Systems and methods for adaptive deep brain stimulation

Abstract

In some variations provided herein, the system for deep brain stimulation includes an implantable device that acquires and stores recordings of neural activity signals and applies electrical stimulation. The system also includes a personal controller device that establishes a first wireless connection to the implantable device. The personal controller device transmits power to the implantable device, and the implantable device transmits recordings of neural activity signals to the personal controller device via the first wireless connection. The system further includes a clinician programmer device that establishes a second wireless connection based on activation of the first wireless connection to receive recordings of neural activity signals from the implantable device. The clinician programmer device sets one or more stimulation parameters based on the neural activity signal recordings.

Description

Technical Field

[0001] This disclosure generally relates to the field of deep brain stimulation, and more specifically to methods and apparatus for enabling data communication and data storage for adaptive deep brain stimulation systems. Background Technology

[0002] Deep brain stimulation (DBS) systems are used in various industries, including medical diagnostics and therapeutics, due to their numerous advantages. For example, DBS delivers electrical stimulation to neural structures in a patient's central nervous system to modulate neural activity. A patient's neural activity can also be studied in conjunction with DBS. However, for safety and patient comfort reasons, DBS devices implanted in biological tissues are typically compact and therefore have limited power capacity, data processing, data storage, and communication interface capacity for operation. Furthermore, conventional DBS is usually programmed by a physician for predetermined stimulation settings. However, each patient typically exhibits symptoms, peak neural activity, and neural activity bands that differ from the standard. These patients can benefit from adaptive and patient-specific calibration. Due to the aforementioned limitations in power capacity, data processing, data storage, and communication interface capacity in known DBS systems, there remains a need for effective and efficient adaptive DBS. Therefore, new and improved systems and methods for deep brain stimulation are required. Summary of the Invention

[0003] Typically, in some variations, a system for deep brain stimulation may include an implantable device that acquires and stores recordings of neural activity signals and applies electrical stimulation. The system may also include a personal controller device that establishes a first wireless connection (e.g., Bluetooth communication) with the implantable device. The personal controller device may transmit power to the implantable device, and the implantable device may transmit recordings of neural activity signals to the personal controller device via the first wireless connection. The system may further include a clinician programmer device that establishes a second wireless connection based on activation of the first wireless connection to receive recordings of neural activity signals from the implantable device. The clinician programmer device sets stimulation parameters based on the recordings of neural activity signals. The clinician programmer device further establishes a second wireless connection (e.g., Industrial, Scientific, and Medical (ISM) communications, Short Range Device (SRD) communications, etc.) to the implantable device based on activation of the first wireless connection (e.g., during authentication of a user-input personal identification number).

[0004] In some embodiments, the power may be a sensed power sensed by the implantable device. In some embodiments, neural activity signal recordings may be automatically transmitted by the implantable device to a personal controller device during a recharging process and / or as needed.

[0005] A personal controller device typically includes a first unit and a second unit. The first unit can be removably connected to the second unit and provides power to the second unit when connected. The first unit may include memory (e.g., solid-state memory) that stores recordings of neural activity signals. The personal controller may also be configured to display an indication of the remaining power status of the implantable device or an indication of the treatment mode of the implantable device. In some variations, the personal controller may receive signals to change the treatment mode of the implantable device.

[0006] The clinician programmer device may include a custom-designed programmable electronic device, a smartphone, tablet, and / or personal computing device. In some cases, the stimulation parameter is a first stimulation parameter, and the treatment mode is a first treatment mode. The clinician programmer device may be configured to generate a second treatment mode and a second stimulation parameter. The clinician programmer device may further transmit the second treatment mode and the second stimulation parameter to an implantable device.

[0007] The system may also include a user computing device with an application program. The user computing device may be configured to receive patient log data and neural activity signal recordings. In some cases, patient log data may be recorded and / or received from an implantable device and / or a personal controller device. The user computing device may correlate patient log data with neural activity signal recordings based at least on the temporal correlation between the patient log data and the neural activity signal recordings. The user computing device may also determine dosing intervals and / or discontinuation intervals based on the neural activity signal recordings and patient log data. The user computing device may also generate stimulation parameters based on neural activity signal recordings during the dosing and discontinuation intervals. In some cases, the dosing and discontinuation intervals may be determined by the user of the user computing device (e.g., a physician, clinician, etc.). In some cases, the user may determine a threshold for classifying intervals as dosing and discontinuation intervals. For example, an interval with neural activity signal recordings having an amplitude greater than a threshold may be classified as a discontinuation interval.

[0008] In some embodiments, the user computing device may include a smartphone, tablet computer, personal computing device, etc. The user computing device and / or clinician programmer device may generate and display graphs or statistical distributions of neural activity signal recordings.

[0009] The user computing device can also be configured to extract spectral features within a frequency band of neural activity signals recorded during a predetermined time period. The user computing device can determine the dosing interval and the discontinuation interval within the predetermined time period. The user computing device can also generate a first average value of the spectral features within the dosing interval and a second average value of the spectral features within the discontinuation interval of the frequency band. The user computing device can generate stimulation parameters based on the first and second average values. The frequency band can be a low-frequency band, an alpha band, or a beta band and gamma frequency.

[0010] In some variations, stimulation parameters may include at least one of stimulation frequency, stimulation pulse width, stimulation amplitude, upper threshold of neural activity signal, and / or lower threshold of neural activity signal.

[0011] In some embodiments, neural activity signal recordings and patient log data may be time-recorded. Neural activity signal recordings may include local field potential recordings in the low-frequency band, alpha band, beta band, and / or gamma frequency band (e.g., from both hemispheres). Local field potentials may include electric field potentials, electromagnetic field potentials, magnetic field potentials, and / or other suitable field potentials. In some variations, neural activity signal recordings and log data may be continuously recorded and stored by an implantable device. In some variations, neural activity signal recordings and log data may be recorded and stored by an implantable device at discrete time intervals.

[0012] User computing devices and / or clinician programmer devices may periodically transmit neural activity signal recordings and / or patient log data or stimulation parameters to a biobank server. In some cases, user computing devices and / or clinician programmer devices may delete neural activity signal recordings and / or patient log data or stimulation parameters from their memory. Periodically clearing memory can help reduce the memory usage of user computing devices and / or clinician programmer devices.

[0013] In some variants, the clinician programmer device can establish an authenticated communication channel with a personal controller device. The personal controller device can transmit stimulation parameters (received from the clinician programmer device) to the implantable device. The personal controller device can also be configured to display an indication of the remaining power status of the implantable device or an indication of the treatment mode of the implantable device. Stimulation parameters include at least one of stimulation frequency, stimulation pulse width, stimulation amplitude, upper threshold of neural activity signal, and / or lower threshold of neural activity signal.

[0014] The clinician programmer device can receive patient log data from a user computing device and correlate the patient log data with neural activity signal recordings, at least based on the temporal correlation between the patient log data and these recordings. The neural activity signal recordings may include local field potential recordings in the low-frequency band, alpha band, beta band, and / or gamma frequency band. The clinician programmer device can then determine dosing and discontinuation intervals based on the patient log data and neural activity signal recordings received from the user computing device. The clinician programmer device can be further configured to generate stimulation parameters based on the neural activity signal recordings during the dosing and discontinuation intervals.

[0015] In some cases, the stimulation parameter is the first stimulation parameter, and the treatment mode is the first treatment mode. The clinician programmer device can be configured to generate a second treatment mode and a second stimulation parameter, and transmit the second treatment mode and the second stimulation parameter to a personal controller device. The personal controller device can then transmit the second stimulation parameter and the second treatment to the implantable device.

[0016] The clinician programmer device can also be configured to extract spectral features within a frequency band of neural activity signals recorded during a predetermined time period. The clinician programmer device can determine the dosing and discontinuation time intervals within the predetermined time period. The clinician programmer device can also generate a first average value of the spectral features within the dosing time intervals and a second average value of the spectral features within the discontinuation time intervals of the frequency band. The clinician programmer device can generate stimulation parameters based on the first and second average values.

[0017] In some embodiments, the user computing device and / or clinician programmer device can be configured to train a machine learning model based on historical neural activity signal recordings or a set of historical stimulus parameters. Once the machine learning model is trained, the user computing device and / or clinician programmer device can identify stimulus parameters by executing the machine learning model based on neural activity signal recordings.

[0018] Typically, in some variations, methods for deep brain stimulation may include receiving recordings of neural activity signals acquired over a predetermined time period. These recordings may be acquired by an implantable device, and the predetermined time period may be one day, five days, ten days, etc. The method may also include mapping the neural activity recordings to dosing and discontinuation time intervals already determined based on patient log data. The method may further include extracting spectral features within a frequency band of the neural activity recordings. The spectral features within the frequency band may include values ​​of spectral features from time intervals within the predetermined time period. The method may also include generating a first average value of the spectral features within the dosing time intervals of the frequency band within the predetermined time period and a second average value of the spectral features within the discontinuation time intervals of the frequency band within the predetermined time period. The method may further include generating stimulation parameters based on the first and second average values.

[0019] Methods for deep brain stimulation may include measuring a set of impedance values ​​from a first set of electrodes. For example, this set of impedance measurements may be performed during a drug withdrawal phase. The method may further include comparing this set of impedance values ​​to an allowable impedance range to identify a second set of electrodes having impedance values ​​within the allowable impedance range. The method may also include using the second set of electrodes to screen a set of neural activity signal recordings of the patient. The method may further include selecting a third set of electrodes that displays the highest neural activity signal recording from this set of neural activity signal recordings.

[0020] In some embodiments, the method may further include defining a minimum stimulus amplitude A that causes a detectable clinical benefit to the patient. MIN and the maximum amplitude of stimulation A before causing side effects on the patient. MAX Stimulation parameters may include minimum stimulus amplitude A. MIN and / or maximum stimulus amplitude A MAX The first average value may include the minimum β-band power value. And / or the second average value may include the maximum β-band power value. .

[0021] In some embodiments, stimulation parameters can collectively define the amplitude of brain stimulation (DBS). The DBS amplitude can typically be limited as follows:

[0022]

[0023] in, It is the power of the β band recorded by neural activity signals.

[0024] In some embodiments, the method may further include determining the peak frequency of recorded neural activity signals within a frequency band, and selecting a patient-specific frequency band based on the peak frequency. The method may also include delivering electrical stimulation according to stimulation parameters to stimulate neural tissue using an implantable device.

[0025] In some embodiments, neural activity signal recordings can typically be acquired by an implantable device. The predetermined time period can be determined based on an indication of the remaining power of the implantable device or an indication of the remaining memory of the implantable device. The method may further include transmitting the indication of the remaining power or remaining memory of the implantable device to a personal controller device, such that the indication of the remaining power or remaining memory is displayed to a user of the personal controller device via a user interface. Attached Figure Description

[0026] Figure 1 This is a block diagram of an exemplary deep brain stimulation system.

[0027] Figure 2A and Figure 2B This is a schematic description of an exemplary deep brain stimulation system.

[0028] Figure 3A This is a schematic description of an exemplary clinician programmer device.

[0029] Figure 3B This is an illustrative description of an exemplary implantation of an implantable device.

[0030] Figure 4A This is a schematic diagram of a variation of the outer casing of an implantable device.

[0031] Figure 4B This is a block diagram of an exemplary implantable device.

[0032] Figure 5 This is a block diagram of an exemplary external device for clinicians.

[0033] Figure 6A and Figure 6B This is a schematic description of an exemplary patient personal controller device.

[0034] Figure 7 This is a schematic diagram of an exemplary method for establishing a wireless connection between an implantable device and a patient's personal controller device.

[0035] Figure 8 This is a block diagram of an exemplary patient personal controller device.

[0036] Figure 9A and Figure 9B This is a schematic description of an exemplary clinician programmer device.

[0037] Figure 10 This is a block diagram of an exemplary clinician programmer device.

[0038] Figure 11 This is an exemplary method for selecting a set of sensing electrodes, a set of stimulating electrodes, and a power band.

[0039] Figure 12 This is an exemplary method for adaptive deep brain stimulation.

[0040] Figure 13 and Figure 14 This is an exemplary method for programming a programmer device for clinicians.

[0041] Figure 15A and Figure 15B These are exemplary records of neural activity signals stored and analyzed by a deep brain stimulation system.

[0042] Figure 16 This is a flowchart illustrating an exemplary communication method and data flow between supporting components of a deep brain stimulation system. Detailed Implementation

[0043] This document describes and illustrates, in conjunction with the accompanying drawings, non-limiting examples of various aspects and variations of the invention.

[0044] This document describes exemplary deep brain stimulation systems and methods suitable for highly reliable and safe deep brain stimulation. The deep brain stimulation systems and methods described herein include implantable devices, patient-person controller devices, user computing devices, and / or clinician programmer devices, which can be communicatively coupled to each other to communicate and process data for adaptive or conventional deep brain stimulation.

[0045] The one or more deep brain stimulation (DBS) systems described herein can record, store, communicate, and analyze patient neural activity signals for effective and efficient adaptive DBS. Furthermore, by dynamically adjusting patient stimulation parameters based on neural activity signal recordings, the one or more DBS systems provide adaptive deep brain stimulation (aDBS). Real-time recording, communication, and / or analysis of patient neural activity signals and aDBS (compared to conventional deep brain stimulation (cDBS)) can significantly improve the clinical outcomes of the one or more DBS systems described herein. Using aDBS in conjunction with the one or more DBS systems described herein allows for more time-oriented improvements / optimization of stimulation parameters, potentially leading to new treatment approaches and discoveries about patient conditions.

[0046] Data flow between the DBS system and its various devices

[0047] Figure 1This is a block diagram of an exemplary deep brain stimulation system 100. The deep brain stimulation system 100 includes an implantable device 101 (also referred to herein as an "implantable pulse generator (IPG) device"), a patient personal controller device 111, a user computing device 121 (also referred to herein as an "app"), and a clinician programmer device 131 (also referred to herein as a "programmer device"). The implantable device 101 is operatively coupled to the patient personal controller device 111 and the clinician programmer device. The patient personal controller device 111 is operatively coupled to the user computing device 121, and in some embodiments, may be further operatively coupled to the clinician programmer device 131. In some embodiments, the user computing device may be operatively coupled to the programmer device 131. The brain stimulation system 100 can collect data from the patient and transmit / analyze data between the implantable device 101, the patient personal controller device 111, the user computing device 121, and / or the clinician programmer device 131. It uses the implantable device 101, the patient personal controller device 111, the user computing device 121, and / or the clinician programmer device 131 to transmit / analyze data to provide deep brain stimulation to the patient, effectively utilizing the storage and processing capabilities of each device. The user computing device 121 is connected to or operatively coupled to a biobank server 160 via a network 150. Alternatively, or additionally, in some embodiments, the clinician programmer device 131 may be connected to or operatively coupled to the biobank server 160 via a network 150.

[0048] The patient personal controller device 111, user computing device 121, and / or clinician programmer device 131 may each include hardware-based computing devices and / or multimedia devices, such as smartphones, tablets, wearable devices, desktop computers, laptops, custom computing devices, etc. Furthermore, each of the patient personal controller device 111, user computing device 121, and / or clinician programmer device 131 may be plug-in powered and / or include a rechargeable battery. The implantable device 101 may be powered by a rechargeable battery, which may be powered via direct electrical connection and / or induction.

[0049] The implantable device 101 described herein is an implantable and rechargeable neurostimulator operatively coupled to a patient-person controller device 111 for initialization and / or operatively coupled to a clinician programmer device 131 for programming. The implantable device 101 includes a processor 102, a memory 103, and a communication interface 104, and can be implanted in a patient to record, store, and / or analyze a set of neural activity signals and / or further provide a set of stimuli to the patient based on a set of stimulation parameters. In some variations, the implantable device may also include a battery for storing power and / or a set of connectors (e.g., an eight-pole connector). The implantable device 101 can be connected to a deep brain stimulation (DBS) probe extension. The implantable device 101 can provide adaptive DBS (aDBS) and / or conventional DBS (cDBS) to the patient via the probe extension.

[0050] Processor 102 may include, for example, a hardware-based integrated circuit (IC) or any other suitable processing means configured to run or execute a set of instructions or a set of code. For example, processor 102 may include a general-purpose processor, a central processing unit (CPU), an accelerated processing unit (APU), an application-specific integrated circuit (ASIC), etc. Processor 102 is operatively coupled to memory 103 via a system bus (e.g., an address bus, a data bus, and / or a control bus, not shown). In some variations, processor 102 may include and / or be operatively coupled to a Vstim generator, diagnostic devices, a current controller, a waveform generator, an impedance measurement device, a signal processing controller, etc.

[0051] The memory 103 of the implantable device 101 may be, for example, a storage buffer, random access memory (RAM), read-only memory (ROM), flash memory drive, secure digital storage (SD) card, embedded multiple-programmable (MTP) memory, embedded multimedia card (eMMC), universal flash storage (UFS) device, etc. The memory 103 may store, for example, one or more codes, including instructions that cause the processor 102 to perform one or more processes or functions (e.g., recording the set of neural activity signals, generating a set of pulse signals, etc.).

[0052] The communication interface 104 of the implantable device 101 may be a hardware component of the first computing device 101 operatively coupled to the processor 102 and / or the memory 103. The communication interface 104 may be operatively coupled to and used by the processor 102. The communication interface 104 may be, for example, a network interface card (NIC), Wi-Fi... TMModules, Bluetooth® modules, optical communication modules, and / or any other suitable wired and / or wireless communication interfaces (i.e., Wireless Medical Telemetry Service (WMTS); Medical Device Radio Communication Service (MedRadio), Medical Implantable Communication Service (MICS), Medical Micropower Network (MNN), Medical Body Area Network (MBAN), etc.). Communication interface 104 can be configured to connect implantable device 101 to patient personal controller device 111, user computing device 121, and / or clinician programmer device 131, as described in further detail herein. In some cases, communication interface 104 can facilitate the reception of sets of neural activity signal recordings and / or stimulation parameters from, or the patient personal controller device 111, user computing device 121, and / or clinician programmer device 131, all of which are communicatively connected to implantable device 101. In some cases, data received via communication interface 104 can be processed by processor 102 or stored in memory 103, as described in further detail herein.

[0053] The patient-person controller device 111 described herein can establish a first wireless connection (RF wireless connection) to the implantable device 101 and / or provide power (induced electrical power, radio frequency (RF) power harvesting, etc.) to the implantable device 101 for operation. The patient-person controller device 111 can receive / transmit data (e.g., neural activity signal recordings, a set of stimulation parameters, etc.) to the implantable device 101 via the first wireless connection. The patient-person controller device 111 includes a processor 112, a memory 113, and a communication interface 114, which may be structurally and / or functionally similar to processor 102, memory 103, and communication interface 104, respectively. In some cases, the patient-person controller device 111 can receive a set of neural activity signal recordings from the implantable device 101 via the communication interface 114 and store the set of neural activity signal recordings in the memory 113. In some variations, the patient personal controller device 111 may include a first component and a second component, both having a processor, memory, and communication interface structurally and / or functionally similar to the processor 102, memory 103, and communication interface 104. The first component may be used to recharge the implantable device 101, and the second component may be used to connect to the first component and provide power to the first component.

[0054] User computing device 121 includes a processor 122, a memory 123, and a communication interface 124, which are structurally and / or functionally similar to processor 102, memory 103, and communication interface 104, respectively. In some cases, user computing device 121 may be a personal device, such as a mobile phone, tablet computer, computing device, watch, virtual reality device, etc. User computing device 121 may include an application program (not shown), which is received as software from communication interface 124, stored in memory 123, and executed by processor 122. For example, code that enables the processor to analyze a set of neural activity data recordings. Alternatively, the application program may be a hardware-based device that can be attached to user computing device 121. For example, an integrated circuit (IC) that enables user computing device 121 to analyze a set of neural activity data recordings.

[0055] The user computing device 121 described herein can be connected to and / or operatively coupled to the patient personal controller device 111 to receive and / or transmit data including recordings of neural activity signals. In some cases, the user computing device 121 can receive and store patient log data. The patient log data can be received from users of the patient personal controller device 111 and / or the user computing device 121 (e.g., the patient, the patient's guardian, the patient's AI personal assistant, etc.) and may include, for example, sequential / time-based descriptions of events (e.g., hourly, daily, weekly, etc.), medication consumption history, etc.

[0056] The application of the user computing device 121 can correlate patient log data with neural activity signal recordings based at least on the temporal correlation between the patient log data and the recordings. The user computing device 121 can also determine a set of dosing intervals and a set of discontinuation intervals based on the neural activity signal recordings and the patient log data. The application can also generate stimulation parameters based on neural activity signal recordings during the set of dosing and discontinuation intervals.

[0057] In some variations, the application may be included in or implemented within the patient personal controller device 111 and / or the clinician programmer device 131. For example, the patient personal controller 111 may receive data including a set of neural activity data records from the implantable device 101 and patient log data from the user of the patient personal controller device 111. The patient personal controller 111 may then determine a set of dosing and discontinuation intervals based on the set of neural activity data records and the patient log data. In some variations, the application may be implemented in a web service provider and accessed via an application programming interface (API) downloaded and / or installed on the user device 121, the patient personal controller device 111, and / or the clinician programmer device 131.

[0058] The clinician programmer device 131 includes a processor 132, a memory 133, and a communication interface 134, which may be structurally and / or functionally similar to processor 102, memory 103, and communication interface 104, respectively. The clinician programmer device 131 can establish a second wireless connection (RF wireless connection) to the implantable device 101 based on the activation of a first wireless connection. The clinician programmer device 131 can store and analyze a set of neural activity signal recordings to provide stimulation / treatment patterns (i.e., cDBS treatment planning patterns, aDBS treatment patterns) to the implantable device 101. The clinician programmer device can be used to program the implantable device 101. The clinician programmable device 131 can be connected to or operatively coupled (e.g., via a 2.5 GHz radio frequency (RF) communication protocol) to the implantable device 101 to receive a set of neural activity signal recordings from the implantable device 101 and / or transmit a set of stimulation parameters to the implantable device 101.

[0059] In one example, the implantable device 101 may initially include a first set of stimulation parameters and a first treatment mode, and record a set of neural activity signals (e.g., local field potentials (LFP)). The first treatment mode may include, for example, a schedule to provide stimulation based on the first stimulation parameters. The implantable device 101 may transmit this set of neural activity signal recordings to a clinician programmer device 131. A clinician (e.g., a doctor, nurse, etc.) using the clinician programmer device 131 may then determine and / or provide a second set of stimulation parameters and / or a second treatment mode based on the set of neural activity signal recordings received from the implantable device 101. The clinician programmer device 131 may transmit the second treatment mode and / or the second set of stimulation parameters to the implantable device 101.

[0060] In some embodiments, the second wireless connection may be an authenticated wireless connection. For example, the second wireless connection may be established only after the user of the clinician programmer device 131 enters a personal identification number (PIN). In some cases, authentication of the second wireless connection occurs after the implantable device 101 and the clinician programmer device 131 exchange keys.

[0061] In some variations, without establishing a second wireless connection with the implantable device 101, the clinician programmer device 131 can receive recordings of neural activity signals from the implantable device 101 based on the activation of the first wireless connection. In such variations, the clinician programmer device 131 can provide treatment modes to the implantable device 101 via the patient personal controller device 111.

[0062] In some variations, the clinician programmer device 131 can be connected to and / or operatively coupled to an external clinician device for impedance measurement of externalized probe extensions in the operating room. Impedance measurement may involve measuring resistance, capacitance, inductance, etc. The clinician programmer device 131 can also format impedance values ​​by normalizing them to a common / normalized scale, analyze impedance values, and / or display impedance values ​​to the user of the clinician programmer device 131.

[0063] Network 150 may be a digital telecommunications network of servers and / or computing devices. Servers and / or computing devices on the network may be connected via one or more wired or wireless communication networks (not shown) to share resources such as data storage, connectivity services, and / or computing power. The wired or wireless communication networks between servers and / or computing devices in Network 150 may include one or more communication channels, such as radio frequency (RF) communication channels, extremely low frequency (ELF) communication channels, ultra-low frequency (ULF) communication channels, low frequency (LF) communication channels, intermediate frequency (MF) communication channels, ultra-high frequency (UHF) communication channels, extremely high frequency (EHF) communication channels, fiber optic communication channels, electronic communication channels, satellite communication channels, etc. Network 150 may include, for example, the Internet, intranets, local area networks (LANs), wide area networks (WANs), metropolitan area networks (MANs), WiMAX® (Global Interoperability Microwave Access Network), virtual networks, any other suitable communication systems, and / or combinations of such networks.

[0064] Biobank server 160 may include a server and / or computing device operatively coupled to user computing device 121 and / or programmer device 131 via network 150. Biobank server 160 may provide data storage to user computing device 121 and / or programmer device 131. In some embodiments, in addition to data storage, biobank server 160 may also provide connectivity and / or computing services to user computing device 121 and / or programmer device 131. In some variations, biobank server 160 may include and / or perform cloud-based services, such as Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS), etc. In some cases, biobank server 160 receives, processes, and stores neural activity data records, patient log data, and / or stimulation parameters. In some embodiments, biobank server 160 generates a timestamped version of each of a set of neural activity data records, patient log data, and / or a set of stimulation parameters before storing them in a database (e.g., a Structured Query Language (SQL) database).

[0065] like Figure 1 As shown, the deep brain stimulation system 100 may include an implantable device 101 that acquires and stores neural activity signal recordings and applies electrical stimulation. The deep brain stimulation system 100 also includes a patient personal controller device 111 that establishes a wireless connection with the implantable device 101 to receive neural activity signal recordings and recharge the battery of the implantable device 101. The patient personal controller device transmits power to the implantable device, and the implantable device transmits neural activity signal recordings to the patient personal controller device via the wireless connection. The patient personal controller device 111 may be operatively coupled (e.g., via Bluetooth, WiFi, etc.) to a user computing device 121 and transmit neural activity signal recordings and / or patient log data to the user computing device 121. The user computing device 121 analyzes the neural activity signal recordings and / or patient log data to determine dosing and discontinuation intervals based on the neural activity signal recordings and generates a set of stimulation parameters. The deep brain stimulation system 100 also includes a clinician programmer device 131, which establishes a second wireless connection with the implantable device 101 based on the activation of a first wireless connection, receives neural activity signal recordings, and sets multiple stimulation parameters based on the neural activity signal recordings. The user computing device 121 can also be configured to connect to the network 150 via a network connection (e.g., WiFi connection, 5G network connection, etc.) and transmit neural activity signal recordings, patient log data, and / or stimulation parameters to the biobank server 160 via the network 150.

[0066] In some cases, the user computing device 121 includes a graphical user interface (GUI), and displays a graph or statistical distribution of the neural activity signal recordings via the GUI of the user computing device 121. The statistical distribution of the neural activity recordings may include, for example, a moving average, a daily average, a weekly average, the variance of the distribution of the neural activity recordings, local maxima, local minima, global maxima, global minima, etc.

[0067] In some cases, to determine the dosing and discontinuation intervals, the user computing device 121 processes (e.g., extracts, displays, etc.) a set of spectral features within a frequency band of neural activity signals recorded during a predetermined time period. The frequency band may include a low-frequency band, an alpha band, a beta band, and / or a gamma frequency, etc. The user computing device 121 may also generate a first average value of the set of spectral features within the dosing interval of the frequency band and a second average value of the set of spectral features within the discontinuation interval of the frequency band. The user computing device 121 may generate stimulation parameters based on the first and second average values.

[0068] In some embodiments, a patient identification card is provided to the user of the deep brain stimulation system 100. The patient identification card may include information about the user, including models of a set of devices of the deep brain stimulation system 100, a set of names for the set of devices, a set of serial numbers for the set of devices, patient identification information, the date of implantation of the implantable device 101 in the user's body, information about the treating clinician (name, phone number, qualifications, licenses, etc.), information about the manufacturer, notes on whether the patient has the implantable device 101 or any other implantable device, notes on whether the patient can undergo diathermy, notes on whether magnetic resonance imaging (MRI) is contraindicated, general safety information, patient-specific safety information, the patient's medical history, etc. In some cases, the patient identification card may be stored in an application on the implantable device 101, the patient controller device 111, and / or the user computing device 121.

[0069] In some embodiments, the clinician programmer device 131 is not operatively coupled to the implantable device 101, and the patient personal controller device 111 may be operatively coupled (e.g., via Bluetooth, WiFi, etc.) to the clinician programmer device 131 and transmit neural activity signal recordings and / or patient log data to the clinician programmer device 131. In such embodiments, the clinician programmer device 131 analyzes the neural activity signal recordings and / or patient log data to determine dosing and discontinuation intervals based on the neural activity signal recordings and to generate a set of stimulation parameters. The clinician programmer device 131 may also be configured to connect to a network 150 via a network connection (e.g., WiFi, etc.) and transmit neural activity signal recordings, patient log data, and / or stimulation parameters to a biobank server 160 via the network 150.

[0070] In some variations, a cDBS treatment mode may be used in addition to the aDBS treatment mode. For example, a month's worth of monitoring / observation of neural activity data recordings (e.g., local field potential activity stored as a numerical time series) may be stored in the patient controller and / or implantable device 101 and then transmitted to the user computing device 121 and / or the clinician programmer device 131 for analysis. The user computing device 121 and / or the clinician programmer device 131 may then generate a set of stimulation parameters and an aDBS treatment mode and transmit them to the patient controller and / or implantable device 101 for use.

[0071] Figure 2A and Figure 2B This is a schematic description based on some variants of exemplary deep brain stimulation systems. For example... Figure 2AAs shown, a deep brain stimulation system may include an implantable device (also known as an IPG), a patient personal controller device (also known as a personal controller), a user computing device, and a clinician programmer device (also known as a "clinician programmer"). The IPG can acquire and store recordings of the patient's neural activity signals and apply electrical stimulation to the patient. The personal controller establishes a wireless connection to the IPG, receives the neural activity signal recordings, and recharges the IPG's battery. The personal controller transmits power to the IPG (e.g., via an induction coil), and the IPG transmits neural activity signal recordings to the personal controller via a wireless connection. The personal controller may be operatively coupled (e.g., via Bluetooth, WiFi, etc.) to the user computing device and transmit the neural activity signal recordings and / or patient log data to the user computing device. The user computing device analyzes the neural activity signal recordings and / or patient log data to determine dosing and discontinuation intervals based on the neural activity signal recordings and generate a set of stimulation parameters. The user computing device may also be configured to connect to a network and transmit neural activity signal recordings, patient log data, and / or stimulation parameters to a biobank server. The clinician programmer establishes a second wireless connection with the IPG based on the activation of the first wireless connection, receives neural activity signal recordings, and sets stimulation parameters based on the neural activity signal recordings.

[0072] like Figure 2B As shown, the deep brain stimulation system may include an IPG, a personal controller, and a clinician programmer. The IPG can acquire and store recordings of the patient's neural activity signals and apply electrical stimulation to the patient. The personal controller establishes a wireless connection with the IPG, receives the neural activity signal recordings, and recharges the IPG's battery. The personal controller can be operatively coupled (e.g., via Bluetooth, WiFi, etc.) to the clinician programmer device and transmit the neural activity signal recordings and / or patient log data to the clinician programmer device. The clinician programmer device can analyze the neural activity signal recordings and / or patient log data to determine dosing and discontinuation intervals based on the neural activity signal recordings and generate a set of stimulation parameters. The clinician programmer device can connect to a network and transmit the neural activity signal recordings, patient log data, and / or stimulation parameters to a biobank server.

[0073] Figure 3AThis is a schematic description of a variant of a deep brain stimulation (DBS) system. The DBS system may include an IPG 314, a patient controller device 321, and a clinician programmer device 322. The IPG 314 may be operatively connected to a patient 301 via an implantable probe 302, a drill cap 303, and a probe extension 304 to record neural activity signals and provide stimulation to the patient 301. The IPG 314 may record and store neural activity signals from the patient 301 and is operatively coupled to the patient controller device 321 and the clinician programmer device 322. In some cases, the patient may wear a T-shirt that facilitates alignment of the patient controller device 321 with the IPG 314 for data communication and power sensing. The patient controller device 321 may store the neural activity signal recordings from the IPG 314 and provide power to the IPG 314. In some cases, the neural activity signal recordings are removed from the IPG's memory once they have been transmitted to the patient controller device 321. The clinician programmer 322 can also receive neural activity signal recordings from the IPG 314 and set stimulation parameters to the IPG 314 based on the neural activity signal recordings.

[0074] Figure 3B This is a schematic description of a variant of a deep brain stimulation (DBS) system that can be used to implant one or more probes into a patient. The DBS system can be used by clinicians for open stimulation procedures (e.g., in hospitals, doctors' offices, etc.). During an open stimulation procedure, the DBS system can be configured to include a clinician external device 323 connected to a probe extension 304 via a probe adapter 305. The clinician external device 323 can generate a set of stimuli to be transmitted to the patient 301 and record and store neural activity signals in a memory (not shown) of the clinician external device 323. The clinician external device 323 can be operatively coupled to a clinician programmer device 322 and transmit the recorded neural activity signals to the clinician programmer device 322.

[0075] Figure 4A This is a schematic diagram of a variant of the housing of an implantable device. Since the implantable device (also referred to herein as an "implantable pulse generator (IPG) device") can be implanted into the patient's body, it can be compact and have a small volume (e.g., 10cc, 20cc, 30cc, etc.) and / or weight (20g, 30g, etc.). Figure 4B This is a block diagram of a variant of the implantable device. The implantable device 400B includes a memory 401, an RF chip 402, a battery charger 403, and a V... stimGenerator 404 and main controller 430. Implantable device 400B may also include diagnostic device 405, current controller 411, waveform generator 412, impedance measurement device 413, probe 421, REC electrode selector, signal processing controller 423, sensing device power regulator 424, and local field potential (LFP) sensing device 425.

[0076] The memory 401 can store data including a set of neural activity recordings, a set of stimulation parameters, etc. The RF chip 402 can process incoming electromagnetic waves and / or process a set of electrical signals received from the main controller 430 to generate outgoing electromagnetic waves. The battery charger 403 may include a set of circuitry to provide power and charge the battery of the implantable device 400B. stim Generator 404 can generate stimulation voltage dynamics. Main controller 430 may include, for example, a hardware-based integrated circuit (IC) or any other suitable processing device configured to run or execute a set of instructions / code. For example, main controller 430 may include a general-purpose processor, central processing unit (CPU), application-specific integrated circuit (ASIC), microcontroller, etc. Main controller 430 can be operatively coupled to and transmit a set of instructions (e.g., via a set of circuitry) to memory 401, RF chip 402, battery charger 403, V... stim Generator 404, diagnostic device 405, current controller 411, waveform generator 412, impedance measuring device 413, probe 421, REC electrode selector, signal processing controller 423, sensing device power regulator 424, LFP sensing device 425.

[0077] In some embodiments, the implantable device 400B may be initialized by a patient-person controller device. The patient-person controller device may be operatively coupled to the implantable device 400B to initiate the implantable device 400B by setting an initial set of parameters (e.g., a set of cDBS parameters for initial treatment and / or collection of neural activity signal recording data). In some embodiments, the implantable device may be programmed by a clinician programmer device. The clinician programmer device may be operatively coupled to the implantable device 400B to program the implantable device 400B using a set of stimulation parameters (e.g., a set of aDBS parameters for collection of neural activity signal recording data and / or patient-specific and adaptive treatment).

[0078] Figure 5 This is a block diagram of an exemplary clinician external device 500 based on some variations. The clinician external device 500 (such as...) Figure 3BThe clinician external device shown and described is an external device for performing impedance measurements from an externalized probe extension in the operating room, and can be used by a clinician (e.g., physician, nurse, etc.) on the day of implantation to confirm that the electrode is correctly placed. The clinician external device 500 may include an RF antenna 501, a memory 502, an RF chip 503, a power device 504, a display 511 (e.g., an LCD monitor), a buzzer 512, an impedance measurement unit 521, a multiplexer 522, a stimulation device 523, a diagnostic device 531, a filtering and amplification device 533, and a control device 540.

[0079] Figure 6A and Figure 6B This is a schematic diagram of a sub-component of an exemplary patient personal controller device. The patient personal controller device (e.g.) Figure 1 The patient controller device 111 shown and described may include two sub-components: a recharger unit for recharging the implantable device ( Figure 6B ) and a portable power source that can be connected to a recharger unit via cable and provide power to it. Figure 6A In some embodiments, each of the recharger unit and the power bank may be structurally and / or functionally similar to, respectively, the description of, the recharger unit and the power bank. Figure 1 The processor 102, memory 103, and communication interface 104 shown and described are described. The recharger unit can receive a set of neural activity signal recordings from the implantable device through the communication channel between the two, and store the received set of neural activity signal recordings in the memory of the recharger unit. The recharger unit can transmit the set of neural activity signal recordings to the memory of the mobile power supply.

[0080] The recharging unit can establish a communication channel with the implantable device (e.g., via a radio frequency (RF) communication channel) to turn the implantable device on or off and / or check the remaining battery level of the implantable device. The power bank may include a user interface, including a graphical user interface (GUI) to display information to the user of the patient personal controller device and / or a set of buttons to receive commands from the user. Status updates of the remaining battery level (remaining charge level) of the implantable device, the recharging unit, and / or the power bank may be displayed on the GUI of the power bank. Furthermore, status updates of the treatment status and notifications of any malfunctions may be displayed on the GUI. In some cases, the power bank and / or the recharging unit may generate warning signs to notify of malfunctions and / or low battery levels. In some cases, the recharging unit may be used to initialize / activate the implantable device. Initialization / activation may involve setting an initial set of charging power and / or stimulation parameters for the implantable device. Similarly, the recharging unit may be used to deactivate / shut down the implantable device.

[0081] Figure 7 This is a schematic diagram of an exemplary method for establishing a wireless connection between an implantable device (also referred to herein as an "implantable pulse generator (IPG) device") and a patient personal controller device. The patient personal controller device can wirelessly transmit power to charge the IPG. Alternatively or additionally, the IPG device can transmit or receive neural activity signal recordings and / or stimulation parameters to or from the patient personal controller device. For example, the IPG can wirelessly transmit neural activity signal recordings to the patient personal controller device, and the personal controller device can wirelessly transmit stimulation parameters or instructions to the IPG. In some cases, a wireless connection can be established between the patient personal controller device and the implantable device (e.g., a recharger unit of the patient personal controller device) when the patient personal controller device and the implantable device are within a predetermined distance range (e.g., 2 cm to 10 cm, 1 mm to 1 m, etc.) and orientation range. The orientation range can refer to, for example, the alignment of the vertical orientation of the patient personal controller device with the vertical orientation of the implantable device within a 5-degree rotation error tolerance, 10-degree rotation error tolerance, etc.

[0082] Figure 8 This is a block diagram of a variant of the patient personal controller device 800 (such as regarding...). Figure 1 The patient-personal controller device shown and described. The patient can use the patient-personal controller device 800 to charge the implantable device and / or download neural activity signal data recorded by the implantable device (as shown in Figure 6 and...). Figure 7 (As shown and described). The patient personal controller device 800 includes an antenna 801 (e.g., a 2.4 GHz RF antenna), a memory 802 (e.g., a secure digital (SD) card memory), an RF chip 803, an induction coil 811, a button 812, a power regulator 813, a main controller 820, and a Bluetooth controller 814.

[0083] The antenna can transmit and receive input electromagnetic waves representing data, which may include a set of neural activity recordings, a set of stimulation parameters, etc. The RF chip 803 can process the input electromagnetic waves received by the antenna and / or process a set of electrical signals received from the main controller 820 to generate output electromagnetic waves. The memory 802 can store data including a set of neural activity recordings, a set of stimulation parameters, etc. The induction coil 811 can generate magnetic flux to sense power to the implantable device (not shown). The button 812 can be activated by a user of the patient personal controller device 800 to start, activate / deactivate, and / or establish communication with the implantable device. The power regulator 813 may include a set of electrical and / or electronic circuitry to regulate the characteristics of the power sensed by the implantable device via the induction coil 811. The Bluetooth controller 814 may include a set of electrical, electronic, and / or RF circuitry to process and / or generate a set of Bluetooth signals. The main controller 820 may include, for example, a hardware-based integrated circuit (IC) or any other suitable processing device configured to run or execute a set of instructions / code. For example, the main controller 820 may include a general-purpose processor, a central processing unit (CPU), an application-specific integrated circuit (ASIC), a microcontroller, etc. The main controller 820 may be operatively coupled to and generate a set of instructions to a memory 802, an RF chip 803, an induction coil 811, a button 812, a power regulator 813, and / or a Bluetooth controller 814.

[0084] Figure 9A and Figure 9B It is an exemplary clinician programmer device (such as regarding Figure 1 A schematic description of the clinician programmer device 131 shown and described. Figure 9A As shown, the clinician programmer device may include a graphical user interface (GUI). In some cases, the GUI may be a touchscreen panel, allowing users of the clinician programmer device (e.g., clinicians, physicians, nurses, etc.) to interact with the clinician programmer device via the GUI.

[0085] The clinician programmer device may include / implement various software applications, including: a connection application for checking the connection status with other devices, a stimulation application for providing stimulation to the patient, and / or a recording application for recording neural activity received from the implantable device and / or the patient's personal controller device. The clinician programmer device may further include / implement a treatment application for setting treatment modes by the user of the clinician programmer device, an impedance application for measuring and setting a set of impedances operatively coupled to electrodes of the clinician programmer device, and / or other suitable applications for the clinician programmer device (e.g., patient information card applications, operating system version information, date / time applications, memory applications, processor applications, etc.).

[0086] like Figure 9B As shown, the clinician programmer device may include a panel interface (e.g., a rear panel interface, a top panel interface, etc.). In some cases, the panel interface may include a power button and / or an antenna, the power button for turning the clinician programmer device on / off, and the antenna for receiving and / or transmitting electromagnetic waves representing data from an implantable device, a patient personal controller device, a network (e.g., the Internet), etc. The panel interface may further include a power plug port for receiving power from alternating current (AC) and / or direct current (DC) power and for charging the battery of the clinician programmer device. The panel interface may provide a universal serial bus (USB) type port for connection to an external host.

[0087] Figure 10 This is a block diagram of an exemplary clinician programmer device 1000, which includes a memory 1001 (e.g., an electrically erasable programmable read-only memory (EEPROM) memory), an RF chip 1002, an antenna 1003 (e.g., an RF antenna), a touch screen 1011, a battery charger 1012, a main controller 1030, and a USB to UART converter 1021, and can be connected to an external host 1022.

[0088] Antenna 1003 can transmit and receive input electromagnetic waves representing data, which may include a set of neural activity recordings, a set of stimulation parameters, etc. RF chip 1002 can process the input electromagnetic waves received by the antenna and / or process a set of electrical signals received from the main controller 1030 to generate output electromagnetic waves. Memory 1001 can store data including a set of neural activity recordings, a set of stimulation parameters, etc. Battery charger 1012 may include a set of circuitry to provide power and charge the battery of the clinician programmer device 1000. Touchscreen 1011 can display a set of images to the user of the clinician programmer device 1000 and receive a set of commands from the user by touching the touchscreen 1011. USB to UART converter 1021 can convert Universal Asynchronous Receiver-Transmitter (UART) port communication to Universal Serial Bus (USB) port communication for engagement with an external host 1022 (e.g., a laptop, desktop computer, etc.). Main controller 1030 may include, for example, a hardware-based integrated circuit (IC) or any other suitable processing device configured to run or execute a set of instructions / code. For example, the main controller 1030 may include a general-purpose processor, a central processing unit (CPU), an application-specific integrated circuit (ASIC), a microcontroller, etc. The main controller 1030 may be operatively coupled to and generate a set of instructions to a memory 1001, an RF chip 1002, an antenna 1003, a touch screen 1011, a battery charger 1012, the main controller 1030, a USB to UART converter 1021, and / or an external host 1022.

[0089] Methods for Adaptive Deep Brain Stimulation (aDBS) Programming

[0090] This paper describes an implantable device (also referred to herein as an "implantable pulse generator (IPG) device") that can provide adaptive deep brain stimulation (aDBS) and / or conventional deep brain stimulation (cDBS). The aDBS mode can modify a set of stimulation parameters in real time based on a set of control variables and the patient's neural activity. More specifically, in the aDBS mode, the IPG device records neural activity signals (e.g., local field potentials) from one or more electrodes of a deep brain stimulation (DBS) probe. The IPG device can then store the neural activity signal recordings as a sample / digital representation of neural activity. The IPG device can also be configured to extract neural activity signal recordings in specific frequency bands (e.g., alpha band, beta band, 12 Hz to 35 Hz, etc.) and adapt the set of stimulation parameters (e.g., stimulation amplitude, stimulation pulse width, etc.) based on a linear relationship. The power of the beta oscillation can be linearly correlated with the patient's clinical state. In other words, a neural activity signal recording with a higher beta power value may indicate a poorer clinical state and therefore may require a higher stimulation amplitude. However, when implemented quantitatively in an IPG device, such linearity may need to be calibrated in a patient-specific manner. Therefore, patient-specific symptom-controlled deep brain stimulation devices may be beneficial.

[0091] When the aDBS mode is activated on the IPG device, the amplitude of deep brain stimulation (DBS) is controlled by the deep brain stimulation system (such as those related to...) Figure 1 The deep brain stimulation system 100 shown and described is automatically determined / set based on neural activity signals recorded by DBS electrodes. More specifically, the aDBS mode modulates the stimulation amplitude after the power of local field potential (LFP) oscillations in a specific frequency band, such as the β band (10-35 Hz). Specific patients may have different center frequencies and different β power values ​​in the β band. Furthermore, specific patients may have different responses to DBS and require specific stimulation intensities to control specific patient-specific symptoms. Therefore, in order to correctly set the aDBS mode, the treating clinician can define a set of parameters, including:

[0092] · The average minimum power achieved by β-band oscillations in a specific patient (also referred to as the first average in this paper) (this is often associated with medication status).

[0093] · The average maximum power achieved by β-band oscillations in a specific patient (also referred to as the second average in this paper) (this is often associated with discontinuation of medication).

[0094] ·A min The minimum DBS amplitude that elicits a detectable clinical effect in a specific patient.

[0095] ·A max The maximum DBS amplitude before causing side effects in a specific patient.

[0096] ·V DBS DBS amplitude output.

[0097] This set of parameters allows for the calibration of the aDBS mode:

[0098]

[0099] in It is the power (or amplitude) of the neural activity signal in the β band, which can be measured by electrodes on the implanted probe.

[0100] Figure 11 This is a method 1100 for selecting a set of sensing electrodes, a set of stimulating electrodes, and a power band. At 1101, method 1100 includes examining the impedance of a set of electrode pairs and excluding subgroups of electrode pairs with abnormal impedance values. At 1102, method 1100 further includes screening the power spectrum of a set of neural activities (e.g., local field potential (LFP) activity) on the remaining electrode pairs. At 1103, method 1100 further includes titrating the treatment window and defining A. max and A min When the patient is not taking medication, A can be measured. max and A min At 1104, method 1100 further includes selecting an electrode pair, in addition to the stimulating electrode, for sensing and displaying the highest β activity. In some cases, A can be determined while the patient is taking medication. max and A min .

[0101] In some embodiments, a clinician programmer device (such as regarding) can be used. Figure 1 The programmer device 131 shown and described) and / or the use of a user computing device (such as a programmer device 131) and / or a user computing device (such as a programmer device 131) are shown and described. Figure 1 The user computing device 121 shown and described implements method 1100. The clinician programmer device can be configured to check the impedance of all available electrode pairs. Alternatively or additionally, an external clinician device can also be used to perform electrode impedance checks during probe implantation. Each electrode whose impedance exceeds a permissible impedance range (e.g., a permissible impedance range of 500 ohms to 2000 ohms) is stored in the memory of the clinician programmer device (stored as per...). Figure 1(In the memory 133 of the programmer device 131 shown and described). Such electrodes with impedance exceeding the permissible impedance range are excluded for stimulation and / or recording. When the patient is in a drug-free state, the clinician programmer device performs a short (e.g., 10 to 30 seconds, etc.) recording of a set of neural activities (e.g., LFP activity) for each available electrode pair (excluding electrode pairs with abnormal impedance values). To ensure proper recording conditions, it is recommended to perform a short recording of a set of neural activities when the patient is in a drug-free state, where Parkinson's symptoms are predominant (e.g., after overnight stimulation and drug withdrawal). The clinician programmer device can be configured to view the characteristics of a short recording of a set of neural activities in a treatment window (e.g., a predetermined frequency domain). The treatment window typically shows oscillatory activity characterizing a short recording of a set of neural activities. In some cases, oscillatory activity is identified by peaks in the treatment window of a short recording of a set of neural activities. Peaks can be characterized by intensity (also referred to herein as "spectral power") and can be reported / displayed in the clinician programmer device. The clinician programmer device also stores peak frequencies (i.e., frequencies with the highest values ​​in the power spectrum) and power spectra associated with short recordings of a set of neural activities. The clinician programmer device performs the above process for each available electrode pair (bilateral).

[0102] A clinician programmer device can be configured to select a set of electrodes on one or more implantable probes, allowing for optimal control of patient-specific symptoms with minimal side effects (i.e., clinical outcomes) and low energy delivery to patient tissue. Each electrode may include broadband spectral characteristics and can record neural activity signals with a broad spectral range. The clinician programmer device can use the selected electrodes even if the selected electrodes have been identified for short-term recording of a set of neural activities. The clinician programmer device can further define A associated with the selected electrodes. min (The minimum clinical benefit to the patient) and A max (The maximum amplitude before causing side effects). The clinician programmer device can... min and / or A maxThe information is stored in the memory of the clinician programmer device. The clinician programmer device can be further configured to identify electrode pairs with the strongest beta band components (excluding electrode pairs selected for stimulation and electrodes with abnormal impedance) that have the highest power in the beta band (e.g., between 10 Hz and 35 Hz). Although the beta band is generally understood to be in the range of ~10–30 Hz, patient-specific beta bands can vary between patients and can be determined by the deep brain stimulation system to personalize the aDBS pattern for the patient. This is because the peak power of neural activity signals (also known as “patient-specific power”) can occur at different frequencies for each patient. For example, patient A may have more activity at 15 Hz than at 25 Hz, patient B may have peak activity at 20 Hz but much lower activity at other frequencies in the beta band, patient C may have more activity at 30 Hz than at 10 Hz, and so on. The clinician programmer device can be configured to determine and / or select a range / boundary (+ / -2 Hz, + / -3 Hz, etc.) for a patient-specific frequency band. For example, a patient-specific β band could be + / -2 Hz around the β peak measured by the patient.

[0103] An implantable pulse generator (IPG) device acquires and / or stores recordings of neural activity signals, such as local field potentials (LFPs) over a predetermined time period. The predetermined time period can be determined by the clinician and, in some variations, can be approximately 1 week, 2 weeks, 20 weeks, 1 day, 10 days, 15 days, 30 days, 45 days, 60 days, etc. The IPG device acquires neural activity signals over the predetermined time period, which can be stored as neural activity signal recordings in the memory of the IPG device. The IPG and / or any external device described herein (e.g., a patient controller device, a programmer device, etc.) can calculate a first average value based on the neural activity signal recordings from the IPG. Second average Neural activity signals are recorded from at least one electrode in the electrode pair selected above, for sensing and displaying the selected highest β activity. Specifically, in non-volatile memory (such as regarding...) Figure 1In the memory 103 of the implantable device 101 shown and described, the IPG device stores spectral features of neural activity signal recordings over a predetermined time period. In some cases, the length of each predetermined time period T can be determined based on the memory space of the memory (e.g., 100 MB, 1 GB, 4 GB, 8 GB, 128 GB, etc.). In such cases, a shorter predetermined time period T is allocated to a larger storage space for better temporal resolution of the data. In some cases, in addition to the spectral features of neural activity signal recordings, the IPG device may also store patient-specific power from patient-specific frequency bands selected above. The value of the patient-specific power from the patient-specific frequency band should be specified for each patient-specific predetermined time period. T' Storage. In some cases, patients are required to store data for a specific pre-determined time period. T' The settings can be configured by a physician and determined based on the spectral characteristics of the neural activity signal recordings, and / or predetermined (e.g., based on total and / or remaining data storage capacity, total and / or remaining battery capacity, a balance between battery power consumption and data temporal resolution, a balance between data storage capacity and data temporal resolution, etc.). For example, neural activity signal recordings can be performed at each time... T1 The spectrum peaks or troughs are displayed on average; therefore, the patient's specific predetermined time period T' It can be set to T1 Multiples of (e.g., multiplied by 0.5, 2, 3, etc.). In some cases, the patient's specific scheduled time period. T' equal to the scheduled time period T Therefore, for a number of X The number of days (e.g., X ≥1), neural activity signal recordings are performed and processed by IPG. Neural activity signal recordings can be performed during deep brain stimulation (DBS) dosing intervals (e.g., when DBS medication is set to be administered) and / or discontinuation intervals (e.g., when DBS medication is set to be discontinued). Dosing and / or discontinuation intervals can be determined based on the patient's specific medical condition.

[0104] In one example, if an IPG device is implanted to replace an older one (e.g., due to the old device's battery running out), the Parkinson's patient may be in an advanced stage of Parkinson's syndrome and may potentially be unable to tolerate the stimulator's discontinuation intervals. In another example, if the IPG device is being implanted in a patient for the first time, there is typically an adjustment period where the discontinuation intervals allow for adjustment of the electrode impedance before setting a set of stimulation parameters. Probe implantation can produce a "stun effect," including edema around the electrodes, and can ultimately bias assessments of the clinical efficacy of the stimulation. Therefore, common clinical practice is to wait for the adjustment phase to end before turning on DBS during the discontinuation intervals. This adjustment period is often suitable for data collection. Preferably, the method for data collection includes a first number of days. X (For example, X ≥1), during which DBS is turned on, allowing neural activity signal recording (power spectrum) and / or patient-specific power of neural activity signal recording (e.g., from at least one electrode) to be acquired and / or stored as data. Then, via, for example, a radio frequency communication channel, in each recharge cycle, it can be transmitted to the patient-specific controller device (such as regarding...). Figure 1 Data stored in the IPG device is downloaded to the patient personal controller device 111 shown and described. Recharge cycles can be performed, for example, once daily, every other day, every 3 days, every 4 days, every 5 days, weekly, etc. Once data is downloaded to the patient personal controller device, it is deleted from the IPG device's memory and subsequently stored in the patient personal controller device's memory (e.g., as per [reference to...]). Figure 1 The memory 113 shown and described can have a larger storage capacity. In some cases, moving data from the IPG device to the patient's personal controller device allows the IPG device to collect data for extended periods of time (e.g., 1 month, 2 months, 3 months, 6 months, 12 months, etc.).

[0105] This paper describes a method for determining a set of stimulation parameters (also referred to herein as a "set of adaptive laws") to provide adaptive deep brain stimulation (aDBS) to an implantable pulse generator (IPG) device. This set of stimulation parameters may include a minimum stimulation amplitude. Maximum stimulation amplitude ,Depend on The first average value or the value represented by The second average value is represented. This set of stimulation parameters can be used to represent the amplitude of brain stimulation (DBS) in the following ways. Commonly defined as:

[0106]

[0107] in, Indicates having the first average value Compared with the second average The power of neural activity signals recorded between the values.

[0108] In some cases, minimum stimulus amplitude and / or maximum stimulus amplitude The treatment window can be determined based on the specific patient, as mentioned above. Figure 11 As stated above. In some cases, the minimum stimulus amplitude... and / or maximum stimulus amplitude It can be determined empirically by gradually increasing the stimulus amplitude (e.g., starting from zero and increasing to a stimulus value determined by the clinician) and continuously recording the gradually increasing clinical outcomes.

[0109] Figure 12 This is an exemplary method 1200 for adaptive deep brain stimulation. Method 1200 can, for example, be programmed by a clinician using a programmer device (such as...). Figure 1 The clinician programmer device 131 shown and described) and / or the use of a user computing device (such as a programmer device for clinical use) and / or a user computing device (such as a programmer for clinical use) are shown and described. Figure 1 The method 1200 is performed by a user computing device 121 shown and described. Method 1200 may include extracting 1201 a set of spectral features from a set of neural activity signal recordings over a predetermined number of days; selecting 1202 a set of spectral features within a frequency band of the set of spectral features; selecting 1204 a set of dosing intervals and a set of discontinuation intervals over the predetermined number of days; generating 1205 the minimum average value of the selected spectral features within the frequency band and within the set of dosing intervals; and generating 1206 the maximum average value of the selected spectral features within the frequency band and within the set of discontinuation intervals. Optionally, method 1200 may include generating 1203 the average value of the selected spectral features within the frequency band and across the predetermined number of days.

[0110] Figure 13 and Figure 14 This is an exemplary method for programming a clinician programmer device for adaptive deep brain stimulation. The method describes obtaining a first average value. Second average , such as regarding Figure 11The method described involves collecting local field spectral features over several days (e.g., 1 day, 2 days, 10 days, etc.). The method also involves selecting a frequency band for the local field potential from low-frequency bands, alpha bands, beta bands, or gamma bands. The method further involves averaging the power of the local field spectral features over the selected frequency band. In some cases, a set of moving averages of the power of the local field spectral features across the selected frequency band can be calculated for a set of time periods (e.g., 10 minutes, 1 hour, 6 hours, 1 day, 2 days, etc.). Therefore, a set of dosing and discontinuation times can be selected from this set of moving averages. In some cases, a threshold is determined by the user (e.g., patient, clinician, physician, etc.), and any time period with a moving average above / below the threshold can be classified as a dosing / discontinuation time. Finally, a first average can be calculated by averaging the power of the selected band over the dosing time. The second average value can be calculated by averaging the power of the selected band over the drug withdrawal period. .

[0111] As described above, deep brain stimulation systems can store and analyze this set of neural activity signal recordings to provide stimulation / treatment modes, including conventional deep brain stimulation (cDBS) treatment planning modes and / or adaptive deep brain stimulation (aDBS) treatment modes. In some cases, user devices (such as those related to...) Figure 1 The user of the user computing device shown and described may select to use a cDBS treatment mode. The cDBS treatment planning mode may involve setting a set of stimulation parameters, including the frequency, pulse width, and / or amplitude of the stimulation. In some cases, the user of the user device may select to use an aDBS treatment mode. The aDBS treatment planning mode may involve setting a set of stimulation parameters, including maximum power, minimum power, bandwidth, minimum stimulation amplitude, maximum stimulation amplitude, frequency, pulse width, etc. Further variations of the stimulation / treatment mode are provided in U.S. Patent No. 10,596,379, which is incorporated herein by reference in its entirety.

[0112] In some embodiments, the user of the clinician programming device and / or the user computing device can (via the GUI of the clinician programming device) select to use an open stimulation mode (also referred to as an "open stimulation procedure"). During the open stimulation mode, the user can set / assign parameters for the probes (e.g., each probe includes a pair of electrodes) to determine the stimulation parameters of the open stimulation mode. Parameters may include, for example, the stimulation amplitude, frequency, pulse width, etc., for each electrode. In some embodiments, the user can choose to operate the clinician programming device and / or the user computing device in a neural signal recording mode to record neural activity signals (e.g., local field potentials) for a duration of time (e.g., 30 seconds) and visualize the power spectrum of the neural activity signal recordings in tables and / or graphs. In some cases, the graph may include a statistical distribution of the neural activity signal recordings, such as moving average, bias, global average, median, etc.

[0113] Figure 15A and Figure 15B These are exemplary neural activity signal recordings stored and analyzed by a deep brain stimulation system. As described above, the deep brain stimulation system can acquire and / or store neural activity signal recordings, such as local field potentials (LFPs) over a predetermined time period (e.g., 1 day, 10 days, etc.). For example, as... Figure 15A As shown, in some cases, neural activity signals can be acquired and recorded separately for the left subthalamic nucleus (STN) and right STN within a frequency range of 5 Hz to 35 Hz during a day (e.g., during regular daily activities). The deep brain stimulation system can select frequency bands for neural activity signal recording from low-frequency bands, alpha bands, beta bands, and / or gamma frequencies. For example, as shown in Figure 15A, in some cases, a frequency band between 12 Hz and 20 Hz can be selected for analysis. The deep brain stimulation system can further average the power of neural activity signal recordings across the selected frequency bands. For example, as... Figure 15B As shown, the average neural activity signal recordings can be further analyzed using the deep brain stimulation system and methods described above to determine the drug administration interval and drug discontinuation interval.

[0114] Figure 16 It is a deep brain stimulation system in some variants (such as those related to...) Figure 1 A flowchart illustrating an exemplary communication method and data flow 1610 between the deep brain stimulation system 100 shown and described and its supporting components (also referred to as the "support system") 1620. Deep brain stimulation can utilize the supporting component 1620 to implement the data flow 1610. The supporting component may include IPG 1621 ( Figure 1 Implantable device 101), patient controller 1622 ( Figure 1 Patient personal controller device 111), application 1623 (in Figure 1 Implemented in the user computing device 121 or in the clinician programmer device 131), cloud service 1624 ( Figure 1 (Biobank server). Data flow includes collecting daily data 1610 on the IPG device. Daily data may include a set of neural activity signal recordings and / or patient log data. Data flow includes downloading daily data 1612 to the patient controller 1622 for long-term data storage. Data flow includes downloading long-term data on the application 1623. Data flow includes sending long-term data to the cloud service 1624 and storing long-term data 1614 in the cloud service 1624.

[0115] The foregoing description, for purposes of explanation, has used specific terminology to provide a thorough understanding of the invention; however, it will be apparent to those skilled in the art that such specific details are not necessary for practicing the invention. Therefore, for purposes of illustration and description, the foregoing description provides specific variations of the invention. These are not intended to be exhaustive or to limit the invention to the precise forms disclosed; obviously, many modifications and variations are possible in light of the foregoing teachings. These variations were chosen and described to explain the principles of the invention and its practical application, thus enabling others skilled in the art to utilize the invention and its various variations with various modifications suitable for the intended particular use. The following claims and their equivalents are intended to define the scope of the invention.

Claims

1. A system (100) for deep brain stimulation, the system comprising: An implantable device (101, 400B) configured to acquire and store neural activity signal recordings and apply electrical stimulation; A personal controller device (111, 800) configured to establish a first wireless connection to an implantable device (101, 400B); and Clinician programmer devices (131, 322, 1000). The implantable device (101, 400B) is configured to record and transmit neural activity signals to a personal controller device (111, 800) via a first wireless connection. The clinician programmer devices (131, 322, 1000) are configured to establish a second wireless connection with the implantable devices (101, 400B) to receive neural activity signal recordings from the implantable devices (101, 400B) and to set multiple stimulation parameters based on the neural activity signal recordings. The personal controller device (111, 800) is characterized in that it is configured to transmit power to the implantable device (101, 400B), and The implantable device (101, 400B) is configured to establish a second wireless connection with the clinician programmer device (131, 322, 1000) based on the activation of the first wireless connection with the personal controller device (111, 800).

2. The system (100) according to claim 1, characterized in that, It also includes a user computing device (121), which is configured to: Receive patient log data; At least based on the temporal correlation between patient log data and neural activity signal recordings, patient log data is correlated with neural activity signal recordings; Based on neural activity signal recordings and patient log data, multiple medication intervals and multiple medication discontinuation intervals were determined. as well as Multiple stimulation parameters are generated based on neural activity signal recordings during multiple drug dosing and discontinuation intervals.

3. The system (100) according to claim 2, characterized in that, The user computing device (121) is also configured to: The statistical distribution of the generated neural activity signal recordings, which includes multiple means and multiple variance values; and The user interface displays graphs of neural activity signal recordings, multiple average values, and multiple variance values.

4. The system (100) according to claim 2 or 3, characterized in that, The user computing device (121) is also configured to: Extract multiple spectral features within the frequency band of neural activity signals recorded during a predetermined time period; Determine multiple dosing intervals and multiple discontinuation intervals within a predetermined time period; as well as The first average value of multiple spectral features within multiple drug administration intervals of the frequency band and the second average value of multiple spectral features within multiple drug discontinuation intervals of the frequency band.

5. The system (100) according to claim 4, characterized in that, The user computing device (121) is configured to generate multiple stimulation parameters based on a first average and a second average.

6. The system according to claim 2 or 3, characterized in that, The user computing device (121) is also configured to: A machine learning model is trained based on a set of historical neural activity signal records that do not include the aforementioned neural activity signal records, or a set of historical stimulus parameters that do not include the aforementioned multiple stimulus parameters; and A machine learning model is executed based on the recorded neural activity signals to identify the plurality of stimulation parameters.

7. The system (100) according to claim 2 or 3, characterized in that, The user computing device (121) is also configured to: Transmitting neural activity signal recordings and / or patient log data or multiple stimulation parameters to a biobank server; and Delete neural activity signal recordings and / or patient log data or multiple stimulation parameters from the memory of the user's computing device.

8. The system (100) according to any one of claims 1 to 3, characterized in that, The power is the inductive power sensed from the patient's personal controller device (111, 800) to the implantable device (101, 400B) via an inductive link for recharging; During recharging, neural activity signal recordings and / or patient log data are automatically transmitted from the implantable device (101, 400B) to the personal controller device (111, 800).

9. The system (100) according to any one of claims 1-3, characterized in that, The clinician programmer device (131, 322, 1000) is configured to establish an authenticated communication channel with the personal controller device (111, 800), and the clinician programmer device (131, 322, 1000) is further configured to: Receive patient log data from a personal controller device; At least based on the temporal correlation between patient log data and neural activity signal recordings, patient log data is correlated with neural activity signal recordings; Based on neural activity signal recordings and patient log data, multiple medication intervals and multiple medication discontinuation intervals were determined. as well as Multiple stimulation parameters are generated based on neural activity signal recordings during multiple drug dosing and discontinuation intervals.

10. The system (100) according to claim 9, characterized in that, The clinician programmer device (131, 322, 1000) is further configured to: The statistical distribution of the generated neural activity signal recordings, which includes multiple means and multiple variance values; and The user interface displays graphs of neural activity signal recordings, multiple average values, and multiple variance values.

11. The system (100) according to claim 9, characterized in that, The clinician programmer device (131, 322, 1000) is further configured to: Extract multiple spectral features within the frequency band of neural activity signals recorded during a predetermined time period; Determine multiple dosing intervals and multiple discontinuation intervals within a predetermined time period; as well as The first average value of multiple spectral features within multiple drug administration time intervals of the frequency band and the second average value of multiple spectral features within multiple drug discontinuation time intervals of the frequency band.

12. The system (100) according to claim 9, characterized in that, The clinician programmer device (131) is further configured to: Transmitting neural activity signal recordings and / or patient log data or multiple stimulation parameters to a biobank server; and Delete neural activity signal recordings and / or patient log data or multiple stimulation parameters from the memory of the clinician programmer device.

13. The system according to claim 2 or 3, characterized in that, The user computing device is configured to establish a third wireless connection to the personal controller device (111, 800), the personal controller device (111, 800) being configured to: Neural activity signal recordings are received from the personal controller device (111, 800) via a third wireless connection, and Patient log data is received from the personal controller device (111, 800).

14. The system (100) according to claim 7, characterized in that, The user computing device (121) and / or the clinician programmer device (131, 322, 1000) are further configured to directly transmit neural activity signal recordings and / or patient log data or multiple stimulation parameters to the biobank server, or transmit them to the biobank server via the user computing device.

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