ES2548794B1 - SYSTEM AND METHOD OF ACQUISITION AND TRANSFER OF NEURONAL ACTIVITY - Google Patents

Abstract

Neural activity acquisition and transfer system (1) comprising at least a plurality of bioelectric sensors (20,000), a wireless transceiver (30,000), a communications node (10,000) connected between the plurality of bioelectric sensors (20,000) and the wireless transceiver (30000), and a plurality of intracranial electrodes (60000), such that the communications node (10000) is configured to transmit data bi-directionally between the plurality of bioelectric sensors (20000) and the wireless transceiver (30000), so that in the sense of data transmission from the wireless transceiver (30000) to the bioelectric sensors (20000), the communications node (10000), manages a parameter configuration, a calibration and a mode of operation of the bioelectric sensors (20000 ) and, in the sense of data transmission from the bioelectric sensors (20000) to the wireless transceiver (30000), collect, be ia and forms neuronal information of a neuronal signal captured by the plurality of bioelectric sensors.

Description

DESCRIPTION

System and method of acquisition and transfer of neuronal activity

OBJECT OF THE INVENTION

The object of the present invention relates to a communications node, comprised in a system for the acquisition and transfer of neuronal activity, configured to transmit data bi-directionally between a plurality of bioelectric sensors and a wireless transceiver, both equally included in said system. .

In a sense of communications, the communications node manages the configuration of parameters and the mode of operation of the plurality of bioelectric sensors and, in the opposite direction, collects, would be and shape the neuronal activity captured by the plurality of bioelectric sensors so that it can be broadcast through the wireless transceiver.

Additionally, the communications node offers two modes of transmission: in one case, the complete neuronal activity is captured, captured and digitized by a selection of 15 among the plurality of bioelectric sensors; otherwise, information relating to the neuronal action potentials detected and characterized by the plurality of bioelectric sensors as a whole is transferred.

With a view to reducing the transmission bandwidth and thus reducing the total power consumption of the system, the transmission of information related to the neuronal action potentials is done based on events, so that information is only transferred from a sensor bioelectric in the event that said sensor verifies the appearance of a potential for neuronal action.

 25

The method associated with the transfer of data between the plurality of said bioelectric sensors and the wireless transceiver of the system for the acquisition and transfer of neuronal activity is also described.

Find special application in the field of physical technology industry and more, 30 specifically, in the field of information and communications technologies applied to bioengineering.

TECHNICAL PROBLEM TO BE RESOLVED AND BACKGROUND OF THE INVENTION

In recent years, new technological advances are allowing the monitoring of brain bioelectric signal from devices implanted in the patient. With these devices, spatial-temporal detail levels are achieved that are much higher than those attainable by electroencephalography, thanks to the use of electrode arrays with separations of the order of tens of microns and bandwidths greater than kilohertz. 5 This increase in resolution is allowing the prescription of more focused treatments, the development of new therapeutic procedures or the implementation of brain-machine interfaces.

The use of implanted electrodes poses specific challenges to the acquisition and transfer systems of neuronal activity. In order to reduce the degradation of the captured signals, eliminate the possibility of infections or failures due to manipulation errors and simplify the surgical procedure of implantation, the use of cables from the brain to the outside of the body must be avoided. For this reason, in a preferred configuration, the acquisition system implanted together with the electrode array contains 15 bioelectric sensors as well as the array electrodes, and the transfer of information to or from an extracorporeal reader is performed wirelessly through a link that must overcome the attenuation imposed by the intermediate tissues.

A critical aspect in the implementation of this preferred configuration of the system of acquisition and transfer of neuronal activity is the use of design techniques with ultra-low power consumption and the use of information compression protocols to reduce the delivery rate of data through the wireless transceiver included in said system. In a preferred configuration of the compression protocol, said transceiver should only send that information that is clinically relevant and remain inactive as long as the captured signal does not show signs of interest.

This strategy aimed at the economics of resources is particularly evident when the acquisition and transfer system is intended for the interpretation of neuronal action potentials. In a preferred configuration of this type of systems, any bioelectric sensor remains in a latent state and, therefore, does not transmit any information to the outside, insofar as it does not detect a potential for neuronal action.

Obviously, the implementation of this preferred solution should not compromise the effectiveness of the therapeutic procedure or the brain-machine interface that makes use of the system for the acquisition and transfer of neuronal activity. Thus, in many applications, such as the one shown in the document “L. R. Hochberg, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature, vol. 442, p. 164, 2006, ”it is not enough to indicate the occurrence of a neuronal action potential, but it is also necessary to provide information regarding the spatio-temporal morphology of the action potentials with a view to their ordering and classification.

Existing neuronal acquisition systems do not fully satisfy all of the 10 previous objectives. For example, the state-of-the-art document with application number US 2010/0106041 A1, entitled "Systems and methods for multichannel wireless implantable neural recording" presents a wireless system for the acquisition of neuronal activity. However, the absence of preprocessing elements for reducing the wireless link data rate makes the power consumption of the implant high and requires the use of batteries which shortens the lifetime of the implant.

The state-of-the-art document with publication number US 2013/0090706 Al and entitled "Methods and associated neural prosthetic devices for bridging brain areas to improve function" also employs detectors of neuronal action potentials but data transmission does not It includes neither the morphological description of the action potential nor the compression due to events, so that the wireless transceiver remains active at all times, whether or not action potentials are detected. In none of the above cases the interface between the array of bioelectric sensors and the wireless transceiver is bidirectional. 25

Therefore, the present invention solves the aforementioned prior art problems, providing a system that has the following advantages:

 30

1. It has a wireless communication system that eliminates the cables from the cerebral cortex to the outside of the body.

2. There are pre-processing elements and compression protocols for reducing the data transmission rate of the wireless link, which allows ultra-low power consumption.

3. The interface between the array of bioelectric sensors and the wireless transceiver is bidirectional. 5

4. The wireless transceiver sends information that is clinically relevant and remains inactive as long as the captured signal does not show signs of interest.

5. Resource economics since every bioelectric sensor remains in a latent state and, therefore, does not transmit any information abroad, as long as it does not detect a potential for neuronal action. Thus, the activity of the acquisition and transfer system is determined by the events of clinical interest captured from the intracranial electrode array.

6. The event-based data compression mechanism does not compromise the effectiveness of the therapeutic procedure or of the brain-machine interface that makes use of the system for the acquisition and transfer of neuronal activity.

7. The occurrence of a neuronal action potential is indicated and information regarding the spatio-temporal morphology of the action potentials 20 with a view to their ordering and classification is provided.

8. Avoid using batteries.

DESCRIPTION OF THE INVENTION

The present invention relates to a neuronal activity acquisition and transfer system comprising:

- a plurality of bioelectric sensors,

- a wireless transceiver comprising a transmitter and a receiver,

- a communications node connected between the plurality of bioelectric sensors and the wireless transceiver, 30

- a plurality of intracranial electrodes, which capture neuronal activity, connected to the plurality of bioelectric sensors,

- a plurality of calibration units connected to the plurality of bioelectric sensors to adjust transfer characteristics of the plurality of bioelectric sensors, and

- a power management and clock synthesis module for communications node management, 5

such that:

- the communications node is configured to transmit data bidirectionally between the plurality of bioelectric sensors and the wireless transceiver so that:

or in the sense of data transmission from the wireless transceiver to the bioelectric sensors, the communications node manages a parameter configuration, a calibration and a mode of operation of the bioelectric sensors and,

or in the sense of data transmission from the bioelectric sensors to the wireless transceiver, it collects, would and forms neuronal information of a neuronal signal captured by the plurality of bioelectric sensors (20000).

Bioelectric sensors comprise: 20

- means for amplification and filtration of the neuronal signal captured from the intracranial electrodes,

- automatic calibration means of maximum voltage levels and a frequency band of the neuronal signal conditioned by the amplification and filtration means; 25

- means for converting the conditioned neuronal signal from the analog to the digital domain;

- means of compression of the captured neuronal information; Y

- means for temporary storage of said captured neural information.

 30

The communications node includes:

- a central processor that interprets and applies instructions received from the receiver, digitally processes the neural signals generated by the plurality of bioelectric sensors, and encodes the neural information collected from the plurality of bioelectric sensors for subsequent transmission through the wireless transceiver, and 5

- a plurality of signal routers that implement a data interface between the plurality of bioelectric sensors and the central processor, where each signal router is associated and electrically connected to a single bioelectric sensor.

 10

The core processor comprises:

 a coding and decoding module for exchanging information with the wireless transceiver;

 a module for receiving and classifying data for the interpretation of the 15 instructions received from the wireless transceiver;

 a memory module of instructions and parameters for storing the configuration of the system of acquisition and transfer of neuronal activity; Y

 a selection, configuration and acquisition module that serves as an interface with the signal routers that transfer the information generated by the plurality of 20 bioelectric sensors.

The coding and decoding module for exchanging information with the wireless transceiver:

- in a sense of communications, decodes a demodulated signal 25 provided by the receiver and comprises:

 a data synchronizer that aligns edges of the demodulated signal with a master clock signal generated by the power management and clock synthesis module; and 30

 a decoder that converts the format of said demodulated signal at the output of the data synchronizer to a binary code,

- in another sense of communications, it encodes output data provided by the central processor for later modulation by the transmitter and comprises:

 5

 a parallel-series converter that would be a signal with the output data after receiving an activation signal; Y

 an encoder that converts the serial signal with the output data to the signal format defined in the transmitter.

 10

The module for receiving and classifying data for the interpretation of the instructions received from the wireless transceiver includes:

 a data record that stores a DATA_DEC data frame of an instruction received by the decoder;

 a CRC validation module to verify the integrity of the data frame 15 DATA_DEC;

 a command identifier that analyzes the contents of the data record and generates a MODE digital vector representative of a mode of operation specified in the instruction received; Y

 a plurality of data reception status machines that are selectively enabled according to a value of the digital vector MODE.

The instructions and parameters memory module for storing the configuration of the neuronal activity acquisition and transfer system comprises:

 a stack of data in which they are dumped, overwriting previous data, a QERS qualifier, an application range and configuration parameters, if any, identified by the data reception status machines; Y

a non-volatile memory where values are stored by default where the data stack loads the values stored by default in non-volatile memory, from where they are transferred to the plurality of bioelectric sensors.

The selection, configuration and acquisition module that serves as an interface with the signal routers that transfer the information generated by the plurality of bioelectric sensors comprises:

 a selection and programming module; 5

 a plurality of data transmission status machines; Y

 a timing block for a generation of clock signals scaled in frequency from the master clock signal.

Signal routers comprise: 10

- a register in which the neuronal information provided by the plurality of bioelectric sensors is stored,

- an internal memory in which neuronal information is organized into fixed-length vectors, 15

- a control module that manages each signal router, and

- a module for the transfer of information comprising a parallel bus for orderly transmitting the fixed-length vectors to the data transmission status machines.

 twenty

The plurality of intracranial electrodes are selected from:

- sub-dura electrocorticographic electrodes,

- intracortical penetrating electrodes,

- a deep brain probe with sensing points, and

- a combination of the above. 25

The number of bioelectric sensors matches the number of intracranial electrodes and the number of signal routers.

The present invention also relates to a method of acquisition and transfer of neuronal activity that employs the previously defined system where:

The communications node includes:

- in the sense of data transmission from the wireless transceiver to the plurality of bioelectric sensors:

 activate, size and calibrate the plurality of bioelectric sensors, in accordance with instructions received from the wireless transceiver 5, for the capture and compression of neuronal activity,

 correct the deviations of analog amplification and filtering circuits included in the bioelectric sensors, and

- in the sense of data transmission from the plurality of bioelectric sensors 10 to the wireless transceiver:

 transfer the data captured by the plurality of bioelectric sensors to the wireless transceiver to externally monitor neuronal activity through an extracranial reader.

 fifteen

Bioelectric sensors, in the sense of data transmission from the wireless transceiver to the plurality of bioelectric sensors comprise two modes of operation:

 a Configuration Mode by which the operating parameters 20 of the bioelectric sensors are defined to capture and compress neuronal activity, and

 a Calibration Mode by which the deviations of the amplification and filtering means included in the bioelectric sensors are automatically corrected. 25

Bioelectric sensors, in the sense of data transmission from the plurality of bioelectric sensors to the wireless transceiver, comprise two modes of operation:

 30

- a Signal Tracking Mode: full, captured and digitized neuronal activity is transferred from the plurality of intracranial electrodes,

- a Data Compression Mode: neuronal activity is transferred relative to neuronal action potentials detected from the plurality of intracranial electrodes, where in said data compression mode, the communications node comprises embedded digital processing means based on events that cyclically examine the bioelectric sensors, 5 identifies those bioelectric sensors where a potential for neuronal action has been verified, forms a data frame for each bioelectric sensor where the event has occurred, and would be the data frames generated for its Subsequent wireless transmission through the wireless transceiver.

 10

Each mode of operation comprises a frame of input data to the central processor, where each frame of data comprises six fields:

- a first field that defines a preamble;

- a second field that defines the mode of operation of the bioelectric sensors 15;

- a third field that defines a range of application between bioelectric sensors;

- a fourth field that defines a particular qualifier for each mode of operation, which addresses parameter groupings or defines variables of execution of the modes of operation,

- a fifth field that defines a set of configuration parameters for the bioelectric sensors selected by said application range, and

- a sixth field that defines a cyclic redundancy code CRC.

 25

The core processor:

- interprets instructions received from the receiver,

- manages the modes of operation of the plurality of bioelectric sensors,

- orders, processes, formats and sends to the wireless transceiver the neural signals 30 transmitted by the plurality of bioelectric sensors and transferred to the communications node through the signal routers, and

- operates with a master clock signal provided by the power management and clock synthesis module.

The present invention also relates to a use of the neuronal activity acquisition and transfer system as the head of a man-machine interface where the system 5 comprises the acquisition of signals from a motor cortex.

BRIEF DESCRIPTION OF THE FIGURES

To complete the description and in order to help a better understanding of the 10 characteristics of the invention, this descriptive report is attached, as an integral part thereof, a set of drawings where, for illustrative and non-limiting purposes, represented the following:

Figure 1.- Shows the complete module diagram of the acquisition system and transfer of neuronal activity where the plurality of bioelectric sensors can be observed, the wireless transceiver comprising the transmitter and the receiver, and the communication node connected between the plurality of bioelectric sensors and the wireless transceiver.

 twenty

Figure 2.- It shows two alternative embodiments of the intracranial electrode array.

Figure 3.- Shows the different modules that comprise the central processor included in the communications node. 25

Figure 4.- Shows the DATA_DEC input data frames interpretable by the central processor to configure the neuronal activity acquisition and transfer system according to the MODE mode of operation.

 30

Figure 5.- Shows the frames of SOUT output data generated by the central processor from the information provided by the bioelectric sensors included

in the system of acquisition and transfer of neuronal activity according to the mode of operation MODE.

Figure 6.- Shows the different modules comprising each signal router used to connect the bioelectric sensors to the central processor in the system of acquisition and transfer of neuronal activity.

Below is a list of the different elements represented in the figures that make up the invention:

 10

1. System of acquisition and transfer of neuronal activity.

10000. Communications node.

11000. Central processor.

11001. Coding and decoding module.

11002. Data reception and classification module. fifteen

11003. Memory module instructions and parameters.

11004. Selection, configuration and acquisition module.

11010. Data synchronizer.

11020. Decoder.

11030. Data record. twenty

11031. DATA_DEC input data frame to the central processor according to the configuration mode.

11032. DATA_DEC input data frame to the central processor according to the calibration mode.

11033. DATA_DEC input data frame to the central processor according to the 25 signal tracking mode.

11034. DATA_DEC input data frame to the central processor according to the data compression mode.

11040. CRC validation module.

11050. Command identifier. 30

11060. Data reception status machines.

11070. Data stack.

11080. Non volatile memory.

11090. Selection and programming module.

11100. Data transmission status machines. 5

11110. Timing block.

11120. Parallel-series converter.

11121. SOUT data frame output to processor according to the mode of operation.

11130. Encoder. 10

12000. Signal routers.

12100. Registration.

12200. Internal memory.

12300. Control module.

12400. Module for the transfer of information. fifteen

20000. Plurality of bioelectric sensors.

30000. Wireless transceiver.

31000. Antenna.

32000. Transmitter.

33000. Receiver. twenty

40000. Power management block and clock synthesis.

50000. Calibration units.

60000. Plurality of intracranial electrodes.

DETAILED DESCRIPTION 25

The communications node (10000) object of the invention is comprised in a system of acquisition and transfer of neuronal activity and serves as a data gateway

bidirectional between a plurality of bioelectric sensors (20000) and a wireless transceiver (30000). Both the plurality of bioelectric sensors (20000) and the wireless transceiver (30000) are also included in said system (1).

The purpose of said system (1) is the capture, conditioning, digitization and wireless transmission of neuronal activity or some of its characteristics.

In a preferred embodiment, the plurality of bioelectric sensors (20,000) are arranged in a matrix manner, hence from now on it will be referred to as a matrix of bioelectric sensors (20,000). 10

In the direction of data transfer to the array of bioelectric sensors (20,000), the communications node (10,000) selectively activates, sizes and calibrates the bioelectric sensors (20,000), in accordance with the instructions received from the wireless transceiver (30000) . fifteen

In the sense of transferring data to the wireless transceiver (30000), the communications node (10000) transfers the data captured by the bioelectric sensor array (20,000) to an extracranial reader, located in the patient's environment within the coverage of the wireless transceiver (30000), which decodes the signal radiated by the wireless transceiver (30000) and, which acts as a data gateway between the neuronal activity acquisition and transfer system (1) and any means of storage, display, computation o dedicated communication for the analysis of captured neuronal activity.

 25

The present invention does not impose any functional or architectural restriction either on the array of bioelectric sensors (20,000) or on the wireless transceiver (30,000). In particular, the communications node (10000) is easily scalable with the number of bioelectric sensors (20,000) included in said matrix.

 30

Additionally, the communications node (10000) offers two modes of transmission:

- Signal tracking mode: full, captured and digitized neuronal activity is transferred from a selection of bioelectric sensors (20,000) from among the plurality included in the bioelectric sensor array (20,000);

- Data compression mode: information related to neuronal action potentials detected and characterized by bioelectric sensors 5 (20000) is transferred.

In the case of data compression mode transmission, the communications node (10000) comprises event-based digital processing means that cyclically examines the plurality of bioelectric sensors (20,000), identifies those 10 bioelectric sensors (20,000) in where a potential for neuronal action has been verified, it forms a data frame for each bioelectric sensor (20,000) where an event has occurred, and would be the data frames generated for its subsequent wireless transmission.

 fifteen

The cyclical review of the bioelectric sensors (20,000), carried out by the communications node (10,000), has a time base much lower than the reason for generating action potentials in biological neurons.

The combination of the data compression mode together with the 20-event-based processing significantly decreases the volume of information provided by the neuronal activity acquisition and transfer system (1), which directly impacts substantial savings in power consumption. .

The communications node (10,000) is integrated into a substrate shared by the array of 25 bioelectric sensors (20,000) and the wireless transceiver (30,000) constituting an inseparable monolithic solution. Therefore, the substrate that integrates the acquisition and transfer system (1): matrix of bioelectric sensors (20,000), communications node (10,000) and wireless transceiver (30,000), is a few millimeters, which facilitates its implementation in brain. 30

The substrate is made of a material selected from: silicon, organic, silicon on insulator, silicon-germanium, indium phosphide and gallium arsenide. Preferably, with a view to

reduce the cost of manufacturing the communications node (10000), silicon substrate is used.

Figure 1 shows the functional diagram of the neuronal activity acquisition and transfer system (1) in which the communications node (10000) object of the present invention is observed where the neuronal activity acquisition and transfer system (1) understands:

- a plurality of bioelectric sensors (20000),

- a wireless transceiver (30000) comprising a transmitter (32000) and a receiver (33000),

- a communications node (10,000) connected between the plurality of bioelectric sensors (20,000) and the wireless transceiver (30,000),

- a plurality of intracranial electrodes (60000), which capture neuronal activity, connected to the plurality of bioelectric sensors (20000), 15

- a plurality of calibration units (50,000) connected to the plurality of bioelectric sensors (20,000) to adjust transfer characteristics of the plurality of bioelectric sensors (20,000), and

- a power management and clock synthesis module (40000) for the management of the communications node (10000). twenty

In a preferred embodiment, the plurality of intracranial electrodes (60000) are arranged in a matrix manner, hence the term "intracranial electrode array" (60000) will be referred to hereinafter.

 25

The intracranial electrode array (60000) can be selected from:

- a sub-dural electrocorticographic mesh (ECOG),

- a formation of intracortical penetrating electrodes (intracortical matrix), and

- a deep brain probe with multiple sensing points. 30

As previously mentioned, the number of bioelectric sensors (20,000) are preferably distributed on a matrix basis to reduce system area consumption.

(1) and coincides with the number of intracranial electrodes (60000), comprised in the matrix of intracranial electrodes (60000), that is, N electrodes.

However, there could be a possibility that a plurality of microelectrodes is multiplexed on the same bioelectric sensor (20,000) and that the arrangement of the 5 bioelectric sensors (20,000) was not matrixed.

Each bioelectric sensor (20000) is identified by a numerical code ID_CELL that distinguishes it from the rest.

 10

The communications node (10000) comprises:

- a central processor (11000) that:

 interprets and applies the commands received from the wireless transceiver (30000), digitally processes the signals generated by the array of bioelectric sensors 15 (20,000), and encodes the information collected from said bioelectric sensors (20,000) for later transmission through the transceiver wireless (30000), and

- signal routers (12000) that:

 They implement the data interface between the array of bioelectric sensors (20,000) and 20 the central processor (11,000).

There are as many signal routers (12000) as there are bioelectric sensors (20,000). Each signal router (12000) is associated and, therefore, electrically connected, to a single bioelectric sensor (20,000). 25

The set of N bioelectric sensors (20,000) are structurally identical to each other and each bioelectric sensor (20,000) comprises:

- means for amplifying and filtering the neural signal captured from the intracranial electrode array (60000), 30

- means for automatically calibrating the maximum voltage levels and the frequency band of the signal conditioned by said amplification and filtering means;

- means for converting the conditioned neuronal signal from the analog to the digital domain;

- means to compress the captured information; Y

- means for temporarily storing said information.

 5

According to these means, bioelectric sensors (20,000) can offer different modes of MODE operation.

The flow of information from the communications node (10,000) to the bioelectric sensors (20,000) is done through a digital vector SEL and a data frame 10 CONF. The digital vector SEL is used to activate a subset of bioelectric sensors (20,000). If it is not addressed by the digital vector SEL, the bioelectric sensor (20000) remains inactive with a view to reducing the power consumption of the neuronal activity acquisition and transfer system (1). On the other hand, the CONF data frame allows the operating parameters of the different means 15 comprised in those bioelectric sensors (20,000) addressed by the digital vector SEL to be serially loaded.

Additionally, the flow of information from each bioelectric sensor (20,000), previously addressed by the digital vector SEL, and the communications node (10,000) is performed through a DCELL data frame and a DRDY logic signal. The DCELL data frame constitutes the serial output provided by said bioelectric sensor (20000). The structure of the DCELL data frame depends on the previously loaded CONF configuration data frame, in line with the selected mode of operation. The DRDY logic signal is a control signal that enables the transfer of the data frame 25 DCELL to the signal router (12000), associated with said bioelectric sensor (20000). Once the transfer of the DCELL data frame is completed, the DRDY logic signal is deactivated.

The data compression means implemented in the bioelectric sensors (20,000) 30 contemplate the real-time detection of neuronal action potentials and the characterization of the time-tension morphology of said action potentials, although they could be performed with any other compression mechanism. of data. Normally the

Neural activity captured and digitized is transferred to a processor where the data is compressed and not in the bioelectric sensors (20,000), so that the information traffic increases and, therefore, the power consumption.

The wireless transceiver (30000) comprises means necessary to establish a short-range radio link with the extracranial reader.

In the sense of data transmission, said wireless transceiver (30000) comprises:

- an antenna (31000) or, in general, any device designed to send the information collected by the system (1) for the acquisition and transfer of neuronal activity by electromagnetic waves, and;

- a transmitter (32000) to define the type of modulation, the data rate, the radiated power and, in general, all those parameters necessary to wirelessly transmit the encoded data frame DATA_ENC provided by the communications node (10000) . In a preferred embodiment, said encoded frame of DATA_ENC data is transferred via a serial connection.

In the sense of receiving data, said wireless transceiver (30000) comprises:

- an antenna (31000), preferably the same one used in the transmission path, intended to receive signals from the extracranial reader, and; twenty

- a receiver (33000) to demodulate the signals coming from said antenna (31000) in order to extract the encoded data frame DATA_DEM interpretable by the communications node (10000) and necessary to correctly configure the acquisition and transfer system (1) of neuronal activity as a whole.

 25

In both the transmission and reception paths, the emitted electromagnetic signals use communication protocols shared by the communications node (10000) and the wireless transceiver (30000).

The central processor (11000) is a processing unit where: 30

- the commands received from the receiver (33000) of the wireless transceiver (30000) are interpreted;

- MODE modes of operation of the bioelectric sensor array (20,000) are managed; Y

- signals representative of the neuronal activity are ordered, processed, formatted and sent to the wireless transceiver, said activity acquired by the bioelectric sensors (20,000) and transferred to the communications node (10,000) through the signal routers (12000).

Unless expressly stated otherwise, the central processor (11000) operates with the CLK master clock signal provided by the power management and clock synthesis module (40000).

 10

The commands interpretable by the central processor (11000) belong to one of four categories, each of these categories linked to a MODE mode of operation of the bioelectric sensors (20,000) and, by extension, of the acquisition and transfer system (1) of neuronal activity as a whole.

 fifteen

In the most general case, each of these categories may include more than one interpretable command. The distinction between commands linked to the same category is established by qualifiers included in those commands.

The bioelectric sensors (20000), being electrically programmable from the outside, 20 allow modifying their configuration by offering the different modes of MODE operation.

MODE modes of operation, representative of the interpretable command categories, are:

 25

1. Configuration Mode (MODE = ‘0 0’) by which the operating parameters of the bioelectric sensors (20,000) are defined with a view to capturing and compressing neuronal electrical activity. As will be seen later, in accordance with the present invention, the central processor (11000) has a default parameter configuration stored in a non-volatile memory (11080) that is preloaded with the start-up of the system (1 ) of acquisition and transfer of neuronal activity. This allows potentially reducing the number of commands needed to configure the bioelectric sensors (20,000). The

distinction between the different commands linked to the Configuration Mode is established by means of CF_Q qualifiers included in those commands. According to an embodiment of the present invention, once the loading of parameters in the bioelectric sensor (20,000), said bioelectric sensor (20,000), responds with a CONFIRM confirmation code that is transferred to 5 through the frame DCELL data.

2. Calibration Mode (MODE = ‘0 1’) by which the deviations of the amplification and filtering analog circuits included in the bioelectric sensors (20,000) are corrected autonomously. CAL_PAR 10 adjustment parameters linked to the Calibration Mode are specified in interpretable commands of the Configuration Mode and in interpretable commands of the Calibration Mode itself. In the most general case, the Calibration Mode can contemplate different execution variants. These variants are specified by CAL_Q qualifiers included in the interpretable commands of the Calibration Mode. Depending on these variants, the participation of calibration units (50,000), activated from the bioelectric sensors (20,000), may be necessary. By way of example, said calibration units (50,000) may consist of time references provided by a frequency synthesizer. According to an embodiment of the present invention, once the calibration of the transfer characteristic of the bioelectric sensor (20,000), said bioelectric sensor (20,000), is completed, it responds with a CONFIRM confirmation code that is transferred through the DCELL data frame. In another possible example of the present invention, the bioelectric sensor (20000) responds with the final value of the parameters set after the calibration process is completed.

3. Signal Tracking Mode (MODE = ‘1 0’) through which brain activity captured from intracranial electrodes (60000) is acquired, conditioned, filtered and digitized. In this mode of operation, the DCELL data frame of the bioelectric sensor (20,000) is formed by a sequence of TR_DATA digital vectors representative of the captured neural signal. TR_PAR parameters linked to the conditioning and filtering operations may come

specified, either by means of interpretable commands of the Configuration Mode, or as a result of the application of commands in Calibration Mode. In the most general case, the Signal Tracking Mode may contemplate different execution variants. These variants are specified by TR_Q qualifiers included in the interpretable commands of the Signal Tracking Mode. 5

4. Data Compression Mode (MODE = '1 1') whereby some of the characteristics of brain activity captured from intracranial electrodes (60000) are extracted and processed with a view to reducing the bandwidth of the transmitted signal towards the wireless transceiver (30000). The CMP_PAR 10 parameters linked to the Data Compression Mode are specified by interpretable Configuration Mode commands. In the most general case, the Data Compression Mode may contemplate different execution variants. These variants are specified by CMP_Q qualifiers included in the interpretable Compression Mode commands. As an example, the applicable data compression techniques for characterizing the time-tension morphology of neuronal action potentials can use approximation strategies with base functions, extraction of main components PCA "Principal Component Analysis", parameter calculation of a Hanning filter, or the conformation with “wavelet analysis” model waves. In a generic case, the characterization of the neuronal action potentials comprises K digital vectors FE_DATAy, where y = 1 ⋯ K. Once the characterization of the detected action potential is concluded, the DCELL data frame of the bioelectric sensor (20000) comprises the concatenation of said digital vectors FE_DATAy. Note that while the detection and characterization of a neuronal action potential does not occur, the DRDY logic signal is in a low logical state and the data output of the bioelectric sensor (20,000) remains inactive.

Figure 3 shows the distribution of modules of the central processor (11000) included in the communications node (10000). 30

1. Coding and decoding module (11001).

The coding and decoding module (11001) comprises means that allow the exchange of information with the wireless transceiver (30000).

In a communication sense, the encoding and decoding module (11001) comprises means for decoding the encoded frame of DATA_DEM data provided by the receiver (33000) comprised in the wireless transceiver 5 (30000). These means include:

- a data synchronizer (11010) that aligns the edges of the DATA_DEM encoded data frame with the CLK master clock signal, provided by the power management and clock synthesis module (40000), and generates an encoded frame of 10 DATA_IN data; Y

- a decoder (11020) that converts the format of the DATA_IN encoded data frame to a DATA_DEC data frame.

In a possible configuration, the format of the DATA_IN encoded data frame can be, for example, of the PIE type (Pulse Interval encoding). fifteen

In another sense of communications, the coding and decoding module (11001) comprises means for encoding a DOUT data frame provided by the central processor (11000), with a view to its subsequent modulation by the transmitter (32000) included in the wireless transceiver 20 (30000). These means include:

- a parallel-series converter (11120) that would be the DOUT data frame at the instance of a LOAD activation logic signal and generate a SOUT data frame; Y

- an encoder (11130) that converts the binary code of the SOUT data frame to the signal format defined in the transmitter (32000).

In a possible configuration, the format of the encoded frame of output data DATA_enc of the encoder (11130) may be of the Manchester type.

2. Module for receiving and classifying data (11002). 30

The data reception and classification module (11002) comprises means that allow the interpretation of the instructions received from the wireless transceiver (30000). These means include:

- a data register (11030) that stores the DATA_DEC data frame of the instruction received from said code provided by the decoder (11020);

- a CRC validation module (Cyclic redundancy check) (11040) to verify the integrity of said DATA_DEC data frame; 5

- a command identifier (11050) that analyzes the content of said data record (11030) and generates a MODE digital vector representative of the mode of operation specified in the instruction received; Y

- a plurality of state machines (11060) for receiving data that are selectively enabled according to the value of the digital vector MODE. 10

In a possible implementation, CRC validation could consist of counting and checking the number of bits with a certain logical value within a DATA_DEC data frame.

 fifteen

Figure 4 shows the DATA_DEC data frames of the instructions recognizable by the communications node (10000) where the DATA_DEC data frames are grouped according to the MODE mode of operation which are:

- DATA_DEC data frames input to the central processor according to Configuration mode 20 (11031),

- DATA_DEC data frames input to the central processor according to Calibration mode (11032),

- DATA_DEC data frames input to the central processor according to the Signal Tracking mode (11033), and 25

- DATA_DEC data frames input to the central processor according to the Data Compression mode (11034).

As can be seen in Figure 4, in the most general case, said data frames comprise digital vectors linked to six fields:

- a preamble;

- the MODE mode of operation defined for the bioelectric sensors (20000);

- a parameter range of application of said instruction between the bioelectric sensors (20000);

- a QERS qualifier of the instruction associated with the DATA_DEC data frame (depending on the mode of operation, said qualifier is characterized as CF_Q, CAL_Q, TR_Q or CMP_Q); 5

- a set of PARAMS configuration parameters for the bioelectric sensors (20,000) selected by said application range, and

- a cyclic redundancy code CRC.

 10

In the data frame DATA_DEC input to the central processor (11000) according to the Calibration mode (11032) the Range parameter only contemplates selection by columns or by individual channels.

In the data frame DATA_DEC input to the central processor (11000) according to the Signal Tracking mode (11033), the Range parameter only contemplates selection by columns or rows. In addition, the TR_Q qualifier is selected from two values, 0 for the selection reading and 1 for the scan from the selection.

In the data frame DATA_DEC input to the central processor (11000) according to the Data Compression mode (11034) the qualifier TR_Q is selected from two values, 0 for the fixed threshold voltage and 1 for the adaptive threshold voltage. twenty

Note that QERS qualifiers can, in some cases, address parameter groupings as exemplified in the DATA_DEC data frame according to the Configuration mode (11031) or, in other cases, define operation options as shown in the frames of data DATA_DEC 25 according to the Signal Tracking mode (11033), and frames according to the Data Compression mode (11034).

Note also that, in the most general case, the range of application can address a single bioelectric sensor (20,000), identified by the code ID_CELL, 30 a row or a column of the array of bioelectric sensors (20,000), identified, respectively by the ID_ROW and ID_COL codes, or the array of bioelectric sensors (20000). However, depending on the mode of operation, not all

Application ranges are allowed. For example, if as illustrated in Figure 1, the calibration units (50,000) are shared by rows of bioelectric sensors (20,000), the calibration mode could only be executed by columns or by individual sensor. In another example, the range of application of the Signal Tracking Mode could also be restricted to a limited number of bioelectric sensors (20,000) (for example, those belonging to a row or column of the array of bioelectric sensors (20,000)) , with the view that the output data rate of the neuronal activity acquisition and transfer system (1) does not exceed a given value.

Also note that not all DATA_DEC data frames must comprise 10 PARAMS parameters. In fact, according to this possible embodiment of the present invention, only the DATA_DEC data frames of the Configuration (11031) and Calibration (11032) operating modes include said parameters. Thus, according to this embodiment, there are no PARAMS parameters for the modes of operation linked to the transmission of information, that is, Signal Tracking and Data Compression.

There are as many reception status machines (11060) as possible modes of operation. Only the reception status machine (11060) that is addressed by the digital vector MODE remains active; the rest is disabled with a view to reducing the power consumption of the neuronal activity acquisition and transfer system (1). The purpose of said reception status machines (11060) is to identify the QERS qualifier of the command, the range of application and the PARAMS configuration parameters, if any, in the corresponding fields of the received instruction. In Figure 3, the INST data frame brings together the information of said fields.

3. Instructions and parameters memory module (11003).

The instructions and parameters memory module (11003) comprises means that store at all times the configuration of the system (1) for the acquisition and transfer of neuronal activity. Said memory module of

Instructions and parameters (11003) includes:

- a data stack (11070) in which the QERS qualifier, the application range and the configuration parameters, if any, are identified by the data reception status machines (11060); Y

- a non-volatile memory (11080) where default values are stored.

 5

With the start-up of the neuronal activity acquisition and transfer system (1), the data stack (11070) loads the values stored in said non-volatile memory (11080), from where they are transferred to the array of bioelectric sensors (20000 ), using a selection, configuration and acquisition module (11004). Likewise, by means of a Configuration Mode command with 10 qualifier CF_Q = ‘1 1 1’ it is possible to recharge the contents of the data stack (11070) in the bioelectric sensor array (20000).

The data reception status machines (11060) make up the OPT data frame and the SELECT digital vector from the INST data frame. The OPT data frame 15 of operation options comprises the QERS qualifier of the received command and the PARAMS configuration parameters, if any, involved in the execution of said INST data frame.

The digital vector SELECT designates a set of sensing channels involved in the application of the received command. Said SELECT digital vector uses the same signal format as the application range field comprised in the INST data frame. In accordance with this embodiment, the digital vector SELECT can identify individual bioelectric sensors (20,000), rows or columns of sensors, or all bioelectric sensors (20,000).

The transmission of the OPT data frame and the digital vector SELECT to the selection, configuration and acquisition module (11004), is carried out by means of serial connections enabled by logic activation signals, OPT_RDY and SEL_RDY (not shown in Figure 3 by simplicity).

4. Selection, configuration and acquisition module (11004). 30

The selection, configuration and acquisition module (11004) comprises means that interface with the signal routers (12000) that transfer the information generated by the bioelectric sensors (20000).

These means include:

- a selection and programming module (11090);

- a plurality of data transmission status machines (11100); Y

- a timing module (11110) for the generation of clock signals 5 scaled in frequency from the master clock signal CLK.

In a general case, the timing module (11130) provides specific clock signals for signal routers (12000) (CLKR signal with FTR frequency), for bioelectric sensors (20000) (CLKC signal with FTC frequency) and 10 for Calibration units (50,000) (CLKD signal with FTD frequency).

The selection and programming module (11090) verifies that the cyclic redundancy code of the instruction received is correct; it takes as input the OPT data frame and the digital vector SELECT generated by the machines of data reception status (11060) and enabled by the logic activation signals OPT_RDY and SEL_RDY; and generates a CONF data frame, a digital SEL vector and a TXON logic signal leading to define the state of the plurality of signal routers (12000), the array of bioelectric sensors (20,000) and the calibration units (50,000). twenty

The CONF data frame is formed by the concatenation of the MODE mode of operation of the received command and the operation options defined in the OPT data frame (QERS qualifier and PARAMS configuration parameters, if any), excluding those options related to the command sequencing between the sensors in the array of bioelectric sensors (20000). Thus, for example, in the Signal Tracking Mode, the CONF data frame does not contain a TR_Q qualifier, since said qualifier, according to an embodiment of the present invention, controls the sweep of readings within the matrix of bioelectric sensors (20000). In other words, the CONF data frame only contains relevant information at the level of the individual bioelectric sensor (20,000), independently of whether said CONF data frame is transferred to more than one bioelectric sensor (20,000).

Once said CONF data frame has been constructed, the selection and programming module (11090) sets the logical signal TXON to a high logical value to activate the plurality of data transmission status machines (11100). With the setting of said TXON logic signal, the CONF data frame is transferred via a serial connection to the bioelectric sensors (20000) addressed by the digital vector 5 SELECT. The transmission rate is FTC, that is, the frequency of the CLKC clock signal. This transmission is enabled by a logical activation signal, CONF_RDY (not shown in figures 1 and 3 for simplicity).

Upon completion of the transmission of the CONF data frame, the digital vector SEL activates those signal routers (12000) and bioelectric sensors (20000) 10 selected to execute the instructions received. In a general case, the digital vector SEL can vary throughout the application of a command, unlike what happens with the digital vector SELECT that remains unchanged. For example, in a possible embodiment of the present invention when the received command is linked to the Signal Tracking Mode and the command qualifier TR_Q is in a high logical state, the application of said instruction determines the scanning by rows or columns of the matrix of bioelectric sensors (20000). In this case, the digital vector SEL varies cyclically so that, at all times, only one row or column of said bioelectric sensor array (20,000) is active. On the contrary, the digital vector SELECT remains static during the execution of the command and only 20 directs the row or column from where the scan begins. In this case, the CONF data frame is transferred to the array of bioelectric sensors (20,000).

In a preferred configuration, the activation of bioelectric sensors (20000) performed by the digital vector SEL is implemented by means of row and column decoders arranged on the periphery of the matrix of said bioelectric sensors 25 (20,000).

The plurality of data transmission state machines (11100) receives as inputs the MODE digital vector representative of the mode of operation, the digital vector SEL indicating the active signal routers (12000) and bioelectric sensors (20,000), and the signal TXON logic generated by the selection and programming module (11090). In accordance with the present invention there are as many data transmission status machines (11100) as possible modes of operation. Only that data transmission status machine (11100) that is

addressed by the digital vector MODE remains active; the rest is disabled with a view to reducing the power consumption of the neuronal activity acquisition and transfer system (1). The purpose of said data transmission state machines (11100) is to read, process and send to the coding means (11001), the digital DATA vectors stored in the signal routers (12000) 5 addressed by the digital vector SEL. The RDY logic signal provided by said signal routers (12000), when it takes a high logical value, indicates that said digital DATA vectors are ready for reading. Otherwise, a low logical value of the RDY logic signal indicates that the signal router (12000) is either in the construction phase of the digital DATA vectors, or in the 10-phase phase waiting to receive information from the associated bioelectric sensor.

The procedure for reading the DATA digital vectors by that state machine for data transmission (11100) enabled by the MODE digital vector is performed by means of a READ pointer that cyclically cycles through the signal routers (12000) addressed by the digital vector SEL. If the READ 15 pointer addresses the signal router (12000) with the RDY logic signal in low logical state, the data transmission status machine (11100) changes the value of said READ pointer to the address of the next signal router ( 12000) within the set of signal routers (12000) enabled by the digital vector SEL. In this case, data transfer is not performed. On the contrary, if the logic signal 20 RDY of the signal router (12000) addressed by the READ pointer is in a high logical state, the digital DATA vectors are transferred to the data transmission status machine (11100) and, when it ends the reading, said data transmission machine (11100) sends a PDW pulse to the signal router (12000) so that it changes the RDY logic signal to the low logical state and changes the value of the READ pointer to the address of the next router. signal (12000) within the set of signal routers (12000) enabled by the digital vector SEL. In accordance with the present invention, the time base for reading the digital DATA vectors provided by the signal routers (12000) (said time base marked by the clock signal CLKR) is much lower than the generation rate 30 of said data (said rate marked by the FTC frequency of the CLKC clock signal).

Once the DATA digital vectors have been read, the data transmission status machine (11100) enabled by the MODE digital vector validates the captured information, potentially combining the DATA vectors of different bioelectric sensors (20,000), and stores the set in DOUT data frames. When said digital frames are formed, the data transmission status machine (11100) sends a LOAD pulse that enables the DOUT transfer to the parallel-series converter (11120) comprised in the encoding and decoding module (11001). Together with the DOUT data frame, the SOUT data frame, the result of the seriation, includes a preamble in the header and a cyclic redundancy code at the end of said frame. 10

In a possible embodiment of the present invention illustrated in Figure 3, said LOAD pulse is also transferred to the selection and programming module (11090) so that, in the event that the received command is linked to the Signal Tracking Mode and the TR_Q command qualifier is in high logic state, 15 the digital vector SEL address the next position in the row or column scan of the bioelectric sensors (20000).

Figure 5 shows the structure of the SOUT data frame at the output of the parallel-series converter (11120), in accordance with an exemplary embodiment of the present invention. Only in the case of operation in the Signal Tracking Mode does the combination of DATA digital vectors from different bioelectric sensors (20,000) specifically those bioelectric sensors (20,000) occur; in the row or column addressed by the digital vector SEL. Said digital DATA vectors have been denoted as TR_DATAx, where x = 1 ⋯ F, 25 being F the number of bioelectric sensors (20,000) comprised in said row or column. In this case, the identifier ID_CELL refers to the first bioelectric sensor (20000) in the selected row or column. In all other modes of operation, the information comes from a single bioelectric sensor (20,000) from among the array of bioelectric sensors (20,000). Thus, the digital vectors FE_DATAy, 30 where y = 1 ⋯ K, represent the representative values of the data compression performed by the bioelectric sensor (20000) identified by the ID_CELL code. Also, according to this embodiment, the digital DATA vectors

corresponding to the Configuration and Calibration modes consist of a CONFIRM confirmation code that indicates the completion of the respective operations.

Figure 6 shows the structure of a signal router (12000) comprised in the communications node (10000). Said signal router (12000) comprises:

- a register (12100) in which, at the request of the DRDY write logic signal, the DCELL data frame provided by the bioelectric sensor (20000) associated with said signal router (12000) is stored;

- an internal memory (12200) in which said information is organized in digital data DATA of fixed length; 10

- a control module (12300) that manages the operation of the signal router (12000); Y

- a module for the transfer of information (12400) that uses a parallel bus for the orderly transmission of the digital DATA vectors to the data transmission status machines (11100) comprised in the central processor 15 (11000).

The signal router (12000) remains in active state as long as it is addressed by the digital vector SEL generated by the selection and programming module (11090) comprised in said central processor (11000). If this is not the case, the signal router (12000) remains inactive in order to reduce the power consumption of the neuronal activity acquisition and transfer system (1). The clock signal that controls the operation of the module for the transfer of information (12400) is CLKR, said signal provided by the timing module (11110) comprised in said central processor (11000). The remaining modules in the signal router (12000) operate with a CLKC clock signal.

From the moment the DCELL data frame provided by the bioelectric sensor (20,000) associated with the signal router (12,000) is completely stored in the register (12,100) and the DRDY logic signal goes to a low logical state, the module Control (12300) identifies the MODE mode of operation of the received command and establishes an internal memory load protocol (12200). According

said protocol, the control module (12300) extracts from the register (12100) each of the parameters or variables contained in said DCELL data frame, and stores them through the parallel FILL connection in the POS position of said internal memory ( 12200), said specific position for each parameter or variable according to the identified mode of operation. Regardless, of the specific content of the DCELL data frame, the first position of the internal memory (12200) is loaded with the value of the digital vector MODE and the identification of the ID_CELL bioelectric sensor within the matrix of N bioelectric sensors (20000) . When the content of the DCELL data frame has been completely dumped into the internal memory (12200), the control module (12300) stops the 10 RDY logic signal to enable the digital vector data transfer DATA via the module for the transfer of information (12400) as soon as the READ pointer generated by the data transmission status machine (11100) addresses the signal router (12000). As mentioned earlier, when the data transfer is complete, said data transmission status machine (11100) sends a PDW pulse to the signal router (12000) so that it changes the RDY logic signal to the low logical state.

The DATA digital vectors, once selected by the data transmission status machine (11100), combined in a DOUT data frame and 20 concatenated by the parallel-series converter (11120) comprised in the encoding and decoding module (11001 ), form the SOUT data frame for subsequent encoding by the encoder (11130).

The connection of both the RDY and PDW logic signals and the DATA 25 output bus from the plurality of signal routers (12000) to the information transmission state machine (11100) comprised in the central processor (11000) is performed by Tri-state buffers controlled by the READ pointer, as shown in Figure 1. This significantly simplifies the number of routes required to communicate the said circuit elements. 30

In a possible application of the present invention, the neuronal activity acquisition and transfer system (1) is used as the header of an interface

man-machine (BMI, "brain-machine interface"). According to this possible application example, the system (1) would acquire the signals coming from the motor cortex and send them abroad for further processing with a view to controlling automatons or other mechanisms that would alleviate some type of motor deficiency of the patient. 5

In another possible example of application of the present invention, the neuronal activity acquisition and transfer system (1) is incorporated into a closed loop system for the detection and treatment of epileptic seizures by neuromodulation techniques. In this application, the activation of neurostimulators would be dictated by the analysis of the signals provided by the neuronal activity acquisition and transfer system (1).

The present invention should not be limited to the embodiment described herein. Other configurations may be made by those skilled in the art at sight 15 of the present description. Accordingly, the scope of the invention is defined by the following claims.

 twenty

Claims (19)

1. System (1) for the acquisition and transfer of neuronal activity comprising: - a plurality of bioelectric sensors (20000), 5 - a wireless transceiver (30000) comprising a transmitter (32000) and a receiver (33000), - a communications node (10,000) connected between the plurality of bioelectric sensors (20,000) and the wireless transceiver (30,000), - a plurality of intracranial electrodes (60000), which capture neuronal activity, 10 connected to the plurality of bioelectric sensors (20000), - a plurality of calibration units (50,000) connected to the plurality of bioelectric sensors (20,000) to adjust transfer characteristics of the plurality of bioelectric sensors (20,000), and - a power management and clock synthesis module (40000) for the management of communications node 15 (10000), characterized by: - the communications node (10000) is configured to transmit data 20 bidirectionally between the plurality of bioelectric sensors (20000) and the wireless transceiver (30000) so that: or in the sense of data transmission from the wireless transceiver (30000) to the bioelectric sensors (20000), the communications node (10000), manages a parameter configuration, a calibration and a mode of operation of the bioelectric sensors ( 20000) and, or in the sense of data transmission from the bioelectric sensors (20,000) to the wireless transceiver (30,000), it collects, would be and form neuronal information of a neural signal captured by the plurality of bioelectric sensors (20000). 30 2. System (1) for the acquisition and transfer of neuronal activity, according to claim 1, characterized in that the bioelectric sensors (20,000) comprise: - means for amplification and filtration of the neuronal signal captured from the intracranial electrodes (60000), - automatic calibration means of maximum voltage levels and a 5 frequency band of the neuronal signal conditioned by the amplification and filtration means; - means for converting the conditioned neuronal signal from the analog to the digital domain; - means of compression of the captured neuronal information; and 10 - means for temporary storage of said captured neural information. 3. System (1) for the acquisition and transfer of neuronal activity, according to any one of the preceding claims, characterized in that the communications node (10000) comprises: - a central processor (11000) that interprets and applies instructions received from the receiver (33000), digitally processes the neural signals generated by the plurality of bioelectric sensors (20,000), and encodes the neural information collected from the plurality of bioelectric sensors ( 20000) for subsequent transmission via the wireless transceiver (30000), and - a plurality of signal routers (12000) that implement a data interface between the plurality of bioelectric sensors (20000) and the central processor (11000), where each signal router (12000) is associated and electrically connected to a single bioelectric sensor (20000). 4. System (1) for the acquisition and transfer of neuronal activity, according to any one of the preceding claims, characterized in that the central processor (11000) comprises:  a coding and decoding module (11001) for the exchange of information with the wireless transceiver (30000);  a module for receiving and classifying data (11002) for the interpretation of the instructions received from the wireless transceiver (30000);  a module of instructions and parameters memory (11003) to store the configuration of the system (1) for acquisition and transfer of neuronal activity; and 5  a selection, configuration and acquisition module (11004) that serves as an interface with the signal routers (12000) that transfer the information generated by the plurality of bioelectric sensors (20000). 5. System (1) for acquisition and transfer of neuronal activity, according to claim 4, characterized in that the coding and decoding module (11001) for the exchange of information with the wireless transceiver (30000) comprises:   - in a sense of communications:  a data synchronizer (11010) that lines edges of a demodulated signal provided by the receiver (33000) with a master clock signal generated by the power management and clock synthesis module (40000); Y  a decoder (11020) that decodes said demodulated signal by converting the demodulated signal to a binary code, 20 - in the other sense of communications:  a parallel-series converter (11120) that would be a signal with output data provided by the central processor (11000), after receiving an activation signal; Y  an encoder (11130) that encodes the serial signal with the output data at a signal format defined in the transmitter (32000) for later modulation by said transmitter (32000). 6. Neural activity acquisition and transfer system (1) according to claim 4 or 5, characterized in that the data reception and classification module 30 (11002) for the interpretation of the instructions received from the wireless transceiver (30000) understands:  a data record (11030) that stores a DATA_DEC data frame of an instruction received by the decoder (11020);  a CRC validation module (11040) to verify the integrity of the DATA_DEC data frame;  a command identifier (11050) that analyzes the contents of the data record (11030) and generates a digital vector MODE representative of a mode of operation specified in the instruction received; Y  a plurality of data reception status machines (11060) that are selectively enabled according to a value of the digital vector MODE 10. 7. Neural activity acquisition and transfer system (1) according to claim 4, 5 or 6, characterized in that the instruction and parameter memory module (11003) for storing the configuration of the acquisition system (1) and 15 Neural activity transfer comprises:  a stack of data (11070) into which, overwriting previous data, a QERS qualifier, an application range and configuration parameters, if any, identified by the data reception status machines (11060); and 20  a non-volatile memory (11080) where default values are stored, where the data stack (11070) loads the values stored by default in nonvolatile memory (11080), from where they are transferred to the plurality of bioelectric sensors (20,000). 25 8. System (1) for the acquisition and transfer of neuronal activity, according to claim 4,5,6 or 7, characterized in that the selection, configuration and acquisition module (11004) which serves as an interface with the signal routers (12000 ) that transfer the information generated by the plurality of bioelectric sensors (20000) 30 comprises:  a selection and programming module (11090);  a plurality of data transmission state machines (11100); Y  a timing block (11110) for a generation of clock signals scaled in frequency from the master clock signal.  5 9. Neural activity acquisition and transfer system (1) according to any one of the preceding claims, characterized in that the signal routers (12000) comprise: - a register (12100) in which the neuronal information 10 provided by the plurality of bioelectric sensors (20000) is stored, - an internal memory (12200) in which neuronal information is organized into fixed-length vectors, - a control module (12300) that manages each signal router (12000), and 15 - a module for the transfer of information (12400) comprising a parallel bus for orderly transmitting the fixed-length vectors to the data transmission status machines (11100). 10. Neural activity acquisition and transfer system (1) according to any one of the preceding claims, characterized in that the plurality of intracranial electrodes (60000) are selected from: - sub-dura electrocorticographic electrodes, - intracortical penetrating electrodes, - a deep brain probe with sensing points, and 25 - a combination of the above. 11. System (1) for the acquisition and transfer of neuronal activity, according to any one of the preceding claims, characterized in that the number of bioelectric sensors (20,000) coincides with the number of intracranial electrodes (60000) and with the number of routers signal (12000). 12. Method of acquisition and transfer of neuronal activity using the system (1) defined in claims 1 to 11, characterized in that the communications node (10000) comprises: - in the sense of data transmission from the wireless transceiver (30000) to 5 the plurality of bioelectric sensors (20000):  activate, size and calibrate the plurality of bioelectric sensors (20,000), in accordance with instructions received from the wireless transceiver (30,000), for the capture and compression of neuronal activity, 10  correct the deviations of analog amplification and filtering circuits included in the bioelectric sensors (20,000), and - in the sense of data transmission from the plurality of bioelectric sensors (20000) to the wireless transceiver (30000): 15  transfer the data captured by the plurality of bioelectric sensors (20,000) to the wireless transceiver (30,000) to externally monitor neuronal activity by means of an extracranial reader.  twenty 13. The method of acquisition and transfer of neuronal activity according to claim 12, characterized in that the bioelectric sensors (20000), in the sense of data transmission from the wireless transceiver (30000) to the plurality of bioelectric sensors (20000) comprise two modes of operation:  25  a Configuration Mode by which the operating parameters of the bioelectric sensors (20,000) are defined to capture and compress neuronal activity, and  a Calibration Mode by which the 30 deviations of the amplification and filtering means included in the bioelectric sensors (20,000) are automatically corrected. 14. Method of acquisition and transfer of neuronal activity according to claim 12 or 13, characterized in that the bioelectric sensors (20,000), in the sense of data transmission from the plurality of bioelectric sensors (20,000) to the wireless transceiver (30000) , comprise two modes of operation:  5 - a Signal Tracking Mode: full, captured and digitized neuronal activity is transferred from the plurality of intracranial electrodes (60000), - a Data Compression Mode: neuronal activity is transferred relative to neuronal action potentials detected from the plurality of intracranial electrodes 10 (60000). 15. Method of acquisition and transfer of neuronal activity according to claim 14, characterized in that in the data compression mode, the communications node (10000) comprises: - detect events through embedded digital processing means by performing a cyclic examination of the bioelectric sensors (20,000), - identify those bioelectric sensors (20,000) where a potential for neuronal action has been verified, - form a data frame for each bioelectric sensor (20,000) where the event has occurred, and - Serial data frames generated for subsequent wireless transmission through the wireless transceiver (30000). 16. Method of acquisition and transfer of neuronal activity according to any one of the preceding claims, characterized in that each mode of operation comprises a frame of input data to the central processor, wherein each frame of data comprises six fields: - a first field that defines a preamble; 30 - a second field that defines the mode of operation of the bioelectric sensors (20000); - a third field that defines an application range between bioelectric sensors (20,000); - a fourth field that defines a particular qualifier for each mode of operation, which addresses parameter groupings or defines execution variables of the modes of operation, 5 - a fifth field that defines a set of configuration parameters for the bioelectric sensors (20,000) selected by said application range, and - a sixth field that defines a cyclic redundancy code CRC. 17. Method of acquisition and transfer of neuronal activity, according to any one of the preceding claims, characterized in that the central processor (11000): - interprets instructions received from the receiver (33000), - manages the modes of operation of the plurality of bioelectric sensors (20000), - orders, processes, formats and sends to the wireless transceiver (30000) the neuronal signals 15 transmitted by the plurality of bioelectric sensors (20,000) and transferred to the communications node (10,000) through the signal routers (12,000), and - operates with a master clock signal provided by the power management and clock synthesis module (40000). twenty 18. Use of the neuronal activity acquisition and transfer system (1) defined in claims 1 to 11 as the header of a man-machine interface. 19. Use of the neuronal activity acquisition and transfer system (1) according to claim 18 wherein the system (1) comprises the acquisition of signals from a motor cortex.