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A Knitted Sensing Glove for Human Hand Postures Pattern Recognition.

Seulah Lee¹, Yuna Choi¹, Minchang Sung¹

¹Department of Electrical and Electronic Engineering, Hanyang University, Ansan 15588, Korea.

Sensors (Basel, Switzerland)

|March 6, 2021

Summary

This summary is machine-generated.

This study introduces a novel knitted glove with integrated strain sensors for accurate hand posture recognition. The simple manufacturing process offers a cost-effective solution for wearable sensor technology.

Keywords:

data glove fabric sensor knitted sensor pattern recognition wearable strain sensor

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Area of Science:

Wearable technology
Textile engineering
Biomedical engineering

Background:

Flexible sensors for data gloves face manufacturing challenges impacting wearability.
Existing methods often involve complex fabrication and integration processes.

Purpose of the Study:

To develop a seamlessly integrated sensing glove using a knitting technique.
To enable accurate hand posture recognition through embedded strain sensors.

Main Methods:

A knitted glove was fabricated using conductive yarn for strain sensors and non-conductive yarn for the glove body.
Electrical resistance variations were measured against hand movement angles and speeds.
Hand posture pattern recognition experiments were conducted with 10 subjects performing 10 distinct postures.

Main Results:

The sensing glove demonstrated distinct electrical resistance variations based on movement angle and speed.
Average classification accuracy for hand posture recognition reached 94.17% using individual subject data.
Accuracy for specific grasp postures reached 97.1%, with an 89.5% average using combined subject data.

Conclusions:

The knitted sensing glove effectively enables accurate hand posture recognition.
The simplified knitting fabrication process reduces manufacturing complexity and cost.
This technology shows significant potential for practical applications in wearable sensing.