Wearable Activity Detection via Wireless Signal
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Solution Overview
Problem
Current activity trackers have limited ability to distinguish between different types of activities without manual input, leading to inaccurate interpretation of activity and well-being.
Innovation Solution
A wearable device equipped with a wireless receiver circuit and sensors that automatically identify activity types using external signals and physiological/behavioral parameters, employing algorithms specific to the detected activity for enhanced data acquisition and feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual input is used to identify activity types, then the device can respond to predetermined questions, but the user intervention increases and accuracy is limited
Solution Approach 1:
The wearable device automatically identifies activity types by receiving external signals (RFID, NFC, Bluetooth) from activity-specific devices without requiring manual user input. The processing circuit autonomously determines activity type based on received signal information, eliminating the need for users to manually respond to questions about their activity type.
Solution Approach 2:
The patent replaces manual mechanical input (user pressing buttons or typing) with wireless electromagnetic signal transmission. External devices transmit activity type information via RFID, NFC, or Bluetooth signals, which the wearable device's wireless receiver circuit automatically captures and processes to identify the activity type.
2Measurement precision
If multiple sensors are used to measure physiological parameters, then the measurement accuracy improves, but the device complexity increases
Solution Approach 1:
The processing circuit dynamically selects which sensors to activate and which algorithms to execute based on the identified activity type. For example, if running is detected, the system activates sensors and algorithms specific to running analysis, while deactivating those not needed for this activity, thereby maintaining high measurement accuracy without permanently increasing device complexity.
Solution Approach 2:
Different sensors and algorithms are optimized for specific activity types. The system applies activity-specific measurement protocols and data processing methods tailored to each activity category (e.g., running, cycling, swimming), ensuring high measurement precision for each specific physiological parameter relevant to that activity.
3Extent of automation
If automated activity detection is implemented, then user intervention is reduced, but the device requires additional components increasing complexity
Solution Approach 1:
The wearable device incorporates a multi-functional wireless receiver circuit capable of receiving signals from multiple external devices using different communication protocols (RFID, NFC, Bluetooth). This universal receiver handles various activity identification scenarios without requiring separate dedicated components for each communication method, reducing overall device complexity while maintaining high automation capability.
Data Source
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Figure 3A~3C
AI summary
In an embodiment, a wearable device (12) is disclosed that automates the detection and determination of a type of activity, and both measures physiological and behavioral parameters and computes information corresponding to measured physiological parameters based on the determined type of activity. An embodiment of the wearable device provides these features by wirelessly receiving a signal with information coded therein that enables the wearable device to automatically detect and identify the type of activity in which a person (82) is engaged. The determination of the type of activity enables a more accurate computation of information that is specific to the activity in which the person is engaged, the computation of information based on the measured physiological and behavioral parameter.