Cybernic treatment with a wearable cyborg Hybrid Assistive Limb for medical use (Medical HAL) improves ambulatory function in patients with progressive neuromuscular diseases. The progress of cybernic treatment is evaluated based on the change in the patient's walking distance and walking speed over a certain treatment period. However, evaluation methods to capture temporal changes in gait functions during each therapy are required for more effective evaluation in clinical practice. Because the patients' muscular activities are measured with each trial of cybernic treatment, bioelectrical signals (BES) of lower limb muscles measured by Medical HAL may aid in evaluating the wearers' gait functions. Thus, this study proposed a method to quantify the BES patterns of patients during cybernic treatment and compared them with the BES patterns of healthy personnel for evaluation, which confirmed the correlation between the BES pattern and the patients' gait abilities. First, we obtained a reference BES pattern from the BES of three healthy personnel during walking using Medical HAL. Second, we calculated the similarity between the reference BES pattern of the healthy personnel and the patient's BES pattern using derivative dynamic time warping (DDTW), which quantified the patients' BES patterns based on their shape. Third, we investigated the correlation between patients' DDTW of BES patterns during cybernic treatment and 2-minute walking distances. The correlation coefficient between the patients was -0.83 (p < 0.01) and that within patients was -0.38 (p < 0.05), indicating a significant BES pattern relationship between walking with Medical HAL and gait abilities. Conclusively, the similarity between the BES patterns of healthy personnel and patients calculated using DDTW might be applied to the evaluation of patients' gait functions. The ability to assess the gait function with data measured during cybernic treatment would provide understandings of the patient's functional changes over time.