Efficacy Model Mapping for Medical Treatment Timing
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Solution Overview
Problem
Incorrect administration of medical treatments, particularly in chronic disease management, can negatively impact treatment success and overall health outcomes, especially in individuals with cognitive and visual coordination issues.
Innovation Solution
A computer-implemented method that utilizes personal care appliances, such as oral care devices, to determine the optimal therapeutic effect point for medical treatments by receiving user data and sensor data from the appliance, mapping this data to an efficacy model, and adjusting parameters such as usage time or treatment administration to maximize treatment efficacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If treatment administration is monitored in an unsupervised home setting relying on unregular patient-GP communication, then patient autonomy and convenience are improved, but treatment adherence and efficacy monitoring become difficult
Solution Approach 1:
The system implements continuous feedback loops where sensor data from personal care appliances is automatically transmitted to the server, which then provides feedback to both patients and GPs. This automated feedback mechanism ensures reliable treatment adherence monitoring while maintaining patient autonomy in the home setting.
Solution Approach 2:
A server acts as an intermediary between the personal care appliances and the GP, receiving sensor data from appliances and transmitting treatment recommendations back to patients. This intermediary enables reliable monitoring without requiring direct unsupervised patient-GP communication.
2Ease of operation
If personal care routines are performed without optimizing timing relative to therapeutic effect windows, then patient convenience is improved, but treatment efficacy deteriorates
Solution Approach 1:
The system determines optimal therapeutic time windows in advance based on medication characteristics and patient-specific factors. Personal care routines are then scheduled within these pre-determined optimal windows, ensuring treatment efficacy while maintaining patient convenience through automated timing recommendations.
Solution Approach 2:
The system dynamically adjusts personal care routine timing based on real-time sensor data, therapeutic effect windows, and patient feedback. This dynamic optimization ensures that routines are performed at the most effective times while adapting to patient needs and maintaining convenience.
3Measurement precision
If sensor data from personal care appliances is collected and mapped to efficacy models, then treatment efficacy determination is improved, but data processing complexity increases
Solution Approach 1:
The data processing system is segmented into modular components: sensor data collection from appliances, data transmission to server, efficacy model mapping, and recommendation generation. This segmentation reduces overall system complexity while enabling precise efficacy determination through specialized processing at each stage.
Data Source
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AI summary
The subject-matter of the present disclosure relates to a computer implemented method (100) for determining an optimised efficacy of a medical treatment based on usage of a personal care appliance (402). The method comprises receiving (101) user-related data comprising a time of administration of the medical treatment, receiving (102) sensor data (t1-t4) from the personal care appliance captured during usage of the personal care appliance, and a usage time of the personal care appliance, mapping (103) the received sensor data to an efficacy model (302) corresponding to the medical treatment, based on the received user-related data and usage time of the personal care appliance, determining (104) a first treatment efficacy based on the mapping to the efficacy model, and determining (105) a second treatment efficacy based on changing the mapping by changing at least one of the usage time of the personal care appliance or the efficacy model (304, 306).