A Study of User Interface with Wearable Devices Based on Computer Vision

Smart wearable devices are widely used in the field of healthcare. This article presents three approaches to human–computer interaction (HCI) via computer vision and hand gestures. They are timeline-user interface, virtual keyboard user interface, and handwritten digit user interface, respectively. These user interfaces are achieved by including the image process and machine learning, such as Convolutional Neuron Networks and AdaBoost. To evaluate the approaches, a prototype of the android device with a built-in color camera was employed. The result of the handwritten digit model was significant for high accuracy of 92.9%. In our view, the results emphasize the validity of our models.