# Reducing the Number of Sensors in the Data Glove for Recognition of Static Hand Gestures
## 1 Introduction  
In the last decade, one can observe a significant development of virtual reality (VR) technology which has resulted in the introduction of systems using this technology to the consumer market. Such systems usually consist of a head-mounted display (HMD), commonly called VR goggles, controllers, and a pair of transceivers. The HMD is a screen, placed at such a distance from the eye to create the impression of being in the displayed image. This impression is so strong that it has become known as the second reality--a virtual reality. However, a device that creates a near-reality phenomenon should also be expected to interact to further enhance the sense of real-world experience. Currently, the most used human interaction devices are joysticks called wands. They are a kind of combination of the human hand's natural way of interacting with the world around us with existing input devices such as joysticks or computer game pads. For most people, especially youngsters, the control with such a \"wand\" is widely accepted and in a way natural, because they have been accustomed to using such devices since their childhood [1]. Additionally, the technologies for intuitive interaction with computers have been developed for years, e.g., through computer games. Computer games often require the player to perform several actions at the same time, e.g., moving simultaneously in the game space, controlling the camera, and performing a certain action. Additionally, online games require all these actions to be performed under stress due to action of the competing players and time pressure. To identify the next stage in the development of human-computer interaction, one can follow the simplified path by which control of modern devices occurs. In order to perform the user's original intention, whether it be a movement in a computer game or the desire to write on the computer keyboard, the user's brain must first translate it into a series of hand movements and then enforce those movements. Thus, any interaction with a computer can be represented as a brain-hand-controller-computer chain [2]. There is already another solution to the problem of controlling a computer, which is the brain computer interface (BCI) [3]. However, it is currently an early stage technology, allowing for the simplest of actions, and is so expensive and non-ergonomic that it will not exist as a commercial solution for several years yet. It can therefore be concluded that the next significant step in the development of control technology will be to eliminate the need to use controller buttons. The greatest benefits of control with a controller that replicates the natural movements of our hand can be achieved when applied to objects with a range of motion similar to that of humans. In the era of growing importance of telecontrol and breakthroughs in robotics, it also becomes necessary to develop a device that would allow an intuitive control of robotic manipulators while maintaining the required precision of their operation. However, for this to be possible, it is necessary to recreate the motor-nervous system of the hand so that the operator can freely perform operations and experience their consequences. This is possible with the use of devices that can track the user's hand movements. A device that allows direct measurement of finger movements was developed and described by [PERSON] et al. [4] and was named data glove. The form of the glove makes the use of this device ergonomic and does not interfere with the tested movements. This allows for natural movement, which is very important when testing all kinds of gestures and sign language. This paper describes a study using a designed data glove. The research focuses on two main objectives:  
1. To test the effectiveness of the constructed glove in recognizing static hand gestures;
2. To investigate the possibility of reducing the number of sensors used in the recognition static hand gestures.