Finger Touch Detection for VR Controllers via Sensor Segmentation
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Solution Overview
Problem
Current virtual reality systems face challenges in transmitting large data sizes related to user holding gestures from VR controllers to the host or head-mounted displays, exceeding the payload capacity of RF signals.
Innovation Solution
A finger touch detecting method for handheld devices with touch sensors, where the processor detects finger distribution areas, distributes data sizes over specific sensors based on bit sizes, quantizes raw data, and transmits the quantized data to reduce overall data transmission, optimizing transmission efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the VR controller detects and transmits complete raw data from all touch sensors to characterize user holding gestures, then the measurement precision and reliability of gesture detection is improved, but the data transmission size exceeds the payload capacity of RF signals
Solution Approach 1:
The patent divides the touch detection area into multiple regions and only activates touch sensors in regions where fingers are actually detected. This segmentation approach allows the system to maintain high measurement precision for active regions while reducing overall data transmission size by excluding inactive regions from processing and transmission.
Solution Approach 2:
The patent dynamically adjusts the resolution and data format of touch sensor readings based on the detected finger distribution. By changing parameters such as bit depth and sampling rate in different regions, the system achieves adequate gesture characterization with reduced data size that fits within RF payload capacity.
2Reliability
If the system processes and transmits data from all touch sensors to ensure complete gesture information, then the reliability of gesture recognition is improved, but the transmission efficiency and productivity deteriorate due to excessive data size
Solution Approach 1:
The patent extracts only the essential touch sensor data from regions where fingers are detected, discarding data from inactive regions. This extraction principle maintains gesture recognition reliability by focusing on relevant information while improving transmission efficiency by reducing overall data volume to fit within communication constraints.
Solution Approach 2:
The patent applies partial processing to touch sensor data by only fully processing sensors in active finger regions while using simplified processing or no processing for inactive regions. This partial action approach maintains sufficient gesture recognition reliability while significantly improving transmission efficiency.
Data Source
AI summary
The embodiments of the disclosure provide a finger touch detecting method and a handheld device. The method includes: detecting a finger distribution area touched by a plurality of fingers on a touch detection area, wherein the touch detection area comprises a plurality of touch sensors, and the finger distribution area includes a plurality of specific sensors of the touch sensors; distributing a predetermined data size over the specific sensors, wherein each specific sensor is distributed with a corresponding bit size; obtaining a raw data detected by each of the specific sensors; quantizing the raw data of each of the specific sensors based on the corresponding bit size; and providing the quantized raw data of each of the specific sensors.