View source for 18596357. Fitting Algorithm to Determine Best Stimulation Parameter from a Patient Model in a Spinal Cord Stimulation System simplified abstract (Boston Scientific Neuromodulation Corporation)

=Fitting Algorithm to Determine Best Stimulation Parameter from a Patient Model in a Spinal Cord Stimulation System=


==Organization Name==

[[:Category:Boston Scientific Neuromodulation Corporation|Boston Scientific Neuromodulation Corporation]]


[[Category:Boston Scientific Neuromodulation Corporation]]

==Inventor(s)==

[[:Category:Ismael Huertas Fernandez of Madrid (ES)|Ismael Huertas Fernandez of Madrid (ES)]][[Category:Ismael Huertas Fernandez of Madrid (ES)]]

[[:Category:Que T. Doan of West Hills CA (US)|Que T. Doan of West Hills CA (US)]][[Category:Que T. Doan of West Hills CA (US)]]

[[:Category:Michael A. Moffitt of Solon OH (US)|Michael A. Moffitt of Solon OH (US)]][[Category:Michael A. Moffitt of Solon OH (US)]]

[[:Category:Changfang Zhu of Valencia CA (US)|Changfang Zhu of Valencia CA (US)]][[Category:Changfang Zhu of Valencia CA (US)]]

==Fitting Algorithm to Determine Best Stimulation Parameter from a Patient Model in a Spinal Cord Stimulation System - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18596357 titled 'Fitting Algorithm to Determine Best Stimulation Parameter from a Patient Model in a Spinal Cord Stimulation System

'''Simplified Explanation:'''
The patent application describes methods for determining stimulation parameters for a patient with a stimulator device, using fitting information and a model specific to the patient.

'''Key Features and Innovation:'''
* Model received at an external system indicating preferred stimulation parameters for the patient
* Fitting information, including symptoms, stimulation during fitting, and phenotype data, used to determine stimulation parameters
* Training data applied to fitting information to select optimal stimulation parameters from the model

'''Potential Applications:'''
This technology can be applied in medical settings where patients require personalized stimulation parameters for their stimulator devices.

'''Problems Solved:'''
The technology addresses the challenge of determining the most effective stimulation parameters for individual patients with stimulator devices.

'''Benefits:'''
* Personalized stimulation parameters for improved patient outcomes
* Efficient and accurate selection of stimulation settings based on fitting information
* Enhanced customization and optimization of stimulator device usage

'''Commercial Applications:'''
Potential commercial applications include medical device companies, healthcare providers, and research institutions looking to enhance patient care through personalized stimulation settings.

'''Prior Art:'''
Readers can explore prior research on personalized stimulation parameters for patients with stimulator devices in medical journals and patent databases.

'''Frequently Updated Research:'''
Stay informed about the latest advancements in personalized stimulation technologies for medical devices by following relevant research publications and conferences.

'''Questions about personalized stimulation parameters for patients with stimulator devices:'''
1. How does the technology in this patent application improve patient outcomes compared to traditional methods?
2. What are the key factors that influence the selection of optimal stimulation parameters for individual patients?


==Original Abstract Submitted==

Methods for determining stimulation for a patient having a stimulator device are disclosed. A model is received at an external system indicative of a range or volume of preferred stimulation parameters, which model is preferably specific to and determined for the patient. The external system receives a plurality of pieces of fitting information for the patient, including information indicative of a symptom of the patient, information indicative of stimulation provided by the stimulator device during a fitting procedure, and/or phenotype information for the patient. The external system determines one or more sets of stimulation parameters for the patient using the pieces of fitting information. In one example, training data is applied to the pieces of fitting information to select the one or more sets of stimulation parameters from the range or volume of preferred stimulation parameters in the model.



[[Category:A61N1/372]]
[[Category:A61N1/36]]
[[Category:CPC_A61N1/372]]