Derivative works

Defensive Disclosure Document for US Patent 11998262

Date: 2026-05-17

This document outlines derivative variations and alternative implementations of the systems and methods described in US Patent 11998262, with the aim of creating defensive prior art to render future incremental improvements by competitors "obvious" or "non-novel." The focus is on expanding the scope of the disclosed invention beyond its explicit claims, anticipating potential advancements and disclosing a broad range of alternatives.

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Derivative Variations for Core Claims (Claim 10 - Device & Claim 17 - Method)

The following derivatives build upon the core inventive concepts of US11998262, specifically regarding the therapeutic device (Claim 10) and its method of use (Claim 17) for neuromodulation and tissue engorgement reduction in the nasal cavity.

1. Material & Component Substitution

Derivative 1.1: Bioresorbable Polymer Support Structures with Conductive Coatings

• Enabling Description: The flexible support elements of the multi-segment end effector (114, 122, 124) and potentially portions of the elongate body (116) are fabricated from bioresorbable polymers such as poly(L-lactic acid) (PLLA), poly(glycolic acid) (PGA), or poly(lactic-co-glycolic acid) (PLGA) with specific degradation profiles (e.g., 6-12 months). These polymer struts are coated with a thin layer of highly conductive, biocompatible material such as titanium nitride (TiN) or an alloy of platinum-iridium (Pt-Ir) to serve as electrodes (136, 137). The electrical connections are achieved via fine, braided platinum-iridium wires (0.005-0.010 inch diameter) embedded within the polymer matrix or run along internal lumens, terminating in exposed conductive tips. This allows for temporary therapeutic modulation with subsequent safe bioresorption of the structural components, eliminating the need for removal and reducing long-term foreign body reactions. The handle (118) and outer sheath (138) remain non-resorbable for reusable or single-use applications. Energy delivery for ablation or neuromodulation would be standard RF (460-480 kHz) or pulsed DC, as described in the patent.

classDiagram
    class TreatmentDevice {
        Handle handle
        ElongateBody elongateBody
        EndEffector endEffector
    }
    class ElongateBody {
        +BioresorbableSheath outerSheath
        +TiN/PtIrElectrodes electrodes
        +PtIrWires internalWiring
    }
    class EndEffector {
        +BioresorbableSegments firstSegment
        +BioresorbableSegments secondSegment
        +TiN/PtIrElectrodes electrodes
        +PtIrWires internalWiring
    }
    class Handle {
        +DeploymentMechanism mechanism1
        +EnergyControlMechanism mechanism2
    }
    TreatmentDevice -- Handle
    TreatmentDevice -- ElongateBody
    TreatmentDevice -- EndEffector
    ElongateBody -- EndEffector
    ElongateBody "1" -- "N" TiN/PtIrElectrodes
    EndEffector "1" -- "N" TiN/PtIrElectrodes

Derivative 1.2: Piezoelectric Ceramic Actuators for End Effector Deployment and Energy Delivery

• Enabling Description: The flexible support elements (struts 130, 132, 134) of the multi-segment end effector (114) are replaced or augmented with micro-scale piezoelectric ceramic actuators (e.g., lead zirconate titanate - PZT) bonded to a polymer or metallic spine. These PZT elements are arrayed to both deploy and retract the end effector segments through controlled electrical excitation causing mechanical deformation (inverse piezoelectric effect). For energy delivery, these same piezoelectric elements are driven at ultrasonic frequencies (e.g., 1-5 MHz) to generate localized high-intensity focused ultrasound (HIFU) energy for thermal ablation or low-intensity pulsed ultrasound (LIPUS) for neuromodulation. The elongate body (116) incorporates miniaturized cabling for independent control of each piezoelectric actuator/transducer. The handle (118) includes a multi-channel piezoelectric driver with pulse shaping capabilities and dedicated user interfaces for deployment and ultrasound energy delivery. Temperature sensors (e.g., thermistors) are integrated into the end effector tips for real-time thermal feedback.

flowchart TD
    A[Handle] --> B{Piezoelectric Driver Module};
    B --> C[Control Signals to Actuators];
    C --> D{End Effector with PZT Arrays};
    D -- Mechanical Actuation --> E[Deploy/Retract Segments];
    D -- Ultrasonic Energy --> F[Tissue Modulation/Ablation];
    F --> G[Nasal Tissue];
    D -- Temperature Feedback --> B;

2. Operational Parameter Expansion

Derivative 2.1: Millimeter-Wave RF Ablation for Enhanced Tissue Specificity

• Enabling Description: The energy delivery elements (electrodes 136, 137) are designed to deliver millimeter-wave radiofrequency (mmWave RF) energy (e.g., 30-300 GHz) instead of conventional RF (460-480 kHz). This higher frequency range allows for extremely shallow penetration depths (tens to hundreds of micrometers) into the mucosal tissue, enabling highly precise and superficial ablation or neuromodulation of the postganglionic parasympathetic nerve fibers without affecting deeper structures or causing collateral damage to bone or cartilage. The electrodes are micro-fabricated patch antennas or slot antennas embedded on the flexible support elements (130, 132, 134) and outer sheath (138). A compact millimeter-wave generator and associated waveguides or coaxial lines are integrated into the console (104) and routed through the elongate body (116). Treatment parameters would involve very low power levels (e.g., 0.1-5 W) for very short durations (e.g., <1 second pulses) to achieve localized hyperthermia or non-thermal cell membrane disruption.

sequenceDiagram
    participant S as Surgeon
    participant D as Device (Handle, Shaft, End Effector)
    participant C as Console (mmWave Generator)
    S->D: Advance Device
    S->D: Deploy End Effector
    Note over D: Electrodes (patch antennas) positioned at target sites
    S->C: Initiate mmWave Energy Delivery (low power, short pulse)
    C->D: Transmit mmWave RF (30-300 GHz)
    D->N: Localized Tissue Ablation/Neuromodulation
    N->D: Temperature Feedback (superficial layer)
    D->C: Temperature Data
    C->S: Real-time Feedback (GUI 112)
    S->D: Retract Device

Derivative 2.2: Ultra-Low Frequency Electrical Neurostimulation for Non-Ablative Modulation

• Enabling Description: Instead of thermal ablation, the device (102) is configured for ultra-low frequency (ULF) electrical neurostimulation (e.g., 1-100 Hz, with biphasic pulses of 10-500 µs duration and amplitudes of 0.1-10 mA) via the electrodes (136, 137). The objective is to achieve long-term, non-ablative neuromodulation of the postganglionic parasympathetic nerves, potentially through neurotransmitter depletion or sustained sub-threshold inhibition, rather than tissue destruction. The flexible support elements (130, 132, 134) and elongate body (116) carry multiple micro-electrodes (e.g., 100-200 µm diameter platinum-iridium contacts) arranged in high-density arrays to facilitate precise current steering and activation of specific nerve branches. The console (104) incorporates a multi-channel pulse generator capable of delivering customizable waveforms and precise current control. This approach aims for reversible or titratable effects, allowing for adjustment of therapy over time without permanent tissue alteration.

stateDiagram-v2
    [*] --> Idle
    Idle --> AdvanceDevice: Surgeon advances
    AdvanceDevice --> DeployEffector: Surgeon deploys
    DeployEffector --> PositionElectrodes: End effector conforms
    PositionElectrodes --> StimulateNerves: Initiate ULF Stimulation
    StimulateNerves --> MonitorResponse: Detect neural/symptom changes
    MonitorResponse --> AdjustStimulation: If needed
    AdjustStimulation --> StimulateNerves
    StimulateNerves --> RetractDevice: After prescribed duration
    RetractDevice --> [*]
    StimulateNerves --> Abort: Safety Trigger

3. Cross-Domain Application

Derivative 3.1: Adaptive Conformable Gripper for Industrial Robotics

• Enabling Description: The multi-segment end effector's (114) retractable and expandable design, with its flexible support elements (130, 132, 134) and conformable segments (122, 124), is adapted for use as a robotic gripper in industrial automation. The "electrodes" (136) are replaced with a multi-array of pressure sensors and/or localized heating elements (e.g., resistive heaters or miniature inductive coils). The "handle" (118) and "elongate body" (116) become the robotic arm's end-of-arm tooling and control interface. The gripper deploys its segments to conform to irregularly shaped objects, using pressure sensor feedback to distribute gripping force evenly. The heating elements can be selectively activated to provide localized thermal adhesion or temporary surface modification for enhanced grip on specific materials (e.g., thermoplastic components). This enables robots to handle fragile or geometrically complex objects that traditional rigid grippers struggle with.

flowchart TD
    A[Robotic Arm] --> B[Gripper (Adapted Device)];
    B -- Deployment Mechanism --> C[Conformable Segments (Adapted End Effector)];
    C -- Pressure Sensors --> D[Feedback Control System];
    C -- Heating Elements --> E[Localized Adhesion/Surface Modification];
    D -- Adjusts Grip Force --> C;
    B -- Object Handling --> F[Irregular Objects];

Derivative 3.2: Subterranean Root Modulation System for Agriculture

• Enabling Description: The entire device architecture (handle, elongate body, multi-segment end effector) is scaled and ruggedized for subterranean agricultural applications. The elongate body (116) is designed as a rigid-flexible probe with sensors (pH, moisture, nutrient levels) and the end effector (114) becomes a deployable root modulation array. The flexible support elements (130, 132, 134) carry electrodes (136) configured for delivering pulsed electric fields (PEF) or low-power RF energy to specific root structures (e.g., 100-500 V/cm, 100 µs pulse width, 1-10 Hz repetition rate). This energy can be used to inhibit specific pathogenic fungal or bacterial growth on roots, stimulate nutrient uptake pathways, or temporarily block root communication signals in invasive species. The "handle" (118) integrates with agricultural machinery, providing GPS-guided positioning and automated deployment. The system monitors soil conditions and adjusts energy delivery parameters autonomously.

graph TD
    A[Agricultural Machinery] --> B(GPS Guidance & Control);
    B --> C[Subterranean Probe (Adapted Elongate Body)];
    C -- Advance/Retract --> D{Root Modulation Array (Adapted End Effector)};
    D -- PEF/RF Energy --> E[Root System];
    D -- Soil Sensors (pH, Moisture) --> C;
    C -- Data Link --> B;
    B -- Automated Operation --> F(Crop Health Management);

4. Integration with Emerging Tech

Derivative 4.1: AI-Driven Adaptive Neuromodulation with Real-time MRI Feedback

• Enabling Description: The neuromodulation system (100) integrates with a real-time, intra-operative magnetic resonance imaging (MRI) system. The elongate body (116) and multi-segment end effector (114) are constructed from MRI-compatible materials (e.g., PEEK, ceramic, non-ferromagnetic alloys) and incorporate fiber optic temperature sensors. Pre-operative high-resolution MRI or CT scans of the patient's nasal anatomy (including detailed neural pathways and vascular structures) are fed into an AI model. During the procedure, the AI model continuously analyzes real-time MRI data to precisely locate the end effector (114) and individual electrodes (136, 137) relative to target neural structures (e.g., postganglionic parasympathetic fibers, specific microforamina). The AI then dynamically adjusts the deployment configuration of the end effector, individual electrode activation patterns, energy levels (RF or other modalities), and treatment duration to optimize therapeutic effect while minimizing collateral damage. The handle (118) provides haptic feedback to the surgeon, guided by the AI, for precise manual control.

graph LR
    A[Pre-op MRI/CT Data] --> B(AI-Driven Treatment Plan);
    B --> C{Real-time Intra-op MRI};
    C --> D(AI Control Module);
    D -- Optimized Parameters --> E[Neuromodulation Device (Handle, Shaft, End Effector)];
    E -- Energy Delivery --> F[Target Neural Structures];
    F -- Tissue Response (Temp, Impedance) --> G[Fiber Optic Sensors];
    G --> D;
    D -- Haptic Feedback/Guidance --> S[Surgeon];

Derivative 4.2: IoT-Enabled Post-Procedure Monitoring and Proactive Intervention

• Enabling Description: The neuromodulation device (102) is paired with a system of miniaturized, bioresorbable IoT sensors (e.g., MEMS temperature, impedance, airflow sensors) that are temporarily implanted within the nasal mucosa at the treatment sites during or immediately after the procedure. These sensors wirelessly transmit data (e.g., via Bluetooth Low Energy or near-field communication) to a patient's mobile device or a dedicated external gateway. This data is then uploaded to a secure cloud platform. An AI algorithm analyzes the long-term physiological data (nasal patency, inflammation markers, nerve activity proxies) to detect early signs of re-engorgement or sub-optimal treatment outcomes. The system generates alerts for the patient and clinician, suggesting proactive interventions (e.g., adjusting medication, scheduling follow-up for touch-up procedures, or recommending lifestyle changes). Blockchain technology is used to immutably log all sensor data, treatment parameters, and clinical observations, creating a verifiable patient treatment history for regulatory compliance and personalized medicine insights.

sequenceDiagram
    participant P as Patient
    participant S as Implanted IoT Sensors
    participant M as Mobile App/Gateway
    participant C as Cloud Platform (AI Analytics)
    participant B as Blockchain Ledger
    participant D as Clinician
    S->M: Wireless Data Transmission (Temp, Impedance, Airflow)
    M->C: Upload Sensor Data
    C->C: AI Analysis (Detect anomalies, predict re-engorgement)
    C->B: Log Sensor Data & AI Insights
    C->M: Alert Notification (if anomaly detected)
    M->P: Notify Patient
    M->D: Notify Clinician
    D->P: Proactive Intervention/Follow-up

5. The "Inverse" or Failure Mode

Derivative 5.1: Diagnostic-Only Mode with Integrated Nerve Mapping and Safe Failure

• Enabling Description: The neuromodulation device (102) includes a dedicated "diagnostic-only" mode where the electrodes (136, 137) are exclusively used for impedance sensing and low-current (e.g., micro-ampere level) nerve stimulation for mapping and identification, without delivering therapeutic energy. This mode is activated by a specific sequence on the handle's (118) control mechanisms (126, 128) or through the console (104) GUI (112). In the event of an detected electrical fault (e.g., short circuit, open circuit, or excessive impedance spike) or an accidental over-temperature reading from integrated thermistors during any operational mode, the device instantly defaults to this safe diagnostic mode, automatically cutting off all therapeutic energy delivery. The end effector (114) would also feature an automatic, spring-loaded retraction mechanism that engages upon loss of power or explicit safety command, pulling the segments back into the protective outer sheath (138) to prevent inadvertent tissue contact.

stateDiagram
    [*] --> Off
    Off --> DiagnosticMode: Power On / Select Diagnostic
    DiagnosticMode --> NerveMapping: Perform Nerve Mapping
    NerveMapping --> ImpedanceSensing: Perform Impedance Sensing
    DiagnosticMode --> EmergencyRetract: Fault Detected / Safety Command
    NerveMapping --> EmergencyRetract: Fault Detected / Safety Command
    ImpedanceSensing --> EmergencyRetract: Fault Detected / Safety Command
    DiagnosticMode --> TherapeuticMode: Surgeon Initiates Therapy
    TherapeuticMode --> DeliverEnergy: Apply RF/Ultrasound
    DeliverEnergy --> TherapeuticMode: Continue Therapy
    DeliverEnergy --> EmergencyRetract: Fault Detected / Safety Command
    EmergencyRetract --> RetractedAndSafe: End Effector Retracted, Power Off
    RetractedAndSafe --> Off: Device Shutdown

Derivative 5.2: Temporary Drug Delivery for Reversible Neuromodulation / Low-Power Functionality

• Enabling Description: The flexible support elements (130, 132, 134) of the multi-segment end effector (114) are modified to incorporate microfluidic channels and porous segments or dissolvable drug-eluting coatings. Instead of delivering thermal or electrical energy for ablation, the device (102) is used to precisely deliver localized pharmacological agents (e.g., topical anesthetics like lidocaine, botulinum toxin for chemodenervation, or anti-inflammatory steroids) to the target sites associated with postganglionic parasympathetic nerve fibers or engorged turbinate tissue. This provides temporary, reversible neuromodulation or symptomatic relief without permanent tissue modification. The "energy control mechanism" (128) on the handle (118) now controls the micro-pump for drug delivery rate and volume. The "elongate body" (116) includes a reservoir and fluid lines (e.g., auxiliary line 121 modified for drug delivery). This offers a low-power, limited-functionality mode where the device acts purely as a drug delivery platform for transient effects, rather than a permanent ablative tool.

flowchart TD
    A[Handle] --> B{Micro-Pump Control};
    B --> C[Drug Reservoir (in Handle/Shaft)];
    C --> D[Microfluidic Channels (in End Effector)];
    D -- Localized Drug Delivery --> E[Target Neural/Mucosal Tissue];
    E --> F[Temporary Neuromodulation/Symptom Relief];
    A -- Deployment Mechanism --> G[Deploy End Effector];

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Combination Prior Art Scenarios with Open-Source Standards

These scenarios combine the inventive concepts of US Patent 11998262 with existing open-source standards to establish obviousness for potential future developments.

Scenario 1: Integration with Open-Source Medical Robotics Framework (ROS-M)

• Description: The therapeutic neuromodulation system (100), including the handheld device (102) and console (104), is implemented using the Robot Operating System for Medical applications (ROS-M). ROS-M, an open-source framework, provides libraries and tools for robotic control, sensor integration, image processing, and human-robot interaction in medical contexts.
  • Handle (118) and Console (104) Integration: The control logic for the deployment mechanisms (126) and energy delivery (128) is implemented as ROS nodes. User input from the handle's ergonomic controls is processed via ROS interfaces, allowing for standardized communication with the energy generator (106) and controller (107).
  • Image Guidance: An endoscope (as mentioned in the patent) or other visualization device (e.g., optical coherence tomography, OCT) is integrated via ROS drivers, providing real-time visual feedback to a ROS-powered GUI (112). This allows for collaborative control where the surgeon manipulates the device, and ROS-M provides augmented reality overlays of anatomical structures and predicted nerve locations (based on open-source anatomical atlases) directly onto the video feed.
  • Sensor Data Fusion: Impedance and temperature sensors (e.g., 108) on the end effector (114) and elongate body (116) stream data to ROS topics. An open-source data fusion algorithm (e.g., from OpenCV or PCL libraries) combines sensor data with anatomical models for enhanced navigation and real-time assessment of tissue response.
• Impact on Obviousness: This combination renders obvious the integration of the device's control, feedback, and image guidance functionalities into any open-source medical robotics or automation framework, facilitating standardized development of precision tools for nasal surgery.

Scenario 2: Energy Delivery Profile Optimization using Open-Source Machine Learning Libraries (TensorFlow/PyTorch)

• Description: The system (100) utilizes open-source machine learning (ML) libraries, such as TensorFlow or PyTorch, running on the console's (104) controller (107) to optimize energy delivery parameters.
  • Data Collection: Real-time physiological data (tissue impedance, temperature feedback from sensors on electrodes 136, 137, ENG signals 108) from numerous procedures are collected and anonymized. This dataset also includes patient-specific anatomical variations and treatment outcomes (e.g., post-operative nasal breathability scores, symptom reduction).
  • ML Model Training: A supervised learning model (e.g., a deep neural network) is trained using this dataset to predict optimal RF energy parameters (power, duration, duty cycle, electrode activation pattern) for individual patients and specific target sites, aiming to maximize therapeutic effect (nerve modulation/ablation, turbinate engorgement reduction) while minimizing collateral damage.
  • Real-time Optimization: During a procedure, the ML model, deployed on the console (104), takes real-time impedance and temperature readings as input. It then suggests or automatically adjusts the energy delivery parameters for the generator (106) and electrode array (114, 116), adapting to subtle tissue variations and ensuring consistent treatment efficacy as per evaluation/feedback algorithms (110).
• Impact on Obviousness: This discloses the obviousness of applying standard machine learning techniques (available through open-source libraries) to optimize the therapeutic energy delivery of the claimed device, moving beyond pre-programmed patterns to adaptive, data-driven treatment protocols.

Scenario 3: Secure Device Management and Tracking via Open-Source Distributed Ledger Technology (Hyperledger Fabric)

• Description: The manufacturing, sterilization, distribution, and usage lifecycle of the therapeutic neuromodulation device (102) are managed and tracked using an open-source distributed ledger technology, specifically Hyperledger Fabric.
  • Supply Chain Transparency: Each device (102), and potentially its critical components (e.g., end effector 114), is assigned a unique digital identity (e.g., serial number linked to a cryptographic hash). This identity is recorded on a blockchain network built with Hyperledger Fabric. Manufacturers, sterilization facilities, distributors, and healthcare providers act as nodes on the network.
  • Immutable Records: Every critical event—batch manufacturing, sterilization cycle, shipping, receipt by a hospital, patient-specific usage (linking to patient ID, date, time, energy settings)—is immutably recorded as a transaction on the ledger. This ensures transparency, traceability, and verifiable compliance with regulatory standards.
  • Smart Contracts for Compliance: Smart contracts define the rules for each stage of the device's lifecycle (e.g., "device must be sterilized before shipment," "only certified clinicians can activate the device for therapeutic energy delivery"). These contracts automatically enforce compliance and trigger alerts for any deviations.
• Impact on Obviousness: This scenario makes obvious the application of widely available open-source blockchain technologies to secure the lifecycle management and operational data of the patent's claimed medical device, addressing common industry needs for traceability, integrity, and regulatory compliance.