Periodic limb movement disorder (PLMD) is a sleep disorder characterized by deteriorated sleep due to involuntary periodic limb movements (PLMs) during sleep. In the field of sleep medicine, PLMs are defined as involuntary movements that primarily occur in the lower extremities, typically involving extension of the big toe, which may be associated with fanning of the toes similar to the Babinski reflex, or with partial dorsiflexion of the ankle. Currently, surface electromyography (sEMG) in polysomnography (PSG) is the key test for diagnosing PLMD. However, sEMG only measures the bilateral tibialis anterior (TA). From the biomechanical perspective, this may overlook PLMs that mainly involve the big toe. Before conducting a prospective study of PLMs in individuals with PLMD using the two auxiliary channels of a commercial PSG device, we identified the abductor hallucis (AH) as an additional candidate muscle for PLM detection based on the results of a three-step investigation involving visual observation of PLM, biomechanical movements, and anatomical location. The average recall values calculated from voluntary simulated PLM-like movements measured in 10 healthy female individuals showed that the AH performed better than the TA in discriminating muscle activation and joint movements mainly involving the big toe; big toe extension (TA: 0.144 ± 0.300 vs. AH: 0.600 ± 0.338) and big toe abduction (TA: 0.050 ± 0.147 vs. AH: 0.878 ± 0.202), but the TA performed better in ankle dorsiflexion (TA: 0.989 ± 0.060 vs. AH: 0.400 ± 0.389). In addition, the average precision values were consistently high (mostly > 0.97), which indicated that the detected events corresponded reliably with voluntary simulated PLM-like movements, regardless of the muscle: big toe extension (TA: 1.000 ± 0.000 vs. AH: 0.975 ± 0.089), big toe abduction (TA: 1.000 ± 0.00 vs. AH: 1.000 ± 0.000), and ankle dorsiflexion (TA: 1.000 ± 0.000 vs. AH: 0.972 ± 0.079). Since recall for the TA and AH showed complementary strengths, combining their sEMGs may improve the accuracy of PLM detection.