An ambulatory system to quantify bradykinesia and tremor in Parkinson's disease

Abstract

Two groups of 10 Parkinson's disease (PD) patients and 10 age-matched Normal subjects performing normal life activities were recorded using a portable recorder and 3D gyroscopes. PD patients had sub-thalamic stimulation implantation for 2043 months. The PD patients performed the test twice: with and without stimulation. Bradykinesia and Tremor of hands in PD patients was quantified and strong correlation between this objective method and UPDRS clinical score was found.

Adaptive Speed and Sensitivity Configuration with Parallel Health Status Validation Via a Gesture-Based Controller - Robotic Arm Interface

“…[5]. As the number of Parkinson diseased people during the last years increased, notable research has been conducted dealing with the measurement of tremor, which presents one of the three fundamental symptoms of Parkinson [6][7][8][9][10][11][12]. Furthermore, in [6,9] the identification of bradykinesia is also proposed.…”

“…At the lower plot the mobility value is also presented, which is calculated from the route mean square values. This value is necessary to identify a bradykinesia by the average over a long time, as proposed in [9], and can also be used for the adaptive speed adaptation of the robotic arm. The Leap Motion controller is analysing the user palm tremor, and the movement speed in the x, y, and z axes, as well as the corresponding roll, pitch, and yaw rotation angles, resulting in total 6 different signals data streams.…”

“…Figure 4 depicts the general approach to identify the tremor using the Leap Motion controller. In order to have comparable results with existing studies [6,9,11], the measured raw data values (position/orientation) are converted into acceleration using a double differentiation. Before using the Fourier transformation to receive the frequency spectrum of the measured acceleration, a Gaussian Window Function with = 0.4 is used to improve the visual result of the Fourier transform, which is displayed on the GUI.…”

“…(8) where represents the FIR filter array, and the filtered velocity of the hand. As the values after a Fourier transformation are complex (the complex value of a number is stored in an even cell index and the real value in an uneven), the multiplication must be performed using equation (9). (9) In order to identify the mobility of the hand the rout mean square algorithm (equation (10)) has been used, as suggested in [9].…”

“…As the values after a Fourier transformation are complex (the complex value of a number is stored in an even cell index and the real value in an uneven), the multiplication must be performed using equation (9). (9) In order to identify the mobility of the hand the rout mean square algorithm (equation (10)) has been used, as suggested in [9]. (10) Finally this value represents the mobility of the user palm in cm/s and thereby is used by the authors to adaptively configure the operating speed of the Jaco Robotic arm.…”