Cardiac Stimulation Device Personalization
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Solution Overview
Problem
Existing cardiac stimulation devices are not effective for a significant portion of patients with heart failure, as they fail to provide personalized therapy matching individual patients' anatomical and physiological characteristics, leading to suboptimal synchronization and contractility.
Innovation Solution
The development of an implantable cardiac stimulation device that uses multi-dimensional spatial and temporal analysis to match a patient's intrinsic electro-mechanical activity with therapeutic stimulation patterns, adjusting delivery to align with eucontractile templates based on anatomical dimensions and physiological characteristics, thereby optimizing therapy delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standardized CRT therapy is delivered to all patients, then device simplicity and ease of operation are maintained, but therapy effectiveness deteriorates for non-responsive patients due to lack of personalization
Solution Approach 1:
The device automatically adjusts multiple therapy parameters including pacing amplitude, pulse width, and timing intervals based on real-time sensing of patient-specific electro-mechanical characteristics. The system modifies stimulation parameters to match the patient's intrinsic cardiac activity patterns, transforming a fixed-parameter device into an adaptive one without requiring manual reprogramming.
Solution Approach 2:
The implantable device performs self-characterization by automatically sensing the patient's intrinsic electro-mechanical activity and using this information to program its own therapy delivery parameters. The system eliminates the need for external programming by healthcare providers, allowing the device to autonomously optimize therapy based on the patient's physiological profile.
2Adaptability or versatility
If pre-programmed default values are used for all patients, then ease of operation and rapid deployment are achieved, but adaptability to individual patient anatomy and physiology deteriorates
Solution Approach 1:
The device automatically senses and characterizes the patient's intrinsic electro-mechanical activity, then uses this self-acquired data to program its own therapy delivery parameters. This self-programming capability eliminates the need for manual configuration by healthcare providers while achieving full personalization to each patient's anatomy and physiology.
Solution Approach 2:
The system performs preliminary characterization of the patient's cardiac activity during initial device operation, building a personalized profile that guides subsequent therapy delivery. By pre-characterizing the patient's electro-mechanical patterns before formal therapy optimization, the device prepares personalized parameters in advance for effective treatment.
3Measurement precision
If multi-dimensional spatial and temporal analysis is implemented for personalized therapy, then therapy precision and effectiveness are improved, but device complexity and programming requirements increase
Solution Approach 1:
The device automatically performs multi-dimensional analysis of the patient's electro-mechanical activity and uses this analysis to self-program therapy delivery parameters. The system handles the complex signal processing and parameter optimization internally without requiring external programming, maintaining measurement precision while managing device complexity through autonomous operation.
Data Source
AI summary
A method of determining pacing therapy for an individual patient including determining representative electromechanical physiologic characteristics for a plurality of normal patients having a range of anatomical dimensions and developing a plurality of normal templates. Each template indicates the representative electromechanical physiologic characteristics of a group of normal patients having similar anatomical dimensions. The method can include measuring the anatomical dimensions of a dysfunctional patient, matching the dysfunctional patient with a template for normal patients having similar anatomical dimensions as the dysfunctional patient, determining the physiologic characteristics for the dysfunctional patient, determining indicated correction factors corresponding to any differences between the dysfunctional patient's physiologic characteristics and those of the matched template, and adjusting therapy delivery by any indicated correction factors to stimulate the patient in a pattern more closely matched to the physiologic characteristics of the matched template.