## 1 Introduction  
Electromechanical data gloves are among the most commonly used systems for recording hand kinematics. These gloves are equipped with strain gauges, which are placed over the joints under study. The signal provided by each gauge, measured in mV, varies depending on the degree of flexion. Electromechanical data gloves are the best choice for recordings involving manipulation, as they do not present problems such as the occlusions that can occur in optical systems or data interferences caused by the proximity of ferromagnetic objects, unlike electromagnetic systems. Furthermore, their setup is significantly easier compared to other systems. Optical systems with markers require initial calibration for each session and marker location, and electromagnetic systems such as Polhemus Fastrak or Polhemus Viper require sensor location in specific hand segments. Data gloves only require an initial calibration process when acquired [1]. CyberGlove (CyberGlove Systems, San Jose, CA, USA) is one of the most used data gloves in biomechanics to record hand kinematics [2; 3; 4; 5; 6; 7]. It has the capability to record either 18 or 22 degrees of freedom (DoFs), depending on the glove model. Its main body is made of elastic fabric, with a thicker section on the back of the hand and a thinner section on the palm contributing to achieve a better fit. To prevent interfering in manipulation, all the wiring and strain gauges are positioned on the back of the hand, and each gauge's position is fixed with seams. This glove has a thin and well distributed wiring facilitated by the slim design of the strain gauge sensors. When analyzing human hand kinematics during activities involving product use, it is key to differentiate between reaching, manipulation, and release phases. However, in recordings using the CyberGlove, a visual analysis is required to distinguish these different phases. This visual analysis involves recording the time stamp of specific events using the data acquisition software. Time stamps allow the segmentation of recordings in several parts at convenience (e.g., in reach, grasp and release phases) or the identification of specific events (e.g., the performance of a specific grasp). Nevertheless, acquiring time stamps though visual analysis requires a person observing all the performed tasks, which also introduces an error associated with their reaction time. An alternative to this visual analysis could be automating the procedure by incorporating pressure sensors to all the products (which may be expensive and time-consuming to install) or using a glove that includes pressure sensors. There are various commercially available data gloves that allow hand posture recording in addition to CyberGlove, such as Rokoko (Rokoko, Kobenhavn, Denmark), Xsens Manus Prime II (Xsens Technologies, Enschede, The Netherlands), or MoCap Pro Gloves (Stretchsense, Auckland, New Zealand), among others. Nevertheless, as observed in recent review studies investigating available commercial data gloves [8] and robotic gloves for remote control [9], there are few commercial gloves that record hand posture and are also equipped with pressure sensors. This low availability of commercial kinematic data gloves with pressure sensors has boosted the development of custom gloves by research groups. Table 1 presents a summary of kinematic data gloves with pressure sensors, both commercially available and custom-made, detailing the number of kinematic DoFs, number of pressure sensors, and commercial availability.