Comparing the placement of two arm-worn devices for recognizing dynamic hand gestures

Kathrin Kefer, Clemens Holzmann, Rainhard Findling

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

5 Citations (Scopus)

Abstract

Dynamic hand gestures have become increasingly popular as an input modality for interactive systems. There exists a variety of arm-worn devices for the recognition of hand gestures, which differ not only in their capabilities, but also in the arm positions where they are worn. The aim of this paper is to investigate the effect of placement of such devices on the accuracy for recognizing dynamic hand gestures (e.g. waving the hand). This is relevant as different devices require different positions and thus differ in the achievable recognition accuracy. We have chosen two positions on the forearm: on the wrist and right below the elbow. These positions are interesing as smartwatches are usually worn on the wrist and devices using EMG sensors for the detection of static hand gestures (e.g. spreading the fingers) have to be worn right below the elbow. We used an LG G Watch worn on the wrist and a Myo armband from Thalmic Labs worn below the elbow. Both are equipped with three-axis accelerometers, which we used for gesture recognition. Our hypothesis was that the wristworn device would have a better recognition accuracy, as dynamic hand gestures have a bigger action radius on the wrist and therefore lead to bigger acceleration values. We conducted a comparative study with nine participants that performed eight simple, dynamic gestures on both devices. We tested the 4320 gesture samples with different classifiers and feature sets. Although the recognition results for the wrist-worn device were higher, the difference was not significant due to the substantial variation across participants.

Original languageEnglish
Title of host publication14th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2016 - Proceedings
EditorsBessam Abdulrazak, Matthias Steinbauer, Ismail Khalil, Eric Pardede, Gabriele Anderst-Kotsis
PublisherAssociation for Computing Machinery
Pages99-104
Number of pages6
ISBN (Electronic)9781450348065
ISBN (Print)978-1-4503-4806-5
DOIs
Publication statusPublished - 28 Nov 2016
Event14th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2016 - Singapore, Singapore
Duration: 28 Nov 201630 Nov 2016

Publication series

NameACM International Conference Proceeding Series

Conference

Conference14th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2016
Country/TerritorySingapore
CitySingapore
Period28.11.201630.11.2016

Keywords

  • Accelerometer
  • Arm-worn devices
  • Gesture recognition
  • Hand gestures
  • Sensor placement

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