**1. Introduction**

The Leap Motion Controller (LMC) is a small, portable, relatively low-cost device compared with other motion capture devices such as Doctor Kinetic**®**. It accurately detects all the hand and finger joints [1]. It is an interactive technology in Virtual Reality (VR) environments. LMC can be used in non-immersive mode, plugged into the computer via USB (desktop version), or attached to VR glasses (headset version) for immersive interaction. It has been currently being investigated as a technological resource to support upper limb motor rehabilitation interventions, as it allows capturing finer movements of the hands and fingers, which are essential for the rehabilitation of manual dysfunctions found in different conditions [2–6].

Several models of VR headsets are on the market, such as Gear VR, Rift glasses, and HTC Vive [2, 7–19]. Gear VR is a more cost-effective solution because it uses the screen of a Samsung smartphone as a viewing display [18]. The trend is that these technologies are available in people's homes, offering services in the most diverse areas of entertainment, education, and health.

Research with LMC points to its potential use by people with difficulties in fine and gross motor skills, explicitly concerning pincer grasp and power grip strength movements, extension and flexion of fists and fingers, forearm supination and

pronation. Due to this extensive repertoire of gestures that LMC can detect, it is possible to find several studies with groups of people with stroke, older people with manual motor dysfunctions caused by aging [13], parkinsonians [8], children with developmental psychomotor disabilities, including cerebral palsy [20], Down syndrome [21], and autism [6].

The LMC allows measuring the motor performance of these people, such as reaction time, bimanual coordination, and the sequence of movements performed with the hands and fingers. For this reason, this remote sensing technology has shown promise for the rehabilitation field as it does not require the patient to wear motion detection devices (e.g., gloves with force and feedback sensors). Therefore, it provides a new interaction between the user and the computer, allowing for more natural and touchfree interaction. Hand dexterity in patients with upper limb motor disorders can be assessed from programmed tasks with graphic objects added to the virtual world [14].

Research involving the LMC integrated with the Box and Block Test (BBT) has emerged recently. Physical and occupational therapists use this test to verify manual function to assess and quantify the unilateral gross manual dexterity in children and adults. The BBT is made up of a wooden box with colored cubes, whose objective is to transport the cubes from one compartment of the box to the other in 1 minute. In the end, the number of cubes transferred per minute is counted. In its VR version, the LMC is used as an interaction device to transport blocks from one compartment to the other of the Box.

This chapter presents the works investigated using the LMC sensor integrated into the BBT. We are developing a version of BBT in VR that can be used on Desktop computers, both with video monitors and with VR glasses (HTC Vive). Then, we present details of this virtual BBT version in this chapter.

In addition to this introductory section, we divided this article into five sections: Section 2 provides details on how the LMC device works; Section 3 briefly presents the main tools for assessing manual function; Section 4 presents the functioning of the Box and Blocks Test and its virtual version in Virtual Reality developed by the researchers of our Game Therapy and Virtual Reality Laboratory; Section 5 shows scientific studies (performed with the Virtual BBT) found in the literature; Section 6 presents the conclusions.

The method adopted for the theoretical review was the query in indexed databases seeking information about the advantages and disadvantages of using the LMC device in immersive and non-immersive virtual reality situations. We sought to identify the errors and inaccuracies most commonly in the use of this device associated with the box and blocks test and the results found regarding the performance of the manual function.
