SensIR: Detecting Hand Gestures with a Wearable Bracelet using Infrared Transmission and Reflection

Jess McIntosh, Asier Marzo, Mike Fraser

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

22 Citations (Scopus)

Abstract

Gestures have become an important tool for natural interaction with computers and thus several wearables have been developed to detect hand gestures. However, many existing solutions are unsuitable for practical use due to low accuracy, high cost or poor ergonomics. We present SensIR, a bracelet that uses near-infrared sensing to infer hand gestures. The bracelet is composed of pairs of infrared emitters and receivers that are used to measure both the transmission and reflection of light through/off the wrist. SensIR improves the accuracy of existing infrared gesture sensing systems through the key idea of taking measurements with all possible combinations of emitters and receivers. Our study shows that SensIR is capable of detecting 12 discrete gestures with 93.3% accuracy. SensIR has several advantages compared to other systems such as high accuracy, low cost, robustness against bad skin coupling and thin form-factor.
Original languageEnglish
Title of host publicationProceedings of the 30th Annual ACM Symposium on User Interface Software and Technology (UIST 2017)
PublisherAssociation for Computing Machinery (ACM)
Pages593
Number of pages597
DOIs
Publication statusPublished - 20 Oct 2017

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