LDAF Sensor Proximity Detection Through Saturated-Signal Filtering
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Solution Overview
Problem
Existing mobile computing devices face challenges in accurately determining user proximity and biometrics, particularly body temperature, due to environmental factors and sensor saturation, leading to inaccurate readings.
Innovation Solution
A mobile computing device equipped with a laser direct autofocus (LDAF) sensor system that emits optical signals towards the user's forehead, processes reflected signals using a collector array, and calculates a proximity metric by discarding invalid signals to ensure accurate biometric readings within a threshold distance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical signals are emitted towards the user's forehead using LDAF sensor, then proximity detection capability is improved, but sensor saturation from environmental factors occurs leading to measurement errors
Solution Approach 1:
The patent segments the reflected optical signals by spatial position, dividing the collector array into multiple regions and analyzing signals from different segments. This allows the system to identify and exclude saturated or erroneous signals from specific regions while retaining valid signals from other regions, thereby maintaining measurement precision while improving reliability
Solution Approach 2:
The patent changes the parameter of signal validation by introducing multiple criteria including signal intensity thresholds, spatial distribution patterns, and temporal consistency checks. By dynamically adjusting validation parameters based on environmental conditions, the system maintains accurate proximity detection while filtering out saturated signals that would compromise biometric measurement reliability
2Measurement precision
If all reflected optical signals are processed to determine proximity metric, then measurement accuracy is improved, but processing and storage requirements increase
Solution Approach 1:
The patent extracts only the essential features from reflected optical signals by identifying and retaining signals that meet validity criteria while discarding invalid signals. This extraction process reduces the data volume requiring processing and storage while preserving the information necessary for accurate proximity metric determination
Solution Approach 2:
The patent applies different processing quality levels to different signal segments based on their validity. Valid signals from the region of interest receive full processing attention for accurate proximity calculation, while invalid or saturated signals are quickly identified and discarded with minimal processing, thereby improving overall processing efficiency without compromising measurement precision
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
Ensures precise biometric measurements by minimizing erroneous proximity determinations, reducing processing and storage requirements, and enhancing operational efficiency by reserving resources for other tasks.
Implementation Method 1
emitting, by an emitter of the LDAF sensor, one or more optical signals in a direction towards the user
Implementation Method 2
receiving, by a collector array of the LDAF sensor, one or more reflected optical signals associated with the one or more optical signals emitted by emitter
Implementation Method 3
obtaining, by a temperature sensor of the mobile computing device, temperature sensor data associated with an object in the FOV of the LDAF sensor
Data Source
AI summary
Computing systems, computing devices, and computer-implemented methods are provided. In one aspect, a mobile computing device includes a display and an image capture assembly having an image capture device and one or more sensors. The mobile computing device further includes one or more processors configured to perform one or more operations. For instance, the operations may include obtaining optical sensor data, processing the optical sensor data to determine a proximity metric for the user, and, subsequent to determining the proximity metric for the user, determining one or more biometrics the user.