One of the most frequently-used body regions in daily activities is the upper limbs, and many of the work-related musculoskeletal disorders occur in this area, mainly the hands. We highlight the importance of studying hand movements executed at work, and how they affect workers’ health and productivity. Data were collected from a hand-motion capture system conformed by six inertial measurement units and six resistive force sensors from hand and fingers movements. Two common hand movements were analyzed using wrist flexion-extension with a small (−15° to 15°) and medium (<−15° and >15°) range of motion and flexion-extension movement with the hand pronated-supinated. Data were classified by traditional methods. A more complex movement involving a 3-finger spherical grip was also recorded. It was found that the lectures from the six inertial sensors and the six force resistive sensors showed a pattern that facilitates the recognition of basic and more complex movements (flexion-extension and spheric handgrip) through visual analysis of the plotted data, even at different ranges of motion.