Grove - Thumb Joystick
Sold outGrove - Thumb Joystick is a Grove compatible module which is very similar to the ‘analog’ joystick on PlayStation 2 controllers.
Overview
The X and Y axes are two ~10k potentiometers which control 2D movement by generating analog signals. The joystick also has a push button that could be used for special applications. When the module is in working mode, it will output two analog values, representing two directions. Compared to a normal joystick, its output values are restricted to a smaller range (i.e. 200~800), only when being pressed that the X value will be set to 1023 and the MCU can detect the action of pressing.
Features:
- Grove Interface
- 5V/3.3V Compatible
- Analog Output
Tech specs
|
Item |
Min |
Typical |
Max |
Unit |
|
Working Voltage |
4.75 |
5.0 |
5.25 |
V |
|
Output Analog Value （X coordinate） |
206 |
516 |
798 |
\ |
|
Output Analog Value （Y coordinate） |
203 |
507 |
797 |
\ |
Get Inspired
For children who experience certain developmental delays, specific types of physical therapies are often employed to assist them in improving their balance and motor skills/coordination. Ivan Hernandez, Juan Diego Zambrano, and Abdelrahman Farag were looking for a way to quantify the progress patients make while simultaneously presenting a gamified approach, so they developed a standalone node for equilibrium evaluation that could do both. On the hardware side of things, an Arduino Nano BLE 33 Sense Rev2 is responsible for handling all of the incoming motion data from its onboard BMI270 six-axis IMU and BMM150 three-axis magnetometer. New readings are constantly taken, filtered, and fused together before being sent to an external device over Bluetooth Low Energy. The board was also connected to a buzzer and buttons for user inputs, as well as an RGB LED to get a real-time status. The patient begins the session by first putting on the wearable and connecting to the accompanying therapist application. Next, a game starts in which the user must move their torso to guide an image of a shark over the image of a stationary fish within a time period — ultimately trying to get the highest score possible. Throughout all of this, a vision system synchronizes its readings with the IMU sensor readings for an ultra-detailed look at how the patient responds to the game over time. To read more about the project, you can visit the team's write-up on Hackaday.io.
