Bone Conduction Exercise Sensor for Motion Artifact Suppression
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Solution Overview
Problem
Existing exercise physiological monitoring devices cause discomfort during high-intensity exercises due to the need for close skin contact, leading to instability in measured physiological data.
Innovation Solution
An exercise physiological sensing system using a bone conduction object with a physiological sensor that detects signals from the otic bones, combined with a signal-to-noise ratio analysis module and computation module, which processes the signals to suppress motion artifacts and generate a stable heart rate signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physiological recorders are worn in close contact with the skin to prevent measurement errors during high-intensity exercise, then measurement precision is improved, but user comfort deteriorates
Solution Approach 1:
The patent introduces bone (otic bones) as an intermediary medium for signal detection. Instead of placing sensors directly on moving skin surfaces, the sensor detects physiological signals through the bone structure, which remains stable during exercise. This intermediary approach maintains measurement precision while eliminating the discomfort of tight skin contact.
Solution Approach 2:
The patent replaces the mechanical contact-based detection system (sensors pressing against skin) with a bone conduction-based detection system. By utilizing the bone's natural vibration and conduction properties, the system achieves accurate physiological monitoring without requiring mechanical pressure or tight fitting, thus improving comfort while maintaining precision.
2Ease of operation
If traditional skin-contact sensors are used for physiological monitoring, then ease of device placement is improved, but measurement stability during high-intensity exercise deteriorates
Solution Approach 1:
The patent uses bone structure as a stable intermediary that bridges the sensor and the physiological signal source. The bone provides a fixed, stable platform for signal detection that is not affected by skin movement or sweat, thereby maintaining signal stability while keeping the device externally placed and easy to position.
Solution Approach 2:
The patent transitions from surface-level skin detection to deeper bone-level detection. By moving the detection interface from the soft, moving skin surface to the harder, more stable bone structure beneath, the system achieves superior signal stability during dynamic exercise while maintaining external device placement.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides a stable and comfortable means to monitor heart rate during exercise, improving data stability and allowing users to be aware of their surroundings while exercising.
Implementation Method 1
The bone conduction object has a physiological sensor. The physiological sensor detects a physiological signal of otic bones of the user.
Data Source
AI summary
An exercise physiological sensing system, a motion artifact suppression processing method and a motion artifact suppression processing device for obtaining a stable exercise heart rate signal of a user during exercise are provided. The exercise physiological sensing system includes a bone conduction object, a signal-to-noise ratio analysis module, and a computation module. The bone conduction object has a physiological sensor. The physiological sensor detects a physiological signal of otic bones of the user. The signal-to-noise ratio analysis module is coupled to the physiological sensor and detects a stability of the physiological signal of the otic bones. The computation module is coupled to the signal-to-noise ratio analysis module and generates the stable exercise heart rate signal according to the physiological signal of the otic bones. Accordingly, the exercise physiological sensing system can effectively improve the detected stability of an exercise physiological signal.