Handheld Multi-Sensor Telehealth Device with Segmented Architecture
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Solution Overview
Problem
Current medical diagnostic devices are large, bulky, and lack portability and usability, while portable devices are limited in accuracy, reliability, and functionality due to size and power constraints, and lack the ability to provide real-time, personalized insights.
Innovation Solution
A hand-held medical diagnostic device integrating multiple health monitoring sensors with proprietary calibration methods and sensor shielding for accuracy, and complex analysis algorithms in application-specific integrated circuits for efficient processing, along with an intuitive user interface and optimized power management for extended operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If large stationary medical diagnostic equipment is used, then measurement precision and reliability are improved, but portability and ease of operation deteriorate
Solution Approach 1:
The patent divides the medical diagnostic system into modular sensor components that can be independently positioned on the patient's body. Each sensor module is small and can be placed by a healthcare provider, eliminating the need for a single large stationary device while maintaining diagnostic accuracy through distributed measurement points.
Solution Approach 2:
The patent introduces a mobile computing device as an intermediary between the sensor components and the diagnostic system. This intermediary collects data from multiple sensors, performs processing, and communicates with healthcare providers, enabling sophisticated diagnostics without requiring stationary equipment at each measurement point.
2Adaptability or versatility
If multiple sensors are integrated into a single portable device, then functionality and comprehensive health monitoring are improved, but device complexity and interference between sensors increase
Solution Approach 1:
Instead of integrating all sensors into one device, the patent segments sensor functionality across multiple separate, body-mounted components. Each sensor measures a specific parameter (temperature, heart rate, respiration, etc.) independently, reducing interference between sensors while maintaining comprehensive monitoring capabilities.
Solution Approach 2:
The patent creates a universal platform where a mobile computing device can interface with multiple different sensor types through standardized communication protocols. This allows the system to monitor various health parameters using different sensor technologies without requiring all sensors to coexist in a single device, reducing mutual interference.
3Adaptability or versatility
If multiple sensors are integrated into a portable device, then comprehensive monitoring is improved, but power consumption and battery life deteriorate
Solution Approach 1:
The patent distributes power consumption across multiple small sensor components rather than concentrating it in one power-intensive device. Each sensor module has its own small battery that can be independently managed and replaced, extending the overall operational duration by allowing selective recharging or replacement of individual low-power components.
Solution Approach 2:
The patent implements periodic data transmission and processing cycles rather than continuous operation. Sensors sample data at intervals, and the mobile computing device processes information periodically rather than continuously, significantly reducing power consumption and extending battery life while maintaining comprehensive monitoring capabilities during active periods.
4Productivity
If AI algorithms are integrated into portable medical devices, then real-time personalized insights are improved, but processing power requirements exceed available computational resources
Solution Approach 1:
The patent introduces a mobile computing device as an intermediary that performs AI processing and data analysis. This intermediary has sufficient computational resources to run complex AI algorithms locally, enabling real-time personalized health insights without requiring the AI processing power to be integrated directly into the sensor components themselves.
Solution Approach 2:
The patent moves AI processing from the sensor level to the cloud or remote server level, adding a new dimension to the system architecture. This allows sophisticated machine learning models to process data from multiple sensors in real-time without constraining the computational power available at the portable device level, while still providing timely insights through networked communication.
Data Source
AI summary
This invention presents a multisensor-connected, AI-enabled telehealth system for assisting healthcare providers with differential diagnosis and patients with early health concern detection. The system comprises a multi-sensor medical device with at least seven sensors, a secure cloud-based platform, and an interactive telehealth module. The device preprocesses and securely transmits patient information to the cloud platform, where an ensemble of deep learning models analyzes the data to generate ranked potential diagnoses with likelihood scores. The telehealth module facilitates communication between providers, patients, and the cloud platform, presenting visualizations and receiving feedback. The system continuously updates and fine-tunes its models using incremental learning algorithms, adapting to new data while retaining previous knowledge. It also generates alerts for providers and patients when deviations from normal physiological patterns are detected, accompanied by explainable AI visualizations.