# Controlling Industrial Robotic Arms Using Gyroscopic and Gesture Inputs from a Smartwatch
## 5 Experimental Configuration  
Experiments were conducted in a laboratory setting with a single operator donning the smartwatch. Predefined gestures were assessed to determine accuracy, latency, and responsiveness. The ThingWorx platform recorded real-time motion data for analysis. The control system was assessed based on command repeatability, perceived usability, and the correlation between wristwatch movements and robotic actions. The proposed method was implemented using a Xiaomi Smartwatch 2 Pro and the WowMouse application created by Doublepoint. This program was chosen for its exceptional versatility and cross-platform compatibility, facilitating smooth communication with various wristwatch devices operating on both Wear OS (Android-based) and watchOS (iOS-based) systems. The WowMouse application facilitated real-time communication between the smartwatch and the robotic platform. The TouchSDK Python library enabled the gathering of sensor data from the smartwatch's integrated inertial sensors. The data streams, comprising accelerometer, gyroscope, and optionally magnetometer readings, were subsequently processed for gesture detection and motion tracking, establishing the foundation for robot control commands. Figure 4 illustrates the practical interaction between the smartwatch interface and the industrial robotic arm during control tasks. In Figure 4a, the operator's hand is in a  
neutral pose, preparing to execute a control gesture. In Figure 4b, the WowMouse app on the Xiaomi Smartwatch 2 Pro detects and highlights an active gesture (e.g., pinch or tap), which is subsequently interpreted by the processing script via TouchSDK and transmitted to the robot for execution. This visual feedback confirms successful gesture recognition and enables real-time user awareness during control tasks. Figure 5 depicts the three principal hand movement directions aligned with the Cartesian coordinate axes--X, Y, and Z--as recorded by the inertial sensors (IMUs) within the smartwatch. * X-Axis Movement: Lateral (left-right) displacement of the hand, usually identified using accelerometer data on the horizontal plane. * Y-Axis Movement: Vertical displacement, typically linked to the elevation or descent of the hand. * Z-Axis Movement: Rotational movement (roll), demonstrated by a twisting motion of the forearm that alters the hand's orientation around its central axis. Figure 4: Smartwatch-based gesture recognition for robotic control. (**a**) Neutral hand pose before initiating command. (**b**) Recognized gesture (rotation) triggers corresponding robot motion. The smartwatch interface confirms detection via on-screen icon. Figure 5: Representative gesture movements along the three IMU axes as recognized by the smartwatch: (**left**) X-axis—horizontal swiping, (**bottom**) Y-axis—vertical lifting/lowering, and (**right**) Z-axis—wrist rotation (clockwise/counterclockwise). These directional gestures correspond to robot motion mapping. These motion directions are crucial for interpreting user intent in a smartwatch-controlled robotic system. The inertial measurement unit (IMU) embedded within the smartwatch captures acceleration and angular velocity in real time. The data are subjected to filtering and fusion algorithms to track movement along the three axes. Understanding and distinguishing these directed movements allows the system to associate each movement with certain robotic commands, such as moving the robotic arm along a specified axis or rotating its joints. Accurate calibration guarantees theuniform and precise identification of these movements among users and under varying operational conditions. This visualization from Figure 6 confirms the alignment between the interpreted gesture and its spatial projection. It supports the debugging of the sensor-to-robot mapping and allows trajectory comparison in gesture recognition training tasks. During the initial phase of testing, the focus was placed on acquiring and interpreting raw sensor data from the smartwatch's embedded inertial measurement unit (IMU).