Evaluating the placement of arm-worn devices for recognizing variations of dynamic hand gestures

Abstract

Dynamic hand gestures have become increasingly popular as touch-free input modality for interactive systems. There exists a variety of arm-worn devices for the recognition of hand gestures, which di er not only in their capabilities, but also in their positioning on users' arms. These di erences in positioning might in uence how well gestures are recognized, leading to di erent gesture recognition accuracies. In this paper, we investi- gate the e ect of device placement on dynamic hand gesture recognition accuracy. We consider devices being strapped to the forearm on two positions: the wrist and below the elbow. These positions represent smart watches being worn on the wrist and devices with EMG sensors for the additional detection of static hand gestures (e.g spreading the ngers) being worn right below the elbow. Our hypothesis is that wrist-worn devices will have better recognition accuracy, caused by higher acceleration values of a bigger action radius of dynamic hand gestures. We conducted a comparative study using an LG G Watch and Thalmic Labs' Myo armband, for which we recorded a total of 12960 gesture samples of eight simple dynamic gestures in three di erent variants with eight participants. We evaluated a potential di erence in gesture recognition accuracies us- ing di erent feature sets and classi ers. Although recognition accuracies for wrist-worn devices seem higher, the di erence is not statistically signi cant due to substantial vari- ations in accuracy across participants. We thus cannot conclude that di erent positions of gesture recording devices on the lower arm have signi cant in uence on correctly recognizing arm gestures.