Wearable Sensor Skin Compression Correction
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Solution Overview
Problem
Wearable devices face challenges in accurately determining physiological values due to skin compression, which varies among users and over time, affecting the accuracy of signals acquired by sensors.
Innovation Solution
The use of image and video analysis, combined with machine learning algorithms and time-of-flight signals, to determine skin compression by analyzing features such as indentations on the skin, allowing for the adjustment of wearable device placement and fastening to optimize signal accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If skin compression is increased to secure the wearable device, then device stability is improved, but signal accuracy deteriorates
Solution Approach 1:
The system dynamically adjusts fastening parameters (tightness, position) based on real-time skin compression measurements and physiological signal quality. When skin compression is detected to be suboptimal, the system modifies fastening parameters to achieve better signal quality while maintaining device stability.
Solution Approach 2:
The system continuously monitors physiological signals and skin compression characteristics, then uses this feedback to adjust fastening parameters. The feedback loop enables the system to maintain optimal signal accuracy by adapting to changes in skin compression over time during device wear.
2Measurement precision
If skin compression is decreased to improve signal accuracy, then signal accuracy is improved, but device stability deteriorates
Solution Approach 1:
The system dynamically adjusts fastening parameters (tightness, position) based on real-time skin compression measurements and physiological signal quality. When skin compression is detected to be suboptimal, the system modifies fastening parameters to achieve better signal quality while maintaining device stability.
Solution Approach 2:
The system continuously monitors physiological signals and skin compression characteristics, then uses this feedback to adjust fastening parameters. The feedback loop enables the system to maintain optimal signal accuracy by adapting to changes in skin compression over time during device wear.
3Stability of the object's composition
If fastening is tightened to prevent device movement, then device stability is improved, but skin compression increases causing reduced signal accuracy
Solution Approach 1:
The system dynamically adjusts fastening parameters (tightness, position) based on real-time skin compression measurements and physiological signal quality. When skin compression is detected to be suboptimal, the system modifies fastening parameters to achieve better signal quality while maintaining device stability.
Solution Approach 2:
The system continuously monitors physiological signals and skin compression characteristics, then uses this feedback to adjust fastening parameters. The feedback loop enables the system to maintain optimal signal accuracy by adapting to changes in skin compression over time during device wear.
4Measurement precision
If fastening is loosened to reduce skin compression, then signal accuracy is improved, but device stability deteriorates
Solution Approach 1:
The system dynamically adjusts fastening parameters (tightness, position) based on real-time skin compression measurements and physiological signal quality. When skin compression is detected to be suboptimal, the system modifies fastening parameters to achieve better signal quality while maintaining device stability.
Solution Approach 2:
The system continuously monitors physiological signals and skin compression characteristics, then uses this feedback to adjust fastening parameters. The feedback loop enables the system to maintain optimal signal accuracy by adapting to changes in skin compression over time during device wear.
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
This approach improves the accuracy of physiological values determined by wearable devices by accounting for skin compression, enhances user comfort and safety, and provides recommendations for optimal device placement and fastening.
Implementation Method 1
depth data indicative of elevations of one or more portions of one or more features on the body may be determined using time-of-flight signals
Data Source
AI summary
A wearable device may compress the skin of a user when worn, which may affect values determined using sensors of the device. To determine the effect of skin compression on the values, a time-of-flight signal, images, or frames of video data that depict a portion of the body having indentations from wearing the device may be acquired. Characteristics of the images, such as shadows associated with the indentations, may be processed using a machine learning algorithm or mathematical function to determine a depth of various portions of the indentations. Depth data from the time of flight signal may be used to refine or modify these determined depths. The amount of skin compression associated with the indentations may be used to modify signals acquired using sensors, or output a recommendation for a band or other method for securing the device.