Interseizure epileptic activity-based intracranial neuron electrical stimulation system for treating epileptic seizure

Abstract

The invention provides an intracranial neuron electrical stimulation system for treating epilepsy and other brain diseases involving epileptic seizure, which can immediately apply intracranial neuron electrical stimulation to the interseizure epilepsy activity in a personalized manner after detecting the interseizure epilepsy pattern each time. And the stimulation is activated by intracranial electroencephalogram (EEG) detection. The intracranial stimulation for epileptic activities in the epileptic seizure period continuously acts along with time, the forming process of an epileptic network can be blocked, the neuronal super-synchronization risk is reduced, and therefore the control effect on epileptic seizure is improved. The invention also includes the use of nerve adjustment biomarkers, thereby dynamically optimizing the detectability and providing more accurate overall assessment for the patient's treatment progress. Finally, according to the scheme, by detecting the intracranial EEG mode and the high-risk state mode (such as the epileptic state and the sudden accidental death risk in epilepsy) in the attack period, an instant alarm is given to the patient / nursing personnel, and it is ensured that safe treatment measures are taken for the patient in time.

Description

Technical Field

[0001] This invention relates to an intracranial neuronal electrical stimulation system for the treatment of epilepsy and other brain diseases involving epileptic seizures. Background Technology

[0002] Epilepsy is a highly destructive brain disorder affecting approximately 50 million people worldwide. It is the fourth most common neurological disorder characterized by seizures. Epilepsy is defined as a sudden, excessive, and rapid discharge of neurons in the brain, detectable by an electroencephalogram (EEG). Seizures significantly and often severely impact a patient's quality of life, preventing them from participating in daily activities such as driving and swimming, affecting personal and family planning, and leading to social and occupational discrimination. Furthermore, poorly controlled seizures can result in various harmful conditions, ranging from status epilepticus due to prolonged seizures to severe cardiopulmonary arrest (either during or after a seizure), which are leading causes of sudden unexpected death in epilepsy (SUDEP).

[0003] Currently, there are two main approaches to treating epilepsy: antiepileptic drugs and epilepsy surgery. Antiepileptic drug treatment can achieve a seizure-free state in 70% of patients. However, the side effects of antiepileptic drugs can significantly impact patients' quality of life, resulting in 40% of patients failing to achieve their treatment goals. Epilepsy surgery is the recognized treatment option for drug-resistant patients. The main goal of epilepsy surgery is the complete removal (or complete transection) of the primary epileptic area in the brain that causes seizures. However, it is estimated that only 50% of drug-resistant epilepsy patients are candidates for epilepsy surgery. For patients who are resistant to both antiepileptic drug treatment and epilepsy surgery, intracranial neuronal electrical stimulation (or neurostimulation) is used as a conservative therapy to improve seizure control.

[0004] Over the past few decades, the U.S. Food and Drug Administration (FDA) has approved neurostimulation devices to address the problems of antiepileptic drug failure and patients' inability to be included in surgical plans. Open-loop neurostimulation systems (i.e., systems without feedback), such as vagus nerve stimulators (VNS) and deep brain stimulation (DBS), are configured to deliver periodic and diffuse electrical stimulation to epileptic brain regions to suppress unexplained seizure activity. Clinical studies have shown significant differences in the efficacy of these devices, with 25% to 75% of patients reporting a 50% reduction in seizures post-surgery, and only 5% achieving seizure-free status. However, research data shows that when the patient's caregiver senses an impending seizure or the onset of a seizure, external use of the provided neurostimulator's magnetic activation system to activate the open-loop implanted neurostimulator can improve seizure control by up to 50%. These data suggest that closed-loop neurostimulation systems may have even greater efficacy.

[0005] Currently, the only FDA-approved closed-loop intracranial neurostimulation system for the brain is the Responsive Neurostimulator (RNS), which consists of a four-channel programmable processing unit capable of both recording and electrically stimulating the brain. This device is implanted into the skull via craniotomy, with electrodes placed in the epileptogenic zone of the brain, determined during the patient's preoperative evaluation at a specialized epilepsy center. The effectiveness of the RNS in reducing seizure frequency has been demonstrated in multicenter clinical studies, with approximately 70% of patients with focal seizures experiencing a significant reduction in seizure frequency. Up to 30% of patients achieved seizure-free status within 6 months post-surgery, while nearly 15% maintained seizure-free status for more than a year.

[0006] Current closed-loop intracranial neuronal electrical stimulation (RNS) methods for treating seizures are based on the detection of neurophysiological markers indicating the onset of a seizure and the immediate application of pre-programmed electrical stimulation upon detection to instantly and momentarily terminate ongoing seizure events, such as those recorded in intracranial EEG (US Patent Application No. 6,016,449; WO2004 / 043536A1). The main hypothesis regarding the mechanism of action of RNS is that ongoing seizure activity is terminated instantly and momentarily through intracranial neuronal electrical stimulation. Although examples of this mechanism are occasionally mentioned sporadically in the published literature, the chronic effects of closed-loop intracranial neuronal electrical stimulation on the brain have not been systematically studied. Instead, there is evidence that patients report improved seizure control, such as reduced seizure frequency and decreased seizure intensity and / or duration, when changes in the neurophysiological characteristics of intracranially recorded seizures are detected. These neurophysiological changes are summarized by the rough term "neuromodulation." Since the primary claim and recommended mechanism of action of the RNS neurostimulation system is to immediately and instantaneously terminate epileptic seizure activity, the occurrence of such neurophysiological phenomena appears to be a side effect of this activity. Therefore, it is necessary to induce neural modulation with sufficient specificity using closed-loop intracranial neuronal electrical stimulation techniques. To this end, it is advantageous to design a closed-loop intracranial neuronal electrical stimulation system that can act over time, progressively altering and weakening the underlying epileptic network, preventing it from generating hypersynchronous activity and inducing paroxysmal discharges. Furthermore, reliable and quantitative detection of the neural modulation generated by intracranial neuronal electrical stimulation is also of great significance. Summary of the Invention

[0007] According to the present invention, an intracranial neuronal electrical stimulation system for interictal epileptic activity as described in claim 1 is provided.

[0008] According to the present invention, an intracranial neuronal electrical stimulation system for interictal epileptic activity is provided for the treatment of brain diseases involving epileptic seizures. The system includes an implantable device (35) having a central intracranial stimulation unit (22) connected via a physical intracranial interface unit (27) to at least two intracranial implantable electrodes, each having at least two contacts. The electrodes can be surgically implanted into the brain parenchyma (24) of a patient (23). The central intracranial stimulation unit (22) is configured to record intracranial electroencephalography (EEG), detect patterns of interictal epileptic activity (4), and provide immediate (e.g., effective within less than 1 second) and personalized intracranial neuronal electrical stimulation (5) upon detection of an interictal pattern.

[0009] This invention provides an intracranial neuromodulation system for treating epilepsy and other brain disorders involving seizures, such as developmental brain malformations, brain tumors, arteriovenous malformations, stroke, and brain injury. The system applies intracranial neuronal electrical stimulation to interictal (rather than ictal) epileptic activity via intracranial EEG. Activation of the electrical stimulation is achieved by continuously recording intracranial EEG and continuously detecting interictal epileptic discharges, forming the first therapeutic closed loop of this invention. While the embodiments of this disclosure are primarily applicable to the treatment of epileptic seizures, they can also address other neurological disorders, such as movement disorders (e.g., Parkinson's disease) and chronic pain, as well as neuropsychiatric disorders (e.g., bipolar disorder, depression, eating disorders, and obsessive-compulsive disorder).

[0010] In a preferred embodiment, the system disclosed in this invention further includes a diagnostic / prognostic loop using novel neuromodulation biomarkers. This loop adapts computational intelligence (CI) detection algorithms to dynamic intracranial EEG data during seizures and provides supervising neurologists with reliable and quantifiable measures for assessing patient status in the context of neurostimulation therapy. Specifically, this invention employs a set of four neurophysiological biomarkers that reliably and quantifiably detect the presence and quality of neuromodulation in the epileptic network of the human brain as a result of chronic intracranial neuronal electrical stimulation, and contribute to adapting intracranial neuronal electrical stimulation parameters to neuromodulation data. The advantage of this integration is that, through a primary diagnostic / prognostic loop, a series of neuromodulation biomarkers provide information for methods of detecting seizure-phase intracranial EEG patterns, thereby detecting the presence and quality of neuromodulation in potential epileptic networks. Therefore, the presence, combination, or absence of these biomarkers constitutes an alternative method for assessing the efficacy of intracranial neuronal electrical stimulation—current efficacy "biomarkers" based on RNS systems refer only to the immediate and instantaneous termination of seizure events. Because each CI algorithm integrated into the implantable device is trained based on each patient's unique data, this technology enables truly personalized treatment for each patient.

[0011] In another preferred embodiment, the system disclosed in this invention includes an additional safety loop. This additional safety loop aims to protect the patient's physical integrity and minimize the risks faced by the patient during a seizure by detecting intracranial EEG patterns during the seizure and detecting high-risk patterns of status epilepticus and SUDEP. The advantage of this integrated solution is that, through the added additional safety loop, it provides immediate alerts to the patient and / or authorized guardians / caregivers by detecting intracranial EEG patterns during the seizure, enabling them to take timely measures to ensure the patient's safety and physical integrity.

[0012] Finally, this invention relates to an intracranial neuronal electrical stimulation method based on the aforementioned original concept. By blocking the establishment process of the epileptic network, it reduces the possibility of neuronal hypersynchronization and produces a positive / beneficial neuromodulation effect on intracranial EEG during epileptic seizures. This innovative technology applies intracranial neuronal electrical stimulation to epileptic activity between seizures rather than during ictal periods. Unlike the acute effect of immediate and instantaneous termination of epileptic seizures proposed by RNS technology, this technology acts over time, gradually altering and weakening the underlying epileptic network, preventing it from generating hypersynchronous activity and inducing paroxysmal discharges.

[0013] Other features and advantages of the present invention, as well as the structure and operating principles of the various embodiments of the present invention, will be described in detail below with reference to the accompanying drawings. Attached Figure Description

[0014] The present invention will be described with reference to several embodiments shown in the accompanying drawings. It should be noted that the drawings show preferred embodiments of the invention and should not be considered as limiting the scope of the invention. It should also be understood that the drawings may include certain optional features, which are not essential in any embodiment.

[0015] Figure 1 An established epileptogenic network is illustrated schematically.

[0016] Figure 2 The expected effects of intracranial neuronal electrical stimulation on the network's ability to generate seizure activity were demonstrated.

[0017] Figure 3 The expected effects of this intracranial neuronal electrical stimulation technique on interictal and ictal discharges in epilepsy are schematically illustrated. (A) Intracranial EEG pattern of an epileptic seizure before the application of this intracranial neuronal electrical stimulation technique. (B) Intracranial neuronal electrical stimulation applied at the moment of appearance of a single interictal spike (marked by a striped box). (C) Intracranial EEG pattern of an expected epileptic seizure after the application of this intracranial neuronal electrical stimulation technique.

[0018] Figure 4 An embodiment of an implantable device is illustrated schematically.

[0019] Figure 5 Two preferred methods for implanting the device are illustrated schematically. (A) Placement on the skull using standard cranial screws, without craniotomy. (B) Subcutaneous subclavian placement above the sternum.

[0020] Figure 6 The electrical stimulation subunit (30) and the digital intracranial interface unit (28) are schematically shown.

[0021] Figure 7 The computational intelligence unit (32) is shown.

[0022] Figure 8 Examples of intracranial neuronal electrical stimulation systems for interictal epileptic activity are summarized, wherein the system is activated each time interictal activity is detected in an intracranial EEG.

[0023] Figure 9 The diagram illustrates the external EEG neural modulation assessment computation system (108) and its interaction with the external CI learning and parameterization computation system (109) and the external monitoring device (62).

[0024] Figure 10 The charging process of the external monitoring device (62) and the implantable device (35) placed on the surface of the skull (A) and under the skin of the sternum (B) is illustrated schematically.

[0025] Figure 11 This is a schematic diagram of an external contactless battery charging device (91).

[0026] Figure 12 A battery contactless charging sub-unit (33) is shown that is connected to a battery (61) of an implantable device (35).

[0027] Figure 13 This is a schematic diagram of a non-contact battery charging unit (64) for a battery (83) connected to an external monitoring device (62).

[0028] Figure 14 An external instant notification device (104) is shown that connects wirelessly to an external monitoring device (62).

[0029] Figure 15 An external monitoring device (62) is shown schematically.

[0030] Figure 16 This is a schematic diagram of the physical intracranial interface unit (27) and the biosignal recording subunit (29).

[0031] Figure 17 A two-way wireless communication subunit (31) is shown.

[0032] Figure 18 This is a schematic diagram of a two-way wireless communication subunit (63).

[0033] Figure 19 The external interface subunit (66) is shown.

[0034] Figure 20 The biometric identification subunit (67) is schematically shown.

[0035] Figure 21Novel neurophysiological biomarkers for detecting neural modulation in epileptic networks derived from chronic intracranial neuronal electrical stimulation are presented. (A) Neuronal oscillation frequency shift (NOFS) in intracranial EEG during seizures. (B) Neuronal oscillation amplitude shift (NOAS). (C) Neuronal oscillation density shift (NODS). (D) Neuronal oscillation temporal sustainability shift (NOTSS). Detailed Implementation

[0036] The present invention will be described below with reference to specific embodiments. Clearly, the system according to the present invention can be implemented in various forms. Therefore, the specific structural and functional details disclosed in the present invention are merely illustrative and do not limit the scope of the invention.

[0037] Terms not specifically defined in this specification shall be given the meaning as understood by those skilled in the art based on this disclosure and the overall context.

[0038] As used in this invention, the term "neuromodulation" refers to changes in the neurophysiological characteristics of episodic EEG discharges as a result of electrical stimulation.

[0039] The term "interictal activity" refers to abnormal brain electrical activity that occurs during the intervals between epileptic seizures.

[0040] As used in this invention, the terms "interictal pattern" or "interictal epileptic activity pattern" are used interchangeably to refer to the morphological and spatial distribution changes of interictal epileptic activity as presented in continuous intracranial EEG.

[0041] The term "postictal activity" refers to abnormal brain electrical activity that occurs immediately following the end of a seizure.

[0042] The term "computational intelligence" refers to the analysis and design of learning and / or generalization models based on numerical data, including but not limited to machine learning, decision support, data mining, neural networks, fuzzy systems, intelligent systems, expert systems, and evolutionary computation, or combinations thereof.

[0043] As used in this invention, the terms "therapeutic" and "treatment" mean eliminating, reducing, suppressing, or delaying the progression, severity, and / or extent of a subject's disease, lesion, clinical signs, or symptoms. The terms also refer to the relief (including complete or partial relief) of clinical signs and symptoms associated with diseases or conditions such as epilepsy.

[0044] This invention takes into account the established fact that epilepsy is a brain network disorder. It is also generally accepted that different regions of the brain are anatomically and functionally interconnected to exchange information via synapses and enhance neuronal performance. Furthermore, it is known that epileptogenic zones electrochemically interfere with normal neural pathways in the brain and utilize these pathways to propagate their resulting abnormal epileptiform activity. Over time, primary epileptogenic zones form epileptogenic networks by building upon their anatomically and functionally interconnected regions. These regions then become secondary epileptogenic zones, which may eventually transform into primary epileptogenic zones if seizures are not effectively controlled over a prolonged period.

[0045] This invention also considers the well-established fact that latent neuronal hypersynchrony is a key characteristic of epileptic networks, and it is this characteristic that endows these networks with epileptic dynamics. Neuronal synchrony is a physiological characteristic of neuronal populations in the brain, reflecting their ability to exchange information and efficiently organize themselves to perform brain functions. However, when neuronal synchrony exceeds normal levels for an extended period (i.e., neuronal hypersynchrony), the resulting electrochemical activity can induce epileptic seizures. Furthermore, the formation of secondary epileptic regions from primary epileptogenic areas via electrochemically mediated synapses is a crucial process in generating neuronal hypersynchrony and thus leading to epileptic seizures. This neuronal hypersynchrony is recorded in intracranial EEG as high-intensity discharge sequences, typically in a spike-wave morphology, and repeats rhythmically or semi-rhythmically throughout the epileptic seizure.

[0046] This invention is based on the original concept that the process of constructing a secondary epileptogenic zone from a primary epileptogenic zone occurs over time through the exchange of brief paroxysmal discharges between the two zones. These brief paroxysmal discharges are recorded on EEG as interictal epileptic activity. Although this is a well-known form of epileptic activity, its role in epileptogenesis remains controversial and unclear in published literature. Examples of interictal epileptic activity include sharp waves, sharp wave complexes, spikes, spike wave complexes, polyspikes, polyspike wave complexes, and rapid paroxysmal activity. The concept of viewing interictal activity as a neuronal building block for establishing and expanding epileptic networks (and thus forming neuronal hypersynchronization) is innovative.

[0047] This invention is based on another innovative concept: targeting interictal epileptic activity with intracranial neuronal electrical stimulation in a personalized manner immediately after the onset of epilepsy (e.g., within less than one second), disrupting neuronal formation processes and preventing the establishment of an epileptogenic network over time. In the context used herein, "personalized" means adjusting the stimulation method according to the unique morphology and spatial distribution of each patient's interictal activity. Figure 1An established epileptogenic network is shown, in which the primary epileptogenic focus (1) establishes anatomical and functional connections with different neuronal clusters via bidirectional synapses (3), exchanging interictal epileptic activity (4) on bidirectional synaptic pathways (3), presented here as sharp wave complexes. These neuronal clusters gradually evolve into secondary epileptogenic focuses (2) over time. Each focus in the epileptogenic network (primary (1) and secondary (2)) is colored using a four-level grayscale to represent the established degree of epileptogenicity, i.e., its ability to generate independent epileptogenic activity: A. Black indicates that the neuronal cluster has the potential to generate a large amount of epileptogenic activity—this is the core characteristic of the primary epileptogenic area (1). B. Dark gray indicates that the neuronal cluster has the potential to generate frequent epileptogenic activity. C. Medium gray indicates that the neuronal cluster has the potential to generate occasional epileptogenic activity. D. Light gray indicates that the neuronal cluster has the potential to generate rare epileptogenic activity. The formation (2) of the primary epileptogenic focus (1) is achieved through chronic bidirectional interictal interactions (4), thereby making the secondary epileptogenic focus (2) also a source of frequent epileptic activity. As described in this invention, neuronal electrical stimulation of interictal epileptic activity can achieve the following effects: isolating the primary epileptogenic focus from the rest of the network, disrupting the connectivity of the existing network, and significantly reducing the network's potential to generate neuronal hypersynchronization—which leads to the occurrence of paroxysmal epileptic discharges.

[0048] Figure 2The expected effects of personalized intracranial neuronal electrical stimulation (5) immediately targeting interictal epileptic activity (4) upon its occurrence were demonstrated, reflecting changes in the network's ability to generate seizure activity. By personalized intracranial neuronal electrical stimulation (5) targeting interictal EEG activity (4) over time, the influence of the primary epileptogenic focus (1) on the secondary epileptogenic focus (2) was significantly reduced. Consequently, the epileptogenic potential of the secondary focus decreased from a level that frequently generated epileptic activity to a level that caused occasional or rare seizures. Consequently, the overall epileptogenic potential of the network was reduced, resulting in any paroxysmal discharges that eventually occurred exhibiting: reduced frequency (low-frequency paroxysmal discharges), weakened intensity (low-intensity paroxysmal discharges), or shortened duration (short-duration paroxysmal discharges). Furthermore, by eliminating the chronic influence of the primary epileptogenic area on the secondary epileptogenic area, the likelihood of these secondary epileptogenic areas generating independent epileptic activity in the future was significantly reduced. This alteration of the neurophysiological properties of the epileptic network—as a result of chronic intracranial electrical stimulation of interictal epileptic activity in a timely and personalized manner—is identified as a positive / beneficial neuromodulation phenomenon in intracranial EEG. The invention is innovative in that timely and personalized intracranial electrical stimulation of interictal epileptic activity can lead to the degradation of connectivity in the epileptic network in the brain, manifested as a positive / beneficial neuromodulation effect in intracranial EEG.

[0049] Figure 3 The expected effects of the intracranial neuronal electrical stimulation technology of this application on paroxysmal discharge in three different time phases (Phase 1: before application, Phase 2: during application, and Phase 3: after application) are demonstrated. Figure 3 In Figure A, an example of intracranial EEG of a focal ictal epileptic discharge (6) is presented, evolving from left to right over time. In this first stage (i.e., before the proposed intracranial neuronal electrical stimulation technique is applied), the ictal epileptic discharge (6) is the result of complete activation of the potential epileptogenic network. In the early stages of the epileptic activity (left side), low-intensity normal EEG gradually synchronizes, leading to synchronized spike activity of increasing intensity (middle). This activity eventually develops into the core ictal activity, producing high-intensity, highly synchronized rhythmic spike discharges (right side). This ictal epileptic activity (6) is precisely the target of intracranial neuronal electrical stimulation in the prior art's closed-loop RNS neurostimulation system, which aims to acutely and immediately interrupt the development of ictal epileptic activity and terminate it immediately. Figure 3 In section B, an example of intracranial EEG (7) showing interictal epileptic spike activity (4) (marked with an asterisk *) is shown. The system disclosed in this invention is configured to perform targeted processing immediately after each interictal epileptic spike (4) to apply the proposed intracranial neuronal electrical stimulation (5). Figure 3(as shown in the striped box in B), rather than targeting fully developed epileptic seizure discharges (6). Figure 3 C demonstrates the expected effects of timely and individualized chronic intracranial neuronal electrical stimulation of interictal epileptic activity upon detection (8), whereby... Figure 3 The epileptic discharge (6) shown in Figure A has undergone significant neurophysiological changes, indicating the effect of neuromodulation. Specifically, the neuromodulated epileptic seizure (8) is characterized by reduced synchronous activity, decreased waveform intensity, and the disappearance of the high synchronicity of rhythmic spike discharges. This paroxysmal discharge pattern generated by the underlying epileptic network after neuromodulation by chronic intracranial neuronal electrical stimulation targeting interictal activity indicates the disintegration of the epileptic network. This phenomenon is the main target of the novel intracranial neuronal electrical stimulation technique proposed in this paper.

[0050] Therefore, in the preliminary overview of the present invention, an intracranial neuroelectric stimulation system is provided, which is based on a method of performing intracranial neuronal electrical stimulation on interictal epileptic activity in an immediate and personalized manner upon detection of interictal epileptic activity. Figure 4 An embodiment of this intracranial neuronal electrical stimulation system for interictal epileptic activity is demonstrated, which is activated by continuous intracranial EEG monitoring. The system includes an implantable device (35) that can be surgically implanted into a patient (23). Based on current neurosurgical techniques, implantation can be achieved in two ways: a. by placing a standard cranial screw on the skull (…). Figure 5 A) No craniotomy required; b) Subcutaneous subclavian placement above the sternum ( Figure 5 B). By placing the implantable device inside the patient's body (on the skull or in the chest cavity), craniotomy can be avoided, thus significantly reducing the degree of trauma to the patient's body during the implantation process.

[0051] During the same surgical procedure described above, intracranial electrodes can be implanted into the brain parenchyma (24) to cover various regions of the epileptic network. The implantable device (35) serves as the primary neuromodulator, responsible for continuously recording intracranial EEG, detecting intracranial EEG patterns during interictal and ictal periods, and applying intracranial neuronal electrical stimulation techniques to interictal epileptic activity in a personalized and immediate manner when interictal epileptic activity is detected.

[0052] Figure 4 The implantable device shown consists of two main parts: A1: A physical intracranial interface unit (27) comprising an adapter for connecting at least two intracranial electrodes. These electrodes may be surgically implanted into the patient's brain parenchyma to anatomically cover the epilepsy network. An implantable device (35) may be interconnected with two, three, four, five, six, seven, or eight intracranial electrodes via a corresponding physical intracranial interface unit (27). The advantage of this integrated system is that it can receive input from more than two intracranial electrodes, providing more comprehensive coverage of the epilepsy network compared to existing closed-loop RNS systems, thereby improving the flexibility of surgical procedures and the effectiveness of electrical stimulation. Each intracranial implantable electrode (25) may include at least two recording contacts. Preferably, each intracranial implantable electrode (25) has five recording contacts. In the latter case, the fifth intracranial electrode contact is used as a reference input for a differential amplifier, thereby generating four bipolar intracranial EEG channels (4) for each electrode: channel 1 = contact 1 - contact 5, channel 2 = contact 2 - contact 5, channel 3 = contact 3 - contact 5, channel 4 = contact 4 - contact 5. By creating four bipolar channels, independent and continuous recording of intracranial EEG signals from each contact is achieved. More preferably, the implantable device (35) is interconnected with eight intracranial electrodes, each of which includes five recording contacts. This configuration achieves an optimal balance between the amount of data recorded and the physical volume of the implantable device (35).

[0053] In one embodiment, the physical intracranial interface unit (27) is also interconnected with one or more auxiliary biosensors (26), preferably two to four auxiliary biosensors (26), for capturing accompanying biomarkers necessary to assess high-risk patterns such as status epilepticus and SUDEP. Suitable biosensors include, but are not limited to, heart rate, body temperature, and blood oxygen saturation sensors.

[0054] A2. A central intracranial stimulation unit (22) is primarily responsible for administering intracranial neuronal electrical stimulation to interictal epileptic activity in a real-time and personalized manner, the stimulation being activated by intracranial EEG detection. The unit records intracranial EEG from implanted electrodes and activates the intracranial neuronal electrical stimulation process when interictal activity is detected in the intracranial EEG. Simultaneously, the unit transmits the recorded data to an external monitoring device (62) and controls the energy storage and charging process of its battery (61).

[0055] A central intracranial stimulation unit (22) is connected to an intracranial implantable electrode (25) responsible for recording intracranial electroencephalography (EEG) to provide precise and personalized intracranial neuronal electrical stimulation by detecting interictal epileptic activity patterns to apply multiple electrical stimulation patterns (including a set of stimulation pulse sequences). Optionally, it also detects ictal epileptic activity patterns and monitors the battery (61) charge of the implantable device (35). In a preferred embodiment, the central intracranial stimulation unit (22) is also interconnected with one or more auxiliary biosensors (26) that record accompanying biological signals required to assess high-risk epileptic activity patterns such as status epilepticus and SUDEP. Suitable biosensors include, but are not limited to, heart rate, body temperature, and blood oxygen saturation sensors.

[0056] In another embodiment, the central intracranial stimulation unit (22) includes an electrical stimulation subunit (30) configured to generate and deliver electrical pulses according to preset programming parameters. Figure 6 The electrical stimulation subunit (30) can be configured to generate electrical pulses synchronously by simultaneously activating all contacts, or asynchronously by selectively activating specific contacts. Since interictal activity occurs asynchronously in the EEG signal, the preferred mode for the electrical stimulation subunit (30) to generate electrical pulses is asynchronous. Preferably, the electrical stimulation subunit (30) includes a biphasic electrical pulse generator (41) which can selectively generate square wave, symmetrical trapezoidal wave, or symmetrical triangular wave electrical pulses. The generator can provide an asynchronous mode for applying electrical pulses, which is activated immediately upon detection of an intracranial EEG pattern of interictal epilepsy. More preferably, the shape, intensity, frequency, and / or duration parameters of individual pulses and pulse sequences are programmed by an external monitoring device (62). In this case, selective electrical stimulation is applied to specific contacts of the intracranial implanted electrode via a line selector (42) according to programming instructions received from the external monitoring device (62). Preferably, the biphasic electrical pulse generator has parameterization options for the intensity, frequency, and duration of individual pulses and pulse sequences.

[0057] In another embodiment of the system of the present invention, the central intracranial stimulation unit (22) further includes an embedded computational intelligence (CI) subunit (32), the embedded CI subunit ( Figure 7The system can detect patterns of epileptic activity during the ictal phase, interictal phase, and optional postictal phase in intracranial EEG, as well as / or high-risk patterns, and provide relevant detection information of the corresponding intracranial EEG patterns to the system, preferably, by transmitting it to the electrical stimulation subunit (30). Based on the above principles and existing technical knowledge, those skilled in the art can design the CI subunit to calculate output data in response to input data—given that all necessary information in a closed-loop system (such as the system proposed in this invention) is, by definition, present in the recorded EEG, the types and complexities of widely applicable algorithms are not limited. Preferably, the embedded CI subunit (32) is an embedded machine learning subunit. The embedded CI subunit may include one or more of the following independent pattern detectors: 1. Interictal epileptic activity pattern detector (43); 2. Ictal activity pattern detector (44); 3. High-risk postictal epileptic activity pattern detector (45); 4. Auxiliary detector (46) for detecting novel intracranial patterns and accompanying biosignals. In a preferred embodiment, the embedded CI subunit (32) includes an independent interictal epileptic activity pattern detector (43), which is personalized for each patient (23), capable of detecting each recording channel of the intracranial implanted electrode (25), and processing all recorded intracranial EEG signals. In another preferred embodiment, the integrated YN subunit (32) includes an independent seizure activity pattern detector (44), which is personalized for each patient (23), for detecting from each recording channel of the intracranial implanted electrode (25), and processing all recorded intracranial EEG signals. In another preferred embodiment, the embedded CI subunit (32) includes an independent high-risk postictal epileptic activity pattern detector (45), which is personalized for each patient (23), for detecting from each recording channel of the intracranial implanted electrode (25), and processing all recorded intracranial EEG signals and accompanying biosignals recorded by an auxiliary biosensor (26) in embodiments where a biosensor is available. According to a preferred embodiment, the detector operates with personalized parameters for each patient and applies these parameters to all available recording channels of the implanted electrode. The detection information can be recorded in the biosignal recording subunit (29) based on its respective timestamp, so as to realize the correlation between the recorded signal and the recognition time of a specific pattern. Figure 7 In this embodiment, the parameters (including architectural elements) of all detectors (47) in the embedded CI subunit (32) can be set and updated wirelessly via external monitoring device (62).

[0058] exist Figure 4In the embodiment of the central intracranial stimulation unit (22) shown, the embedded CI subunit (32) is configured to communicate with the electrical stimulation subunit (30) such that when the embedded CI subunit (32) detects an interictal epileptic intracranial EEG pattern (4), the electrical stimulation pulse generated by the electrical stimulation subunit (30) is asynchronously provided to specific contacts of the intracranial implanted electrode via a line selector (42) according to a pre-installed program.

[0059] By continuously recording intracranial EEG, epileptic discharges during each interictal period were detected, and intracranial neuronal electrical stimulation was immediately applied. Figure 8 (35->5->24->4->35), which constitutes the first closed-loop treatment system of the present invention.

[0060] Therefore, the system disclosed in this invention is entirely opposite to the closed-loop intracranial neuronal electrical stimulation technique implemented in existing RNS systems. The latter aims to electrically stimulate the onset of interictal epileptic activity during a seizure to directly and immediately intercept and terminate the interictal epileptic activity. Compared to the prior art, the advantage of this invention lies in implementing an innovative treatment approach—namely, applying intracranial neuronal electrical stimulation technology to interictal epileptic activity in an immediate and personalized manner, aiming to gradually weaken the epileptic network's ability to trigger seizures.

[0061] As those skilled in the art will understand from the above description, Figure 4 The structure shown is merely one embodiment of the present invention. Many other configurations or improvements discussed in this invention, and which can be made by those skilled in the art without departing from the scope defined by the claims, are possible.

[0062] The system disclosed herein may also include an external monitoring device (62) that can be worn by the patient—secured to the body (e.g., arm) by a strap. Figure 5 The device may be placed in a carrying device (e.g., in a backpack) or in the patient's immediate vicinity (e.g., on a desk). The device provides a graphical user interface for the patient and / or authorized users (guardians / caregivers, clinical supervisors) to perform specific procedures related to the patient's neurostimulation therapy. The external monitoring device (62) is configured to perform one or more of the following functions: communicate with the central intracranial stimulation unit (22), receive, store and transmit intracranial EEG data; receive notifications from the embedded CI subunit (32) when an episodic intracranial EEG pattern (6) or a high-risk post-ictal pattern is detected; set and update intracranial neuronal electrical stimulation parameters, exchange system information with the implanted device, monitor the battery (83) power of the external monitoring device (62), receive epileptic seizure warning information from the patient, and provide immediate alerts when an episodic epileptic pattern is detected in the intracranial EEG.

[0063] In another embodiment, the system of this disclosure further includes an external EEG neuromodulation assessment computing system (108) that processes intracranial EEG data to enable personalized assessment of neuromodulation levels. Figure 9 Preferably, the system processes intracranial EEG data using classical neurophysiological computational methods, and detects neuromodulation phenomena for each patient in an individualized manner based on key intracranial EEG biomarkers. More preferably, the personalized assessment of the level of neuromodulation is based on one or more biomarkers of intracranial epileptic seizure EEG, the biomarkers being selected from the group consisting of: neuronal oscillation frequency shift, intracranial EEG paroxysmal spike amplitude shift, intracranial EEG paroxysmal spike density, and the temporal length of intracranial EEG paroxysmal neuronal oscillations. The original biomarkers are detailed in Examples 1 to 4. The presence, combination, or absence of these biomarkers can serve as an alternative method for assessing the effects of intracranial neuronal electrical stimulation and can more accurately reflect the patient's treatment progress. The data can also optionally be co-assessed with seizure log data submitted by the patient and / or guardian / caregiver through an external monitoring device (62).

[0064] In a preferred embodiment, the system further includes an external CI learning and parameterization computation system (109) responsible for developing software residing in and running on the embedded CI subunit (32), which detects the user's personalized episodic and interictal activities. Preferably, in embodiments where the implantable device (35) is also connected to an assistive biosensor, the software developed by the external CI learning and parameterization computation system (109) for the embedded CI subunit (32) enables it to also detect high-risk patterns based on a combination of postictal intracranial EEG data and accompanying biosignals from the assistive biosensor. Figure 9 Seizure log data reported by the patient and / or guardian / caregiver via external monitoring devices (62) can be jointly assessed with intracranial recorded data as needed. Figure 9 In one embodiment, the external CI learning and parameterization calculation system (109) can receive and process all intracranial data of the patient via an external monitoring device (62), preferably transmitted via a secure server (107). Furthermore, the system can also receive data on the type and quality of neural modulation from an external EEG neural modulation assessment calculation system (108), and accordingly configure a corresponding algorithm for identifying intracranial EEG patterns during an attack for each patient. According to the above preferred embodiment, adapting assessment criteria for detecting intracranial EEG patterns during an attack using neural modulation biomarkers constitutes the second diagnostic / prognostic closed loop of the present invention. Figure 8(35 -> 62 -> 107 -> 108 -> 109 -> 62 -> 35), enabling the system to dynamically optimize its detection capabilities and more accurately monitor the patient's treatment progress.

[0065] according to Figure 4 In the illustrated embodiment, the intracranial neuronal electrical stimulation system may include an external non-contact battery charging device (91) wirelessly coupled to the central intracranial stimulation unit (22) and the external monitoring device (62) to non-invasively charge their respective batteries via electromagnetic induction (see [reference]). Figure 10 A, 10B). The advantage of the embodiment is that the non-contact battery charging function, through periodic non-contact charging, minimizes the need for sequential battery replacement surgery for implantable devices, thereby significantly reducing the degree of invasiveness experienced by patients. According to Figure 11 In the preferred embodiment shown, the external contactless battery charging device (91) may include an induction coil system (93) and a charging management module (94) for controlled wireless charging (95) from its own wire-chargeable battery (92) to the battery (83) of the external monitoring (62) device and / or the battery (61) of the implantable device (35). According to a more preferred embodiment, the external contactless battery charging device (91) includes an identification structure for coupling with the implantable device (35) and the external monitoring device (62), transmitting device identification data via an identification data encoding system (96), a parallel-to-serial data converter (97), a wireless data repeater (98), and an antenna (102) to ensure dedicated coupling with the central intracranial stimulation unit (22) and the external monitoring device (62). Alternatively or simultaneously, the identification structure coupled to the implanted device (35) and the external monitoring device (62) can receive device identification data via an antenna system (102), a wireless data receiver (99), a serial-to-parallel data converter (100), and an identification data decoder (101). Figure 11 ).

[0066] according to Figure 12 In the illustrated embodiment, the central intracranial stimulation unit (22) may include a contactless battery charging subunit (33) responsible for monitoring the available power level of the battery (61) of the implantable device (35). The charging process is achieved through an interface coupled to an external contactless battery charging device (91), preferably through an induction coil system (58) and a charging management subunit (59), thereby implementing controlled wireless charging (60) of the battery (61) of the implantable device (35).

[0067] according to Figure 13In one embodiment, the external monitoring (62) device may include a contactless battery charging unit (64) configured to interface with an external contactless battery charging device (92) via an induction coil system (80) and a charging management subunit (81) to perform controlled wireless charging (82) on the battery (83) of the external monitoring device (62).

[0068] In another embodiment, the present invention provides immediate notification to the patient and / or authorized guardian / caregiver by detecting intracranial EEG patterns during an attack, so as to take timely measures to ensure the patient's safety and physical integrity. According to the embodiment, the system of the present invention may include one or more external instant notification devices (104) wirelessly coupled to an external monitoring device (62) to notify guardians / caregivers in the patient's surrounding environment of the detection results of attack-related activity patterns and high-risk post-attack activity patterns. Figure 14 Preferably, one or more external real-time notification devices establish a dedicated secure coupling with the external monitoring device (62) through the external interface subunit (66) of the external monitoring device (62). Figure 15 The specific implementation method will be described below.

[0069] Preferably, to achieve coupling with external monitoring devices (62), one or more external real-time notification devices include, for example, Figure 14 The device includes a Bluetooth Low Energy (BLE) or similar low-power protocol interface module (105). It may also include a notification visualization interface module (106) (via a display screen or other visual notification means) to display relevant information to authorized users (guardians / caregivers) carrying the device.

[0070] By assessing intracranial EEG data and accompanying biological signals, alerts are provided to patients and their caregivers / nursing staff regarding their condition. Figure 8 (35->62->104->23), forming a third safety loop (open loop for the system but closed loop for the patient) to support efforts to minimize the risk during a patient’s seizure.

[0071] According to one embodiment, the central intracranial stimulation unit includes a digital intracranial interface subunit (28). Figure 4 It is configured to digitize analog data recorded by intracranial implanted electrodes (25) via a physical intracranial interface unit (27). Figure 16The analog data recorded by the auxiliary biosensor (26) is also digitized in embodiments that include an auxiliary biosensor (26). In a preferred embodiment, the digital intracranial interface subunit (28) includes a differential amplifier (37) for the analog intracranial EEG signal corresponding to each pair of intracranial electrodes, preferably connected via an input isolator (36). The differential amplifier (37) for the analog intracranial EEG signal is configured to have a dual function: firstly, to create a bipolar recording channel, and secondly, to modulate the signal to an appropriate potential level for digitization. As previously mentioned, when the intracranial implantable electrode (25) includes five recording contacts, the fifth contact serves as the reference input of the differential amplifier, thereby generating four (4) bipolar intracranial EEG channels for each electrode. The input isolator (36) serves to protect subsequent amplification stages from the current generated during the intracranial neuronal electrical stimulation phase. In a more preferred embodiment, the digital intracranial interface subunit (28) includes an analog-to-digital converter (38) to digitize the analog signal corresponding to the intracranial EEG signal of each channel obtained from the preamplifier (37).

[0072] according to Figure 16 In the illustrated embodiment, the digital intracranial interface subunit (28) can be coupled to the biosignal recording subunit (29) to enable continuous recording of intracranial EEG (and, in a system embodiment including an auxiliary biosensor (26), accompanying biosignals can also be recorded). More preferably, intracranial EEG data from at least two (preferably eight) intracranial implantable electrodes (25) and two to four auxiliary biosensors (26) and auxiliary biosensor data can be synchronously recorded in the biosignal recording subunit (29) via the digital intracranial interface subunit (28). The biosignal recording subunit (29) can include a data storage architecture (39) to store intracranial EEG data from the intracranial implantable electrode assembly and data from the auxiliary biosensors received by the digital intracranial interface subunit (28), and operate in a first-in-first-out (FIFO) mode. Alternatively or simultaneously, the data storage architecture (39) may receive additional detection data from the embedded CI subunit (32), which provides detection information on intracranial EEG episodic and interictal patterns, as well as information on electrical stimulation application.

[0073] In a preferred embodiment, the biosignal recording subunit (29) can perform archiving recording types selected from the group consisting of: 1. periodically archiving intracranial EEG background recordings of a fixed duration of 5 minutes every 30 minutes for use by the attending neurologist for diagnosis; 2. urgently archiving continuous intracranial EEG recordings during seizure pattern detection, with a variable recording duration, including seizure activity from 1 minute before the first detection to 5 minutes after the last detection, for both diagnostic analysis and immediate notification of the patient and / or guardian / caregiver; 3. urgently archiving continuous intracranial EEG recordings during high-risk post-seizure pattern detection, with a variable recording duration, including recordings extended to 5 minutes after the last detection of a high-risk post-seizure pattern, for immediate notification of the patient's guardian / caregiver; and 4. any combination of the above modes. Overall, whether it is routine background EEG recording or emergency recording of seizure activity, the system archives the recorded data in an intermittent (non-continuous) manner to limit the size of the physical storage space (data storage device) of the data, thereby adapting to the limited space of the implantable device. Recording (biomarker, stimulation, and detection data) can be controlled by a programmable timer (40) and synchronized using a timestamp (real-time measurement data) accompanying the sampling, provided by a real-time clock embedded in the central intracranial stimulation unit (22). In a more preferred embodiment, the biosignal recording subunit (29) archives a routine 5-minute continuous intracranial EEG recording every 30 minutes, controlled by the programmable timer (40). Recording and archiving 5 minutes of intracranial EEG every 30 minutes is equivalent to collecting 4 hours of data every 24 hours, increasing the daily sample size of intracranial information by 40 times (x40) compared to existing RNS systems, thereby significantly enhancing the representativeness of data on treatment status and progress. In another preferred embodiment, the biosignal recording subunit (29) urgently archives continuous intracranial EEG recordings during seizure pattern detection for a variable duration, including seizure activity from 1 minute before the first detection to 5 minutes after the last detection, controlled by the programmable timer (40). In another alternative preferred embodiment, the biosignal recording subunit (29) urgently archives continuous intracranial EEG recordings during high-risk post-ictal pattern detection, with the archiving duration being variable, including ictal period recordings extended to a time range of 5 minutes after the last detection of a high-risk post-ictal pattern, the process being controlled by a programmable timer (40).

[0074] The central intracranial stimulation unit (22) can be equipped with a two-way wireless communication subunit (31). Figure 17This enables wireless coupling with an external monitoring device (62). Preferably, the pairing relationship with the external monitoring device (62) is exclusive, thereby ensuring communication security. The coupling may include one or more of the following types of information exchange: 1. Transmitting intracranial EEG data and intracranial EEG pattern detection information during an attack to the external monitoring device. 2. Receiving the programming parameters and architectural elements of the CI subunit and electrical stimulation from the external monitoring device (62). 3. Exchanging system information with the external monitoring device (62). In terms of data transmission security, the bidirectional wireless communication subunit (31) includes a data encoding module (50), which has data encoding, compression and / or encryption functions, preferably implemented through a parallel-to-serial data conversion system (51), a wireless data repeater (52) and an antenna (57). Accordingly, in order to achieve secure data reception, it may include a data decoding module (55), which has data decoding, and / or decompression, and / or data decryption functions, preferably implemented by an analog antenna system (57), a wireless data receiver (53) and a serial-to-parallel data converter (54).

[0075] According to one embodiment, the bidirectional wireless communication subunit (31) includes an asynchronous data transmission module (48) for transmitting stored intracranial EEG data along with corresponding stored intracranial EEG pattern recognition information to an external monitoring device (62). Alternatively or simultaneously, the bidirectional wireless communication subunit (31) also includes a synchronous data transmission module (49) for transmitting on-demand system information and real-time intracranial episodic EEG pattern recognition information to the external monitoring device (62). Stable data reception is achieved through synchronous transmission. The bidirectional wireless communication subunit may also include a power monitoring module (56) for monitoring the power consumption of the implantable device and adjusting asynchronous data transmission (which transmits the largest amount of data) to ensure that the power consumption is always below a preset threshold.

[0076] To optimize operational coordination, the central intracranial stimulation unit (22) may include a central control unit (34), which includes an application-specific integrated circuit or a general-purpose processor, configured to execute pre-loaded programs in its built-in memory and, based thereon, arbitrate one or more subunits of the central intracranial stimulation unit regarding data channel usage and system condition status. The central control unit has a built-in real-time clock for synchronizing data and control program sequences.

[0077] according to Figure 15In the illustrated embodiment, the external monitoring device (62) may include a bidirectional wireless communication subunit (63) that is wirelessly coupled to the implantable device (35). Preferably, the pairing with the implantable device (35) is exclusive to ensure communication security. The bidirectional wireless communication subunit (63) may be configured to transmit programming parameters and / or system information of the CI and electrostimulation unit to the implantable device (35). In a preferred embodiment, to enhance the security of wireless data transmission, the bidirectional wireless communication subunit (63) includes a data encoding module (71) that has data encoding, compression, and encryption functions to achieve secure wireless transmission, and is connected via a parallel-to-serial conversion system (72), a wireless data repeater (73), and an antenna (79). Alternatively or simultaneously, the bidirectional wireless communication subunit (63) may be configured to receive intracranial EEG data, accompanying biosignal data, intracranial EEG pattern recognition data, and / or system information from the implantable device (35). In a preferred embodiment, to enhance the security of wireless data reception, the bidirectional wireless communication subunit (63) includes a data decoding module (76). The data decoding module (76) has data decoding and / or decompression and / or decryption functions to achieve the security of wireless reception, and is connected through an antenna system (79), a wireless data receiver (74), and a serial-to-parallel data converter (75).

[0078] according to Figure 18 In the illustrated embodiment, the bidirectional wireless communication subunit (63) may include an asynchronous data acquisition module (77) for receiving recorded data from the implantable device and simultaneously acquiring the corresponding stored intracranial EEG and high-risk pattern recognition information. Alternatively or simultaneously, the bidirectional wireless communication subunit (63) may include a synchronous data acquisition module (78) for receiving system information and key / high-risk intracranial EEG pattern recognition information from the implantable device (35) in real time as needed.

[0079] The external monitoring device (62) can preferably be wirelessly connected to one or more external instant notification devices (104) via an external interface subunit (66) to notify the caregiver / nursing staff in the patient's surrounding environment when an episodic activity pattern or a high-risk post-epidemic activity pattern is detected. Figure 14 External interface subunit (66) Figure 15 , 19The system is configured to transmit intracranial EEG data (including encoded, compressed, and / or encrypted data), accompanying biosignals (where available), and intracranial EEG pattern recognition information, preferably via a secure Ethernet interface to a secure server (107). Optionally, the external interface subunit (66) can receive upgraded versions of the parameters of the embedded CI subunit (32) from an external CI learning and parameterization calculation system (109). Figure 19 In some embodiments, the external interface subunit (66) may include an Ethernet interface module (86) implementing the IEEE 802.11 protocol (any version) or other high-bandwidth wireless protocols and connected via a synchronous transmission system (84) and a data selector (85), preferably via a secure server (107). Alternatively or concurrently, the external interface subunit (66) may include a Bluetooth Low Energy (BLE) interface module or a similar low-power protocol interface module (87) connected via the synchronous transmission system (84) and the data selector (85).

[0080] Optionally, the external monitoring device (62) may include one or more intracranial EEG data storage subunits (65) coupled to a bidirectional wireless communication subunit (63) for local storage of intracranial EEG data, accompanying biosignals and / or intracranial EEG pattern recognition information acquired from the implantable device (35).

[0081] To ensure the safety and exclusive access of patients and / or authorized users (guardians / caregivers, clinical administrators), the external monitoring device (62) may include a biometric identification subunit (67). Figure 20 Preferably, the biometric identification subunit (67) provides secure access through the biometric controller system (89), the biometric data storage module (88), and the external biometric fingerprint sensor (90).

[0082] The external monitoring device (62) can provide a graphical user interface for patients and / or other authorized users to input and view information related to neurostimulation therapy via a display interface subunit (69). Based on the same principle, the external monitoring device (62) includes and runs an operating system (68), which provides a graphical user interface for patients (23) and / or other authorized users (103) to input and view information. Figure 15 ).

[0083] The external monitoring device (62) may include a central control unit (70), which includes an application-specific integrated circuit or a general-purpose processor and performs programmed operations according to instructions from an installed operating system (68). The central control unit (70) arbitrates the aforementioned subunits of the external monitoring device regarding the use of data channels and the conditional status of the system. The external monitoring device (62) includes a central control unit (70) whose processor executes a program determined by the operating system (68) and arbitrates the use of data channels and the conditional status of the system regarding the bidirectional wireless communication subunit (63), the contactless battery charging subunit (64), the intracranial EEG data storage subunit (65), the external interface subunit (66), the biometric identification subunit (67), the display interface subunit (69), and / or the operating system (68).

[0084] Based on the above, the external monitoring device (62) can be configured to perform one or more of the following functions: a. as an intermediary device for forwarding data that can be recorded and generated by the implantable device (i.e., intracranial EEG, accompanying biomarkers, and related detection data), which is forwarded to the external EEG neuromodulation assessment calculation system (108), and / or received from the external CI learning and parametric calculation system (109), and / or forwarded to the external instant notification device (104); b. as a programming device for the implantable device (35) for adjusting electrical stimulation parameters, detection parameters, and central programming; c. providing power status information of its own battery (83) and the battery (61) of the implantable device (35) to optimize the charging process arrangement; and d. providing a seizure log application, submitted by the patient or guardian / caregiver, whose data will be collaboratively evaluated together with the intracranial EEG data and seizure pattern recognition data provided by the external CI learning and parametric calculation system (109).

[0085] Another aspect of this invention provides a method for intracranial neuronal electrical stimulation based on the aforementioned original concept. This method generates a positive / beneficial neuromodulation effect in intracranial EEG during epileptic seizures by blocking the epileptic network establishment process and reducing the likelihood of neuronal hypersynchronization. This innovative technique applies intracranial neuronal electrical stimulation to interictal (rather than ictal) epileptic activity in an immediate and personalized manner upon detection of interictal epileptic activity. This technique does not produce the acute effect proposed by RNS techniques (i.e., immediate and instantaneous termination of seizures), but rather gradually alters and weakens the underlying epileptic network over time, causing it to lose its ability to generate hypersynchronous activity and induce paroxysmal discharges.

[0086] In accordance with the above, a method for intracranial neuronal electrical stimulation for treating epilepsy and other brain diseases involving epileptic seizures is provided, the method comprising the following steps in the following order: a) Surgically implanting a device comprising at least two intracranial implantable electrodes (each electrode having at least two recording contacts) into the patient’s brain parenchyma; b) Intermittent routine and emergency archiving of intracranial EEG recordings via intracranial electrodes; c) Detecting interictal epileptic discharges in intracranial EEG; d) Apply electrical stimulation pulses to each interictal discharge in an immediate and personalized manner (which may ultimately be asynchronous overall).

[0087] According to a preferred embodiment, after step (d), the above method further includes the following steps: e) Detect key discharges in critical intracranial EEGs using the electrodes; f) Detect high-risk intracranial EEG patterns and auxiliary biosignals after an attack using the electrodes; g) Utilize one or more intracranial EEG biomarkers during an attack to develop an algorithm for each patient to identify intracranial EEG patterns and changes during an attack; h) The programming parameters for intracranial neuronal electrical stimulation are individually adjusted and updated for each patient.

[0088] Neurophysiological biomarkers for detecting epileptic network neural modulation induced by chronic intracranial neuronal electrical stimulation: Example 1 Neuronal Oscillator Frequency Shift (NOFS) Index This neurophysiological marker of neural modulation focuses on changes in the neuronal oscillation frequency component in key intracranial EEGs and is therefore known as the neuronal oscillation frequency shift (NOSF) index. Figure 21 A shows the occurrence of NOSF in primitive intracranial EEG induced by chronic intracranial neuronal electrical stimulation. Figure 21 The left side of A shows a sample of intracranial EEG during an attack of neuronal oscillation frequency f(9), presented before intracranial neuronal electrical stimulation was performed. Figure 21 The right side of A shows two manifestations of NOSF, which may appear after intracranial electrical stimulation. NOSF in the upper right quadrant of intracranial episodic EEG is characterized by an increase in baseline neuronal oscillation frequency f by a coefficient a (where a > 1), thereby establishing a new, increased neuronal oscillation frequency. f mod =a*f>f(10) The lower right quadrant shows that the NOSF of intracranial episodic EEG is the baseline neuronal oscillation frequency f decreasing with a coefficient b (where b < 1), thereby establishing a new reduced neuronal oscillation frequency: f mod =b*f <f(11) The expression for the neurophysiological biomarker NOSF is: △f=ff mod It predicts two subclasses of neuronal modulation: one characterized by an increase in neuronal oscillation frequency, and the other by a decrease. The latter indicates a reduced degree of neuronal hypersynchronization in the underlying epileptogenic network due to insufficient construction of secondary epileptogenic regions, and is considered a positive / beneficial neuromodulation phenomenon. The former, on the other hand, indicates an enhanced degree of neuronal hypersynchronization in the underlying epileptogenic network due to increased construction of secondary epileptogenic regions, and is considered a negative / harmful neuromodulation phenomenon.

[0089] Example 2 Neuronal Oscillation Amplitude Shift (NOAS) Index The second neurophysiological biomarker of neural modulation involves changes in the amplitude of spike discharges in intracranial EEG during an attack, and is therefore known as the Neuronal Oscillation Amplitude Variation (NOAS) index. Figure 21 B illustrates the occurrence of NOAS in primitive intracranial EEG induced by chronic intracranial neuronal electrical stimulation. Figure 21 The left side of B shows an intracranial EEG sample during an episodic episode, exhibiting episodic spike discharges with an oscillation amplitude k (12), a phenomenon occurring before intracranial neuronal electrical stimulation. The right side shows two forms of NOAS, both of which appear after intracranial electrical stimulation. The upper right quadrant shows that NOAS in intracranial episodic EEG is a new, increased spike amplitude established by increasing the baseline spike amplitude k by a coefficient j (where j>1): k mod =j*k>k(13) NOAS in intracranial episodic EEG in the lower right quadrant is characterized by a decrease in baseline spike amplitude k with a coefficient y (y < 1), thereby establishing a new, reduced spike amplitude: k mod =y*k <k(14) The expression for the neurophysiological biomarker NOAS is: △k=kk mod It can predict two subtypes of neuronal modulation: one is characterized by an increase in neuronal oscillation amplitude, and the other by a decrease in neuronal oscillation amplitude. The former indicates enhanced neuronal hypersynchronization in the underlying epileptogenic network, which is due to the increased formation of secondary epileptogenic areas and belongs to a negative / harmful neuromodulation phenomenon; the latter indicates weakened neuronal hypersynchronization in the underlying epileptogenic network, which is due to the inadequate formation of secondary epileptogenic areas and belongs to a positive / beneficial neuromodulation phenomenon.

[0090] Example 3 Neuronal Oscillatory Density Shift (NODS) Index The third neurophysiological biomarker of neural modulation involves changes in the spike discharge density of intracranial EEG during an attack, and is therefore known as the neuronal oscillation density shift (NODS) index. Figure 21 C illustrates the occurrence of NODS in primitive intracranial EEG induced by chronic intracranial neuronal electrical stimulation. Figure 21 The left side of C shows a sample of intracranial EEG during an episodic episode with spike density i (15), which presents the morphology before intracranial neuronal electrical stimulation. The right side shows two NODS manifestations, both of which may appear after intracranial electrical stimulation. The upper right quadrant shows that the NODS of intracranial episodic EEG is established by increasing the baseline spike density i by a coefficient c (c>1), thereby establishing a new increased spike density: i mod =c*i>i(16) The lower right quadrant shows that the NODS of intracranial episodic EEG is a decrease in spike density i with a coefficient d (d<1), thus establishing a new reduced spike density: i mod =d*i <i(17) The expression form of the neurophysiological biomarker NODS is as follows: △i=i–i mod It can predict two subtypes of neuromodulation: one manifested as increased spike density, and the other as decreased spike density. The former indicates enhanced neuronal hypersynchronization in the underlying epileptogenic network, resulting from increased formation of secondary epileptogenic zones, and is a negative / harmful neuromodulation phenomenon. The latter indicates weakened neuronal hypersynchronization in the underlying epileptogenic network, resulting from insufficient formation of secondary epileptogenic zones, and is a positive / beneficial neuromodulation phenomenon.

[0091] Example 4 Neuronal Oscillation Time-Domain Sustainability (NOTS) Index The fourth neurophysiological biomarker of neural modulation involves the temporal sustainability of neuronal oscillations in key intracranial EEGs, and is therefore known as the Neuronal Oscillation Temporal Sustainability (NOTS) index. Figure 21 D shows the occurrence of NOTS in the primitive intracranial EEG induced by chronic intracranial neuronal electrical stimulation. Figure 21 The left side of D shows samples of intracranial EEG during the ictal phase, where the neuronal oscillation duration t is the duration from the onset to the termination of the neuronal oscillation during the ictal phase (18), which occurs before intracranial neuronal electrical stimulation. The right side shows three manifestations of NOTS, which can appear after intracranial electrical stimulation. The upper right quadrant shows NOTS in intracranial ictal EEG where the baseline neuronal oscillation duration t is reduced by a coefficient e (e<1) to establish a new, increased neuronal oscillation duration: t mod=e*t <t(19) The right middle quadrant shows that the NOTS of intracranial episodic EEG is the baseline neuronal oscillation duration t increasing with a coefficient g (g>1), thus establishing a new increased neuronal oscillation duration: t mod =g*t>t(20) The lower right quadrant shows that NOTS in intracranial episodic EEG represents an interruption of the episodic neuronal oscillation, the duration of which is m, a percentage of the basic neuronal oscillation duration t, where m < 1. In this case, although the total duration of the intracranial EEG phenomenon may equal the basic neuronal oscillation duration t, the overall duration of the neuronal oscillation will still be reduced: t mod =tm*t <t(21) The expression for the neurophysiological biomarker NOTs is: △t=t- t mod , It can predict three subtypes of neuronal adjustment: one is characterized by a decrease in the duration of neuronal oscillations, another by an increase in the duration of neuronal oscillations, and the third by discontinuities (interruptions) in the evolution of EEG phenomena during seizures, leading to a decrease in the total duration of neuronal oscillations. The first and third manifestations indicate that the underlying epileptogenic network fails to adequately construct secondary epileptogenic regions, resulting in a decrease in neuronal hypersynchronization, which is a positive / beneficial neuronal adjustment phenomenon. The second manifestation indicates that the underlying epileptogenic network has an increased capacity for constructing secondary epileptogenic regions, resulting in an increase in neuronal hypersynchronization, which is a negative / harmful neuronal adjustment phenomenon.

Claims

1. An intracranial neuronal electrical stimulation system for interictal epileptic activity, for treating brain diseases involving seizures, the system comprising an implantable device (35) having a central intracranial stimulation unit (22) connected via a physical intracranial interface unit (27) to at least two intracranial implantable electrodes (25), each having at least two recording contacts; wherein the electrodes may be surgically implanted into the brain parenchyma (24) of a patient (23), and the central intracranial stimulation unit (22) is configured to record continuous intracranial electroencephalography (EEG), detect patterns of interictal epileptic activity (4), and provide immediate and personalized intracranial neuronal electrical stimulation (5) upon detection of an interictal pattern.

2. The system of claim 1, wherein the implantable device (35) is interconnected with an auxiliary biosensor (26) via the physical intracranial interface unit (27), wherein the biosensor is configured to capture biomarkers for assessing high-risk epileptic activity patterns.

3. The system according to claim 1 or 2, wherein the central intracranial stimulation unit (22) further comprises an embedded computational intelligence (CI) subunit (32), the embedded CI subunit being configured to detect patterns of interictal, ictal, and optionally postictal activity in the continuous intracranial EEG, and to provide the central intracranial stimulation unit (22) with detection information of the corresponding intracranial EEG patterns.

4. The system according to claim 3, wherein the central intracranial stimulation unit (22) is configured to, upon receiving interictal intracranial EEG pattern detection information, provide electrical stimulation pulses to specific contacts of the intracranial implanted electrode in an immediate and personalized manner according to a pre-installed program.

5. The system according to any one of claims 1 to 4 further includes an external monitoring device (62) configured to receive, store and transmit intracranial EEG data, establish and update parameters of the intracranial neuronal electrical stimulation, set and refresh operating parameters of the implantable device (35), receive epileptic seizure warning information from the patient, and provide an immediate alert when a seizure pattern is detected in the intracranial EEG data.

6. The system of claim 5 further includes an external EEG neuromodulation assessment calculation system (108) configured to process the intracranial EEG data to provide a personalized assessment of neurophysiological changes in episodic EEG patterns.

7. The system of claim 6, wherein the personalized assessment of neurophysiological changes in the ictal EEG pattern comprises one or more biomarkers for assessing the neuromodulation effect of the ictal intracranial EEG, the biomarkers being selected from a set of quantifiable phenomena including neuronal oscillation frequency shift, neuronal oscillation amplitude shift, neuronal oscillation density shift, and temporal sustainability of the ictal intracranial EEG.

8. The system of claim 6 or 7, wherein the system further comprises an external computational intelligence (CI) learning and parameterization computing system (109), wherein the learning and parameterization computing system is configured to receive a combination of data related to neurophysiological changes in intracranial EEG patterns during an attack from the external EEG neuromodulation assessment computing system (108) and from the external monitoring device (62), in order to configure a personalized intracranial EEG pattern recognition algorithm for each patient based on the data.

9. The system of claim 8, wherein the external EEG neuromodulation assessment computation system (108) is configured to detect neurophysiological changes in episodic EEG patterns in the intracranial EEG data in a personalized manner for each patient based on the biomarker, and to notify the external computational intelligence (CI) learning and parameterization computation system (109) of the neurophysiological changes, thereby enabling the learning and parameterization computation system (109) to adjust and update the programming parameters of the intracranial neuronal electrical stimulation in a personalized manner for each patient.

10. The system according to any one of claims 5 to 9 further includes one or more external instant notification devices (104) wirelessly coupled to the external monitoring device (62) for notifying the patient's guardian / caregiver in the patient's surrounding environment when a seizure activity pattern and a high-risk post-seizure activity pattern are detected.

11. The system according to any one of claims 5 to 10, wherein the central intracranial stimulation unit (22) includes a bidirectional wireless communication subunit (31) wirelessly coupled to the external monitoring device (62), wherein the bidirectional wireless communication subunit (31) is configured to transmit the intracranial EEG data and / or episodic intracranial EEG pattern detection information to the external monitoring device (62), and to receive programming parameters of the CI subunit and the electrical stimulation subunit from the external monitoring device (62).

12. The system according to any one of claims 5 to 11, wherein the external monitoring device (62) includes a bidirectional wireless communication subunit (63) which is wirelessly coupled to the implantable device (35) and is configured to receive the intracranial EEG data, intracranial EEG pattern recognition data, and / or transmit programming parameters of the CI subunit and the electrical stimulation subunit to the central intracranial stimulation unit (22) of the implantable device (35).

13. The system according to any one of the preceding claims, wherein the central intracranial stimulation unit (22) further comprises a biosignal recording subunit (29), wherein the biosignal recording subunit is coupled to the intracranial implantable electrode and / or auxiliary biosensor for recording intracranial EEG and / or for recording accompanying biosignals via the intracranial implantable electrode (25).

14. The system of claim 13, wherein the biosignal recording subunit (29) is configured to intermittently archive continuous intracranial EEG recordings periodically and temporarily under the control of a programmable timer (40).

15. The system according to any one of the preceding claims, wherein the system further comprises an external non-contact battery charging device (91) configured to wirelessly couple with the central intracranial stimulation unit (22) and / or the external monitoring device (62) to charge their respective batteries (61, 83) by electromagnetic induction rather than invasively.

16. The system according to claim 15, wherein the central intracranial stimulation unit (22) and / or the external monitoring device (62) includes a non-contact battery charging module (33, 64) and a charging management subunit (59, 81), wherein the non-contact battery charging module (33, 64) is connected to the external non-contact battery charging device (91) via an induction coil system (58, 80).

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