Portable Exertion Forecasting Device Using Segmented Sensor Modules
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Solution Overview
Problem
Current devices cannot accurately forecast and manage physiological parameters of a subject over a real itinerary, lacking the ability to adjust in real-time and account for environmental factors, making it difficult to monitor and optimize physical exertion during activities like rehabilitation, training, or sports.
Innovation Solution
A portable device equipped with sensors for physiological parameters, a positioning system, and a data-processing unit that generates forecasts based on the subject's position and environmental data, providing real-time feedback to the user to manage physical exertion effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a device collects and forecasts physiological parameters over a real itinerary, then the ability to manage physical exertion is improved, but the device complexity increases
Solution Approach 1:
The device is divided into distinct functional modules: a sensor unit for physiological parameter collection, a positioning unit for location data, a communication module for data transfer, and a processing unit for forecast generation. This segmentation allows each component to be optimized independently while working together to provide comprehensive exertion management capabilities.
Solution Approach 2:
The device integrates multiple functions into a single portable unit: it simultaneously collects physiological data, determines position, communicates with external systems, processes information, and generates forecasts. This multi-functionality consolidates what would otherwise require separate devices, managing complexity through integration rather than multiplication of components.
2Ease of operation
If the device provides real-time forecasting and feedback during physical activity, then the ease of operation is improved, but the use of energy increases
Solution Approach 1:
Instead of continuous processing, the device performs physiological parameter collection and forecast generation at periodic intervals. The sensor unit samples data at predetermined time intervals, and the processing unit generates forecasts at these discrete moments rather than continuously, significantly reducing energy consumption while maintaining real-time monitoring effectiveness.
Solution Approach 2:
The device automatically generates forecasts and provides feedback without requiring user intervention. The processing unit autonomously processes collected data, compares it against threshold values, and generates alerts or information for the user, eliminating the need for manual analysis and reducing the energy that would be required for user-side processing.
3Measurement precision
If the device includes sensors, positioning system, and data processing for physiological parameter forecasting, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The device combines multiple data sources (physiological sensors, positioning system, environmental data) and integrates them through a unified processing approach. By merging these diverse inputs and using a single processing unit to handle all data types and generate forecasts, the system achieves high measurement precision without proportionally increasing overall complexity.
4Ease of operation
If the device is made portable for use during real itineraries, then the ease of operation is improved, but the manufacturing precision requirements increase
Solution Approach 1:
The device employs a nested architecture where smaller components are integrated within larger housings. The sensor unit, positioning system, communication module, and processing unit are arranged in a compact nested configuration that minimizes overall device size and weight while maintaining manufacturing feasibility. This nesting approach allows portable form factor without excessive precision requirements.
Data Source
AI summary
A device (1) for assisting with physical exertion management, includes a physiological sensor, a positioning device, at least one memory in which data representative of the itinerary to be travelled during the physical exertion can be recorded, and at least one data processing unit organised so as to produce forecast data representative of the change in an physical exertion parameter over the remaining itinerary to be travelled by the individual, to compare these forecast data with predetermined data, and to produce and transmit a message, the content of which depends on the result of the comparison of the forecast data and the predetermined data, with a view to communicating the message to a user.


