Essential tremor measurement and analysis

A computer sensor network is developed to monitor hand position of those with essential tremor, a nervous system disorder that causes uncontrollable shaking of the hands and upper body [1]. The sensor network collects three-dimensional positional data using two ZX Distance and Gesture Sensors, an Arduino Uno board, and a Raspberry Pi. The ZX Distance and Gesture Sensors, which use two infrared (IR) light-emitting diodes (LEDs) and a receiver to collect positional data, are connected to the Arduino. From there, the data are transmitted serially to the Raspberry Pi via an I2C multiplexer. Data from a series of carefully selected hand movements performed by a subject without essential tremor are collected and analyzed using Python to assess network accuracy. Graphs are produced to represent different data features. Theoretical plots are also generated for comparison to experimental results. Average deviation from a theoretical path of motion is calculated for each task performed and found to be no higher than 0.24 inches (0.61 cm). These values quantify the shakiness of the “normal” hand relative to theoretical paths of motion. With data collected from real tremor patients, this computer sensor network could improve the way essential tremor is monitored and classified for the millions of patients who struggle to find treatment.