In this work, traditional, clinical methods of evaluating autonomic neural control systems are compared with the newer method based on the signal processing applied on Heart Rate Variability signal. The information available from the time-frequency representation of HRV signals is useful in classifying the subject population into four classes namely normal, sympathetic loss, parasympathetic loss and combined losses. The results suggest that the presence of autonomic neuropathy can be clearly detected by short time HRV signal analysis possible in the clinical environment.