photograph of the transmitter are presented, while in section 2.2.2 the block diagram, a photograph of the receiver, and its key components are discussed.

Finally, in section 2.3, the lab validation results, obtained generating test sinusoidal signals at different frequencies in the band of interest are shown.

Furthermore, a complete measurement setup, consisting of the transmitter and the receiver is shown. The metal wires are used as electrodes, and surgery was performed to insert them on the embryo brain surface. We report a real EEG measurement acquired in vivoon chicken embryos.

2.2

Design of the proposed infrared EEG system

An important function of the human brain is to sleep. Sleep and sleep cycles are funda-mental for sensory system development in embryonic life and people, to preserve brain

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activity, to create long-term memory and for learning [35].

The first description of sleep stages and sleep cycles was made in 1957 by Dement and Kleitman. The description and the interpretation of dreams and sleep disorders were the major subjects of sleep studies. Still today, the development of the cycles of sleep and waking during embryonic life is an unanswered question. The diagnostic method mostly used to study sleep is based on detecting patterns of brain activity by means of an EEG or ECoG recorder.

The goal of this work was to design an EEG/ECoG system to acquire neurological signals during embryonic life to try to understand the origin of sleep and waking cycles. To study primarily sleep, animal models are used instead of humans. Usually, in the laboratory rats are used as animal models, but for our application, they are not useful for several reasons, the most important is that the embryo is not easily accessible. It has been shown that mammals and birds have the same sleep stages, each of which has its EEG pattern [4]. Exactly for this reason, in this study, we have used chicken embryos as animal models. Using chicken has many practical advantages: easiness of accessibility of chicken embryos and early stages of embryo development (21 days) are the most important.

The developed system was designed for the acquisition of real-time EEG and ECoG signals and the storage of the data on a PC for post-processing analysis. The neurolog-ical signals are detected from the brain of in-ovo chicken embryos.

The system includes 7 electrodes (six signal electrodes and one reference electrode), a transmitter and a receiver that communicate through an InfraRed (IR) data link. The main constraints of the transmitter are the size, weight, power consumption and place-ment during the signal acquisition.

Since the transmitter is battery operated, the transmitter power consumption has to be minimized to extend the battery operating time. The infrared data link has been chosen because the transmitter has to be placed in a PET machine, designed specifically for small animals.

Such a chamber consists of a cylinder with a diameter of 80 mm and about half a meter long. Using an IR data link instead of a radio frequency (RF) communication, commonly used in biomedical applications, involves a better compatibility with the environment of a PET scanner. Furthermore, IR radiation can be easily confined in a small space, reducing privacy issues, and could be generated simply by an IR LED or IR Laser. Since in this application a large angle of view is necessary, an IR LED has been chosen, where the angle of view is about 60◦, allowing easy alignment between transmitter and receiver.

2.2.1 Transmitter

The transmitter has been designed with the target of obtaining a small and low power electronic system. A block diagram of the transmitter is shown in Fig. 2.1 and a photograph of a fully assembled transmitter is shown in Fig. 2.2.

Six signal electrodes and one reference electrode, made with metal wires, are con-nected to the transmitter by means of a header connector. In detail, the electrodes are

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Figure 2.1: Block diagram of the infrared transmitter: six electrodes send data to amplifiers with high gain. The signal is sampled with a 16 bit ADC and fed to a microcontroller through SPI communica-tion. The processor sends data from the SPI port to a power transistor and an infrared (IR) emitting diode.

made from 38-gauge (0.1 mm diameter) Teflon-insulated gold-plated copper wire. Af-ter the electrode insertion, the egg and the transmitAf-ter are placed inside an incubator, with controlled temperature and humidity, in order to ensure the survival of the embryo. Two AA alkaline batteries connected in series supply power to the transmitter. The total supply voltage is 3 V and the battery package and transmitter are attached outside the eggshell, both inside the incubator.

Figure 2.2: Photo of the designed transmitter. In the top layer (above in the photo) we can see the two quad op-amps, the ADC and the programming connector, which can be disconnected after software download, in order to reduce size. The processor and the IR transmitting diode (small white square) are located in the bottom layer (below in the photo).

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The transmitter includes 6 signal channels and one reference conditioning front-end that removes the DC voltage present at the input, amplifies the signal and feeds the ADC.

The reference electrode applies to the brain a reference voltage equal to half of the battery voltage, obtained with a voltage divider and an op-amp buffer.

Each channel is anti-aliasing filtered, setting an upper cut-off frequency of 100 Hz, using a single operational amplifier in a quad package (LTC6078 provided from Linear Technologies), mounted in non-inverting configuration.

The filtered signals are then sampled by an eight-channel ADC converter (AD7689 from Analog Devices), of which only 6 channels are used, with a sampling rate of 200 Hz and a resolution of 16 bits. The ADC is then connected to an ATtiny88 micro-controller from Atmel through the SPI interface. Since the dynamic range of the EEG signal is about 60dB, in order to reduce the used bandwidth only 12 bits are transmitted and all the other bits are discarded.

The microcontroller takes the data stream from the 6 channels of the ADC and cre-ates a 128-bit packet, including ADC data together with the value of the system temper-ature (from the internal tempertemper-ature sensor of the microcontroller), the battery voltage, the timestamp and a checksum. Then the packet is encoded using the bi-phase mark-coding scheme (BMC) and transmitted with a data rate of 62.5 kbit/s. The transmission time of each packet is about 2 ms and is followed by a 3 ms pause before the next packet.

The BMC coding scheme has been chosen since it simplifies the clock recovery and is less prone to errors in communication in noisy environments. The only drawback of this scheme is that at least 2 microcontroller clock cycles are necessary for each transmitted bit.

The ATtiny88 firmware was written using C with some subroutines in assembly code for better efficiency.

The transmitter PCB layout and AVR firmware have been optimized to reduce over-all size, weight and power consumption. To reduce the PCB area even further, the programming connector could be easily removed after the microcontroller firmware upload, breaking the PCB at the breaking points placed on it.

2.2.2 Receiver

The transmitted IR signal is captured by a photodiode placed on the receiver. In Fig. 2.3 the receiver block diagram is shown.

It is made up of two different PCBs, one with the IR low noise analog front-end and the trans-impedance amplifiers, and one with the voltage amplifier and the microcon-troller. The signal between the 2 PCBs propagates through an SMA cable.

The optical signal from the transmitter is detected by an IR photodiode and then it is amplified by a chain of three amplifiers. The first amplifier is in the first PCB, while the other two are in the second one.

The solution with 2 different PCBs has been chosen to eliminate the crosstalk noise between the noisy microcontroller and the low noise IR front-end and to simplify the placement of the photodiode outside the incubator, near the IR diode.

The first PCB, shown at the bottom-left corner of Fig. 2.4, includes the photodi-ode and an operational amplifier in the trans-impedance amplifier configuration. The

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Figure 2.3: Block diagram of the receiver: the first board contains the photodiode used to detect the IR signal and a transimpedance amplifier (OPA627) used to amplify the signal and send data to a second board. Two other amplifiers (AD817 and AD600) amplify the signal, and send it to an ARM Cortex-M4 processor. A USB protocol or RS-232 can be used to send data to a PC.

OpAmp is an OPA627 supplied by Burr-Brown. This PCB is very small in size (33 x 38 mm2_{), simplifying its placement in the limited space of the PET gantry, which is}

a cylindrical space with an 80 mm diameter in the case of the preclinical unit used in these experiments, and ensuring a good received signal.

The second PCB, the large board shown in the center of Fig. 2.4, includes the two remaining voltage amplifiers, a microcontroller and the USB and RS-232 interfaces used to communicate with the PC.

The first amplifier is a 10 dB fixed gain amplifier (AD817 from Analog Devices) and the second one is a variable gain amplifier (AD600 from Analog Devices). The mi-crocontroller is an 80 MHz 32-bit ARM Cortex-M4 processor from Texas Instruments. It is a TM4C123GXL, included in the Tiva™C LaunchPad evaluation kit. The Texas Instruments evaluation kit is clearly visible in Fig. 2.4 (the red PCB mounted on top of the second PCB).

The gain of the second amplifier is digitally controlled by the microcontroller using the mean amplitude of the received signal and implementing an automatic gain control loop, as shown in the block diagram. The comparator is simply a microcontroller GPIO pin configured as Digital Input. The digital signal is then processed by the Cortex-M4 processor, which extracts the data stream from the BMC modulated signal, reformats the packet and sends the data to the PC. The communication from the Microcontroller to the PC can be either with a USB or an RS-232 connection. The receiver is equipped with both physical interfaces and can be programmed to communicate with the PC with either of them.

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Figure 2.4: Photograph of the developed receiver: the small board in the bottom left corner is the first PCB with the photodiode and the transimpedance amplifier; the large board at the center is the second PCB with the other amplifiers, the microcontroller and the PC communication interfaces.

2.3

Lab validation and experimental results

In Fig. 2.5 a picture is shown of the complete measurement setup mounted in the laboratory to test the system.

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The system was connected to a test signal generator, based on an FPGA prototype board, as shown in the bottom-left corner of Fig. 2.5 to verify the correct functionality of the complete system, including the IR link communication. The test signal genera-tor has been programmed to generate 6 different sinusoidal test signals and each signal feeds one different channel of the EEG transmitter. Each signal has a different fre-quency (0.5, 1, 3, 8, 20 and 50 Hz) and a fixed amplitude of 300 µV; those values have been chosen to be as close as possible to neurological signals.

The FPGA generates digital test signals using a PWM (pulse width modulation) modulators, one for each signal. The generated PWM signal have a clock signal of 80MHz, then six RC low pass filters (with 100Hz bandpass) are used to extract the sinusoidal signal from the PWM signal, one for each test signal.

Figure 2.6: (a) Oscilloscope snapshot of two complete transmitted (pink) and received (green) BMC packets. (b) A detailed view of first bits of a BMC packet.

In Fig. 2.6 an oscilloscope snapshot of the communication between transmitter and receiver is shown. Fig. 2.6a shows two complete packed exchanged between transmit-ter and receiver, while 2.6b shows a detailed view of the first bits of a packet, highlight-ing the correct functionality of the automatic gain control loop.

The received signals were filtered and analyzed in the frequency domain using MAT-LAB tool, to extract the signal frequency components and to evaluate the performances of the entire system, as the SNR, knowing the amplitude of the input test signals.

Then, the six test signals at different frequencies are applied to the system and the corresponding measurement results are shown in Fig. 2.7.

A noise test was performed terminating all inputs with 50 Ω resistors, in order to check the output signal when no input signal is present, and a noise floor of about 0.5 µV was estimated as a result of this test.

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Figure 2.7: Snapshot of the received test signals at six different frequencies, 0.5, 1, 3, 8, 20 and 50 Hz and amplitude of 300 µV peak-to-peak. Each channel receives a sinusoidal signal at a different frequency.

Experimental setup and results of in-ovo measurements

The recorder was tested also in-vivo with a chicken embryo. Photos of this test are shown in Fig. 2.9 and Fig. 2.8.

Figure 2.8: Experimental setup: inside the incubator, the IR transmitter is attached to the eggshell. The transmitter collects signals from the embryo head through metal wires (visible near the transmitter edge). The first PCB with the IR photodiode is taped to a glass window of the incubator.

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Figure 2.9: Surgical procedure: photograph of chicken embryo after the insertion of the electrodes in the brain.

First, a surgical procedure was performed to implant electrodes on the chicken dura surface. Starting from the 16th day, the embryo brain is ready and developed, and it is possible to open the head to place electrodes inside the dura.

Electrodes are implanted for six days, because usually, hatching of the egg occurs after 21 days of incubation. In detail, to implant electrodes on the brain, a small open-ing was made on the top of the egg skull. After the openopen-ing, the chicken head was extracted seven small holes were made in the specific position of the brain to insert metal electrodes. After the insertion, metal wires are glued in the position to hold them in place and to prevent them from stripping off over time.

To guarantee the survival of the embryo, the egg was placed inside an incubator with controlled humidity and temperature to reproduce the embryonic field. The transmitter and its power supply were kept in the incubator. The first PCB with the photodiode was taped to the transparent glass window of the incubator. The photodiode is placed in front of the infrared diode to allow communication and data transfer (Fig. 2.8).

In this test, seven thin metal wires have been used as electrodes and they are clearly visible in Fig. 2.8, close to the transmitter. These electrodes are made from 38-gauge (0.1 mm diameter) Teflon-insulated gold-plated copper wire.

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was used to connect the AA batteries used as power supply for the transmitter.

Data was acquired by the receiver and then post-processed using a PC. An excerpt of four channels of the collected signal from the chicken brain is shown in Fig. 2.10.

Collection and recording of brain signals in chicken embryos

C

OLLECTION AND RECODING OF BRAIN SIGNALS IN

CHICKEN EMBRYOS

Ringraziamenti

I

Summary

S

Sommario

U

List of publications

Contents

CHAPTER

1

Introduction

1.1

1.2

1.3

1.4

1.5

1.6

CHAPTER

2

Wireless Infrared EEG/ECoG recorder for chicken

embryos

2.1

2.2

2.3