## 1 Introduction  
Human-System Interaction (HSI) is currently actively pursued as a separate research field dedicated to the development of new technologies facilitating human communication with systems [1]. Depending on the application, such interaction systems are also referred to as Human-Computer Interfaces (HCI) or more generally human-machine interfaces. The design and construction of such systems requires an interdisciplinary research approach and involves knowledge of sensory perception mechanisms in humans, cognitive processes, and information processing, as well as basics of ergonomics. A well-designed user interface often determines the usefulness of an entire system [2]. Designing interfaces accessible for persons with sensory and motor disabilities is a particularly challenging research issue [3, 4]. It is necessary to develop innovative solutions that enable handicapped users to communicate with such devices or systems. The interfaces use alternative, often multimodal communication methods that compensate for the diminished or lost sensorial or physical functions [5]. Individuals with hearing loss use sign language (one of the so-called visual-spatial languages) and are aided by sign language computer applications. For people with physical disabilities, special input-output devices utilizing inertial sensors and innovative interfaces are built so that \"contactless\" communication with a computer via, among others, Brain-Computer Interfaces (BCI) [6] and video interfaces, which are capable of tracking eye movements [7] or detecting intentional blinks [8], have been developed. The work reported in [9] shows that people with cerebral palsy can communicate with the use of personalized gesture datasets while aided by an intelligent user interface. The visually impaired, on the other hand, interact with computers using speech synthesizers and the so-called Braille displays that allow them to type in and display the Braille alphabet. A more complex problem for a blind person is handling devices while in motion. The basic mobility aid that the blind use is a white cane, which engages one hand and hence, complicates the operation of an additional device, e.g., a navigation tool during a walk. The control of computer applications is traditionally performed using a keyboard and/or a computer mouse or a touch screen. However, solutions that enable people with serious physical disabilities to work with computers are increasingly more common. In [10], an interface based on the recognition of head movements and simultaneous lip movements designed for users with limb disability was reported. It is, however, not only computer applications that can be controlled in a non-contact manner. It was shown that the movement of an electric wheelchair of a disabled person can be controlled by means of head movements [11; 12; 13] or eye gaze [14] and even EEG signals [15]. Recent advances in electromechanical MEMS (Micro Electro Mechanical Systems) technologies have made it possible to develop miniature and cheap inertial sensors, and consequently use them in human-computer interfaces [16]. In [17], in order to identify eight different types of physical activity, a three-axis accelerometer placed on the wrist of the dominant hand was used. In [18], five acceleration sensors were used to recognize the movement of hands and to distinguish gait from immobility. The sensors were placed on the chest and on all the limbs. Similarly to our work, 3-axis compass, 3-axis accelerometer and 3-axis gyroscope were mounted on the user's head and used to identify six different head gestures [19]. In [20], a system that can be utilized to monitor the body movements of people with neurodegenerative diseases was reported. In this system, signals recorded from three sensors were analyzed, one of them was mounted on the head and the other two on the shins. The fusion of signals acquired from an accelerometer and surface EMG electrodes was used in [21] to assess [PERSON]'s disease-related symptoms.