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Recognizing the Operating Hand and the Hand-Changing Process for User Interface Adjustment on Smartphones.

Hansong Guo1, He Huang2, Liusheng Huang3

  • 1School of Computer Science and Technology, University of Science and Technology of China, Hefei 230000, China. guohanso@mail.ustc.edu.cn.

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Summary

New smartphone systems automatically detect the hand being used for operation. This improves user experience by adjusting interfaces without manual input, enhancing usability for all users.

Keywords:
accelerometer and gyroscopehand-changing process detectionoperating hand recognitionsmartphonesupervised classificationtouchscreenuser interface adjustment

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Area of Science:

  • Human-Computer Interaction
  • Mobile Computing
  • Machine Learning

Background:

  • Larger smartphone screens degrade single-hand operability, particularly for female users.
  • Current solutions require manual input for hand switching, disrupting user experience.
  • Adaptive user interfaces necessitate accurate detection of the operating hand.

Purpose of the Study:

  • To develop and evaluate novel systems for automatic operating hand recognition and hand-changing detection.
  • To improve smartphone user experience through intelligent, context-aware interface adjustments.
  • To enable frequent hand-switching without compromising usability.

Main Methods:

  • Developed a system using touchscreen traces for operating hand recognition.
  • Implemented a second system utilizing accelerometer and gyroscope data for hand-changing detection.
  • Employed supervised classifiers trained on refined sensor and trace features.

Main Results:

  • Achieved 94.1% precision and 94.1% True Positive Rate (TPR) for hand recognition using touchscreen traces.
  • Attained 93.9% precision and 93.7% TPR for hand-changing detection using motion sensors.
  • Reported low False Positive Rates (FPR) of 2.6% and 0.7% respectively.
  • Demonstrated high accuracy for independent and joint system operation.

Conclusions:

  • Proposed systems offer a convenient and practical solution for adaptive smartphone interfaces.
  • Automatic hand detection and adjustment significantly enhance user experience on large-screen devices.
  • The developed methods provide a foundation for more intuitive and accessible mobile interactions.