Multi-Spectral Wearable Sensor for Light Exposure Measurement
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Solution Overview
Problem
Current wearable devices fail to accurately measure non-visual light exposure, physical activity, and sleep patterns, often providing meaningless or erroneous information due to improper placement and limited spectral measurement ranges, which affects the assessment of light's impact on human health and circadian rhythms.
Innovation Solution
A wearable device equipped with a 3-axis accelerometer, temperature measurement unit, and multi-spectral light radiation sensor to measure wavelengths from 290 nm to 1150 nm, allowing for accurate data analysis of acceleration, inclination, temperature, and light radiation over extended periods, providing detailed insights into physical activity, sleep quality, and light exposure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a multi-spectral sensor measuring 290 nm to 1150 nm is used, then measurement precision of light exposure is improved, but device complexity increases
Solution Approach 1:
The wearable device integrates multiple measurement functions into a single platform: multi-spectral light radiation measurement (290-1150 nm), temperature measurement, and acceleration measurement. This multi-functional approach allows comprehensive health monitoring while managing device complexity through unified system architecture.
Solution Approach 2:
The light radiation measurement is divided into multiple spectral bands (UV, blue, green, red, infrared) with specific sensors for each range. This segmentation allows precise measurement of different wavelength components that affect circadian rhythms differently, while enabling selective data processing based on measurement needs.
2Reliability
If the device measures multiple parameters including temperature and acceleration, then reliability of sleep assessment is improved, but device complexity increases
Solution Approach 1:
The device combines temperature measurement, acceleration measurement, and light radiation measurement into a single integrated system. This merging of multiple measurement modalities enables comprehensive sleep assessment by analyzing correlations between body temperature, movement patterns, and light exposure, thereby improving reliability while managing complexity through unified hardware and software architecture.
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 device provides improved and accurate information on light type exposure, physical activity, and sleep quality, enabling health-related recommendations and environmental adjustments to optimize light exposure for better health outcomes.
Implementation Method 1
a light radiation measurement unit configured to provide light radiation data, said light radiation measurement unit comprising at least one multi-spectral sensor configured to measure wavelength bands over the range 290 nm to 1150 nm
Implementation Method 2
a 3-axis accelerometer unit configured to provide acceleration data and inclination data
Implementation Method 3
a temperature measurement unit configured to provide temperature data, the temperature measurement unit being configured to measure the user body temperature in the first wearing position
Data Source
AI summary
A wearable health and lifestyle device including at least a measurement module configured to be worn by a user in at least a first wearing position, the measurement module comprising a 3-axis accelerometer unit configured to provide acceleration data and inclination data, a temperature measurement unit configured to provide temperature data, a light radiation measurement unit configured to provide light radiation data, said light radiation measurement unit comprising at least one multi-spectral sensor configured to measure wavelength bands over the range 290 nm to 1150 nm, a storage module configured to receive and store said acceleration data, said inclination data, said temperature data and said light radiation data, and an analysis module configured to analyze a data set comprising acceleration data, inclination data, temperature data and light radiation data.