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Capturing Representative Hand Use at Home Using Egocentric Video in Individuals with Upper Limb Impairment

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Robust Finger Interactions with COTS Smartwatches via Unsupervised Siamese Adaptation.

Wenqiang Chen¹, Ziqi Wang², Pengrui Quan²

¹Massachusetts Institute of Technology USA.

Proceedings of the ACM Symposium on User Interface Software and Technology. ACM Symposium on User Interface Software and Technology

|March 22, 2024

Summary

This summary is machine-generated.

ViWatch enables robust finger interactions on smartwatches using a single IMU sensor. This unsupervised system achieves 97% accuracy, offering a convenient alternative to small smartwatch interfaces.

Keywords:

Finger Interaction Gesture Recognition Unsupervised Adversarial Training Vibration Sensing

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Area of Science:

Human-computer interaction
Wearable technology
Sensor fusion

Background:

Smartwatches and wearable devices offer convenience but have limited interfaces.
Small screens hinder user interaction and computing functionality.
Existing solutions often require complex calibration or multiple sensors.

Purpose of the Study:

To introduce ViWatch, a novel system for robust finger interaction on smartwatches.
To overcome limitations of small smartwatch interfaces using ubiquitous IMU sensors.
To develop an unsupervised learning method for accurate and adaptable interaction detection.

Main Methods:

Designed an unsupervised Siamese adversarial learning framework.
Utilized a single Inertial Measurement Unit (IMU) sensor common in smartwatches.
Developed a real-time system deployed on commodity smartwatches.
Conducted extensive testing with over 100 volunteers.

Main Results:

Achieved approximately 97% system accuracy over a week-long evaluation.
Demonstrated robustness against variations in hand shape, finger activity, and device placement.
User study indicated a preference for the unsupervised approach over supervised calibration.

Conclusions:

ViWatch provides a highly accurate and adaptable solution for finger-based interactions on smartwatches.
The unsupervised learning method eliminates the need for tedious supervised calibration.
ViWatch enhances smartwatch usability and opens possibilities for new mobile applications.