SensIR: Detecting hand gestures with a wearable bracelet using infrared transmission and reflection

Jess McIntosh; Asier Marzo; Mike Fraser

doi:10.1145/3126594.3126604

SensIR: Detecting hand gestures with a wearable bracelet using infrared transmission and reflection

Jess McIntosh, Asier Marzo, Mike Fraser

University of Bristol

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

69 Citations (SciVal)

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 language	English
Title of host publication	UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology
Publisher	Association for Computing Machinery
Pages	593-597
Number of pages	5
ISBN (Electronic)	9781450349819
DOIs	https://doi.org/10.1145/3126594.3126604
Publication status	Published - 20 Oct 2017
Event	30th Annual ACM Symposium on User Interface Software and Technology, UIST 2017 - Quebec City, Canada Duration: 22 Oct 2017 → 25 Oct 2017

Publication series

Name	UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology

Conference

Conference	30th Annual ACM Symposium on User Interface Software and Technology, UIST 2017
Country/Territory	Canada
City	Quebec City
Period	22/10/17 → 25/10/17

Funding

This research was supported by EPSRC Doctoral Training funding through grant EP/M507994/1.

Keywords

Gesture recognition
Infrared
Wearables

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Human-Computer Interaction
Software

Access to Document

10.1145/3126594.3126604

Cite this

McIntosh, J., Marzo, A., & Fraser, M. (2017). SensIR: Detecting hand gestures with a wearable bracelet using infrared transmission and reflection. In UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology (pp. 593-597). (UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology). Association for Computing Machinery. https://doi.org/10.1145/3126594.3126604

SensIR: Detecting hand gestures with a wearable bracelet using infrared transmission and reflection. / McIntosh, Jess; Marzo, Asier; Fraser, Mike.
UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery, 2017. p. 593-597 (UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology).

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

McIntosh, J, Marzo, A & Fraser, M 2017, SensIR: Detecting hand gestures with a wearable bracelet using infrared transmission and reflection. in UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology. UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology, Association for Computing Machinery, pp. 593-597, 30th Annual ACM Symposium on User Interface Software and Technology, UIST 2017, Quebec City, Canada, 22/10/17. https://doi.org/10.1145/3126594.3126604

McIntosh J, Marzo A, Fraser M. SensIR: Detecting hand gestures with a wearable bracelet using infrared transmission and reflection. In UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery. 2017. p. 593-597. (UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology). doi: 10.1145/3126594.3126604

McIntosh, Jess ; Marzo, Asier ; Fraser, Mike. / SensIR : Detecting hand gestures with a wearable bracelet using infrared transmission and reflection. UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery, 2017. pp. 593-597 (UIST 2017 - Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology).

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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.",

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SensIR: Detecting hand gestures with a wearable bracelet using infrared transmission and reflection

Abstract

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Keywords

ASJC Scopus subject areas

Access to Document

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