Implantable Device Predictive Diagnosis Asymptomatic Heart Failure

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Patients with implanted medical devices that respond to metabolic and activity sensors often adapt their behavior unconsciously to avoid symptoms of heart failure, leading to delayed diagnosis and potential crises, as they reduce activity to prevent symptoms, making it difficult for the device to accurately assess their clinical status without noticeable symptoms.

Innovation Solution

An implantable device equipped with both physiologic and physical sensors that processes information to assess the patient's status and evolution, even in the absence of symptoms, by distinguishing between activity and rest phases and using statistical processing to update memory fields and evaluate clinical status indices, triggering preventive alarms if necessary.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If the device relies on sensor signals to detect patient status, then automatic monitoring is enabled, but the device cannot detect asymptomatic clinical modifications when patients unconsciously adapt their behavior

Engineering Contradiction:

Improveaccuracy of clinical status assessmentVSAvoiddetection of asymptomatic status changes

Core Design Contradiction:

ReliabilityVSDifficulty of detecting and measuring

Solution Approach 1:

The device performs preliminary statistical processing of sensor data to establish baseline patterns and predict future status changes before they become clinically apparent. By analyzing trends in respiratory and activity data proactively, the system can alert patients and clinicians before asymptomatic changes lead to symptomatic heart failure crises.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The device implements feedback mechanisms by continuously monitoring sensor data, comparing it against established patterns, and providing alerts when deviations are detected. This closed-loop system enables the device to adapt to changing patient conditions and maintain accurate monitoring even as patients modify their behavior in response to early symptoms.

Inventive Principle:

Principle #23Feedback

2Object-affected harmful factors

If the patient reduces activity to prevent heart failure symptoms, then symptom avoidance is achieved, but the device cannot accurately assess clinical status due to altered behavior patterns

Engineering Contradiction:

Improveprevention of heart failure symptomsVSAvoidaccuracy of metabolic and activity measurement

Core Design Contradiction:

Object-affected harmful factorsVSMeasurement precision

Solution Approach 1:

The device monitors changes in sensor parameters (respiratory rate, activity levels) and detects deviations from baseline patterns that indicate clinical status changes. By tracking parameter trends rather than relying on absolute values, the system can accurately assess patient status even when activity levels are reduced due to symptom avoidance behavior.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system performs preliminary statistical analysis to establish individual baseline patterns and detect early deviations before they manifest as obvious symptoms. This allows the device to maintain measurement precision even when patients alter their behavior to prevent symptomatic episodes.

Inventive Principle:

Principle #10Preliminary action

3Loss of time

If the device uses traditional sensor monitoring, then current status can be tracked, but early prediction of worsening clinical status is not possible

Engineering Contradiction:

Improvetime delay in diagnosisVSAvoidpredictive accuracy of clinical status

Core Design Contradiction:

Loss of timeVSReliability

Solution Approach 1:

The device performs preliminary statistical processing of sensor data to identify trends and patterns that predict future clinical status changes. By analyzing data proactively and comparing it against established baselines, the system can predict worsening conditions before they manifest as obvious symptoms, reducing diagnostic delays.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements continuous feedback loops that monitor sensor data, detect deviations from normal patterns, and provide early warnings of impending clinical deterioration. This enables timely intervention before life-threatening events occur, reducing the time delay between status change and diagnosis.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS8798748B2Predictive diagnosis of a patient's status in an active implantable medical device notably for cardiac pacing, resynchronization, defibrillation or cardioversion

Publication Date: 2014.08.05 SORIN CRM

AI summary

An active implantable medical device or pacing, resynchronization defibrillation and/or cardioversion, and/or a device for diagnosing patient conditions, having a predictive diagnosis of the patient's status. The device measures a physiologic parameter, notably the minute ventilation; measures a physical parameter, notably the acceleration; discriminates between phases of activity and rest of the patient; and includes a memory containing a plurality of fields selectively updated by statistical processing. These fields are comprising one first set containing data related to the patient's activity phases, and one second set containing data related to the patient's rest phases. The statistical processing is updating in a dissociated manner the first and second sets of fields, selectively as a function of the value taken by the status indicator, and the analysis evaluates at least one clinical status index based upon the data contained in the fields of both first and second sets.