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 re- quire 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 po- sitions 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 wrist-
		  worn 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 signif- icant due to the substantial
		  variation across participants.<br>
<br><pre>@inproceedings{Kefer_16_ComparingPlacementTwo,
  author = {Kefer, Kathrin and Holzmann, Clemens and Findling, Rainhard Dieter},
  title = {Comparing the Placement of Two Arm-Worn Devices for
  		  Recognizing Dynamic Hand Gestures},
  booktitle = {Proc. {MoMM} 2016: 14th International Conference on
  		  Advances in Mobile Computing and Multimedia},
  year = {2016},
  pages = {99--104},
  address = {Singapore},
  month = nov,
  publisher = {ACM},
  doi = {10.1145/3007120.3007146},
  keywords = {Gesture recognition; Hand gestures; Accelerometer; Sensor
  		  placement; Smartwatch;Myo armband}
}
</pre>