Sensor Adapter Module for Mobile Biological Data
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Solution Overview
Problem
Existing mobile communication devices require deep integration into hardware and software, and suffer from limitations in data communication capabilities when capturing and processing biological and medical data.
Innovation Solution
A mobile communication device system that includes a sensor for capturing biological and medical data, with an adapter module connected to a subscriber identity module and a radio interface, allowing for wireless communication using standards like ZigBee or NFC, enabling data processing and transmission without significant impact on the device's hardware and software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors are deeply integrated into the mobile phone hardware and software, then biological and medical data can be captured and processed, but the device complexity and impact on existing terminal hardware and software increase
Solution Approach 1:
The patent introduces an adapter module as an intermediary component that bridges the sensor and the mobile phone without requiring deep integration into the phone's core hardware and software. The adapter module contains a processor that handles data processing independently, while only requiring basic communication interfaces (such as UART, I2C, or SPI) with the mobile phone, thus resolving the contradiction between data capture capability and device complexity
Solution Approach 2:
The system is segmented into independent functional modules: the sensor module for data acquisition, the adapter module for data processing and communication, and the mobile phone for user interaction and data display. This segmentation allows each module to be optimized independently and simplifies the integration process, reducing the impact on the mobile phone's existing hardware and software architecture
2Device complexity
If simple processing steps are used (comparing data with threshold values), then the system remains simple, but the interpretation capability and feedback quality are limited
Solution Approach 1:
The processing complexity is made dynamic and adaptable. The adapter module's processor can perform simple threshold comparisons when basic monitoring is sufficient, but can also execute more complex analysis algorithms when needed. The system dynamically adjusts the processing level based on the specific application requirements, user needs, and available computational resources, thereby resolving the contradiction between processing simplicity and interpretation quality
Solution Approach 2:
The system implements multi-level feedback mechanisms. Basic feedback includes threshold-based alerts for immediate attention. Advanced feedback involves comprehensive data analysis, pattern recognition, and predictive insights that provide users with actionable health recommendations. The feedback quality adapts to the processing capability and requirements, ensuring information is neither lost nor unnecessarily complex
Data Source
AI summary
There is provided a mobile communication device. An exemplary mobile communication device comprises an input unit, a display and a processing unit being connected with a subscriber identity module and with an adapter module, wherein the adapter module is in communication with at least one sensor capturing biological and/or medical data of the user of the mobile communication device.