Introduction: DBS is a routinely performed surgical procedure for treatment of movement disorders like Essential Tremor (ET). However, the target selection in DBS is not fully optimized. Incomplete knowledge of the mechanisms of action being one of the reasons, we believe, suboptimal usage of information during surgery is another. We have previously demonstrated the use acceleration sensors to quantify changes in patient tremor during deep brain stimulation surgery. In this paper, we would like to analyze the correlation of the acceleration data results with the different deep brain structures. We present in this paper the result from 5 ET patients implanted in the VIM. Methods: A 3 axis acceleration sensor was used to record and quantify changes in the patient's tremor while test stimulations were performed during DBS surgery using the method described previously. During surgery, for every test stimulation position, the maximum change in patient's tremor and the stimulation amplitude at which it was observed subjectively were noted. As the acceleration data was continuously recorded, it was possible, from offline analysis, to find stimulation amplitudes for changes in statistical features equal to those found subjectively. Additionally, the stimulation amplitudes at which acceleration data suggested maximum change in tremor were also identified for every test stimulation position. For the anatomical analysis, the surgical team carefully identified the anatomical location of the electrode and attributed one thalamic sub-structure to it. Based on this information, the change in tremor and its corresponding stimulation amplitude were grouped into respective sub-structures. For the identification of most effective anatomical sub-structures, we checked for higher reduction in tremor at lower amplitude, both for subjective evaluations and acceleration data analysis. This method was applied to acceleration data collected from 5 Essential tremor patients under a clinical study in University Hospital in Clermont-Ferrand France. A total of 107 test stimulations were analyzed. The different sub-structures of the thalamus have been named according to the previously published nomenclature. Results: The 107 different test stimulation positions were found to be distributed in different parts of the thalamus: Intermedio-Lateral (InL, n=20), Ventro-Oral (VO, n=16), VIM (n=37), Ventro-Caudal-Lateral (VCL, n=2), Central-Medial (CM, n=3), Ventro-Caudal-Medial (VCM, n=23) and the PreLemniscal Radiations (PLR n=6). As the number of test stimulations in the VCL, CM and PLR is low, the significance of the results is very low.For the other structures, the effective stimulation amplitudes for the same clinical effect were lower for acceleration data than the subjective ones (p<0.01, alpha=0.05). On the basis of subjective evaluation data, we found that for same average effective stimulation amplitude (1.8 mA), the average reduction in tremor was higher for VCM (74%) than for VIM (55%). The results from the acceleration data were similar: The stimulation amplitude required for maximum change (>75%) was on average lower in the VO (1.8 mA) and in VCM (1.9 mA) as compared to the VIM (2.5 mA) and in InL (2.5 mA). Conclusion: The use of sensitive acceleration measurements during the surgery introduces a new approach to analyze the effectiveness of stimulation in different target structures. Our results suggest that the VCM is a better target than the VIM. This information should be considered during the planning of the exploration paths to have more contacts in the effective thalamic area. However, the current analysis does not take into considerations stimulation induced side effects. Those influence the final implant position significantly and can alter our conclusion. Also, attributing one stimulation position to just one structure considering it as a point is suboptimal. A better approach would be to simulate the stimulated volume by using electric field simulations. Along with additional analysis of the results with reference to the known mechanisms of actions of DBS they may result in increasing our understanding of DBS efficiency.