Remote Implant Programming via Secure Cloud Health Networks

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Solution Overview

Problem

Existing implantable medical devices require in-person programming due to the need for close contact, limiting remote patient care capabilities and increasing healthcare delivery costs.

Innovation Solution

A cloud-centric digital health network architecture enabling secure, remote programming of implantable medical devices through clinician and patient devices, utilizing AI and ML for real-time kinematic and auditory analysis, and secure data transfer.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If in-person programming using short-range communication links is used, then security against third-party access is improved, but remote patient care capability deteriorates

Engineering Contradiction:
ImprovesecurityVSAvoidremote patient care capability
Core Design Contradiction:
ReliabilityVSEase of operation

Solution Approach 1:

The patent introduces a cloud server as an intermediary between the patient's mobile device and the implantable medical device. The cloud server establishes a secure communication path that allows remote programming while maintaining security through encrypted channels and authentication protocols, eliminating the need for direct short-range communication between the clinician and patient device.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces the mechanical requirement of physical proximity (short-range communication links requiring close contact) with wireless cloud-based communication. This substitution allows clinicians to program implantable devices remotely through internet-connected mobile devices, transforming the interaction from in-person to distance-based while maintaining security through digital authentication and encryption.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If in-person programming is required, then security against unauthorized access is improved, but healthcare delivery cost increases

Engineering Contradiction:
ImprovesecurityVSAvoidhealthcare delivery cost
Core Design Contradiction:
ReliabilityVSProductivity

Solution Approach 1:

The system enables patients to initiate and manage their own device programming sessions through mobile applications, reducing the need for clinician time and in-person visits. Patients can schedule remote programming sessions, and the automated cloud-based system handles the communication and programming processes with minimal clinician intervention, thereby reducing healthcare delivery costs while maintaining security protocols.

Inventive Principle:
Principle #25Self-service

3Ease of operation

If cloud-centric remote communication is implemented, then remote patient care accessibility is improved, but system complexity increases

Engineering Contradiction:
Improveremote patient care accessibilityVSAvoidsystem complexity
Core Design Contradiction:
Ease of operationVSDevice complexity

Solution Approach 1:

The patent utilizes existing multi-functional mobile devices (smartphones, tablets) that patients and clinicians already possess. These devices serve multiple purposes: they act as communication interfaces, authentication devices, and programming controllers. The cloud server provides universal access points that work across different mobile platforms, reducing the need for specialized hardware and simplifying the overall system architecture despite the remote communication capabilities.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentUS12472365B2Systems and methods for providing digital health services
Publication Date: 2025.11.18 ADVANCED NEUROMODULATION SYSTEMS INC
  • US12472365B2 patent drawing
  • US12472365B2 patent drawing
  • US12472365B2 patent drawing

AI summary

The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.