gms | German Medical Science

Objective: In surgical treatment (DBS) of movement disorders, such as tremor, the exact electrode placement and the strength of the stimulating current are critical parameters for the outcome of the treatment. In the present study a custom-programmed Android smartphone was used to measure tremor intraoperatively and to document stimulation amplitude effects.

Method: We examined 7 patients with Parkinson’s disease and essential tremor during surgery under analgosedation. The patients performed simple exercises for the assessment of movement disorders. A Sony Xperia X10 mini smartphone with a 3-axes accelerometer and Wi-Fi connectivity was used as the sensor. Attached to the patient's wrist, it measures the acceleration about 40 times per second with the accuracy of approximately 0.05 m/s² and transmits the data to a laptop. There the spectral analysis and data storage was performed. We examined the tremor spectrum power as a function of the stimulation current. To compensate for the different baseline tremor amplitudes between the patients, we normalized each patient's spectrum power to baseline. Since tremor can only asymptotically approach zero, but never fall below it, we tested several non-linear models, in addition to the simple, linear one: exponential, inverse linear (hyperbolic), and inverse square.

Results: Out of 13 patients with idiopathic Parkinson’s disease or essential tremor we examined seven patients (5 IPS, 2 ET) with 30 measurements, leading to 1 and 28 degrees of freedom for the F-test. We measured resting tremor for the IPS patients and holding tremor for the ET patients. The baseline spectrum power was 1.82 ± 4.87 m²/s⁶. The stimulation current was always in the range 0–4 mA and resulted in tremor reduction by 96% ± 3.7% at 2.75 ± 1.04 mA. Partial response (30% tremor reduction) was achieved at 1.25 ± 0.46 mA and sufficient response (90% reduction) at 1.87 ± 1.07 mA. Already the simple linear model (P/Pmax=–0.264•I+0.77) provided the best fit for the data (F=44.67 and p=3•10^-7). The exponential model was slightly worse, describing the data with F=42.04, p=5•10^-7. The inverse square and inverse linear model were of a lower quality, having F=17.41 and F=8.53 with p=0.00026 and p=0.0068, respectively.

Conclusions: We documented objective intraoperative tremor suppression by using spectral analysis. The described smartphone-centered system can provide informative feedback for adjusting the stimulation current.