The goal of previous efforts has been to create hand prostheses with natural movements. Researchers have used tools to identify patterns in muscle signals associated with different hand movements. While many studies have successfully classified types of hand movements, it's important to analyze speed and strength to ensure that the resulting movements are natural. In this study, 16 healthy subjects were evaluated for (two) different forces and (six) hand movements using surface electromyographic (sEMG) records. A mixed effects model was used to examine the relationship between force and forearm sEMG signals. The results showed high R2 values (median 0.9) and significant random effects, indicating that sEMG signals can explain variations in force signals during different hand movements by introducing the type of movement as part of the random effects of the model.