Dystonia is a movement disorder in which a person's muscles contract uncontrollably. The contraction causes the affected body part to twist involuntarily, resulting in repetitive movements or abnormal postures.
Physical therapy is a common method of treating dystonia, but it requires a small number of specialists and is expensive. At the same time, these patients are often unable to communicate verbally, so understanding their nonverbal intentions and helping them express nonverbal intentions are essential.

Children with dystonia

In this project, we conducted two experiments on children (around 11 years old) with dystonia:

• Orthoses Experiment: if children with orthoses can express their nonverbal intentions better.
• QTrobot Experiment: if children are more willing to interact with a humanoid robot than normal electronic equipment, for example, a screen.
  

The experiment will go like this table:

We designed a set of “number games” for children to play with a robot called QTrobot and wearing orthoses to test the two metrics during the game and collect all kinds of data (raw video, audio etc.) for later analysis.

During the game, QTrobot will do different speaking, listening, guessing and other kinds of gestures and a lot of emotions to interact with children, and we designed encouraging and rewarding feedback for QTrobot during the game to make children more comfortable. In addition, we also did the work of using the camera to identify the thumb orientation, which is used in the game.

• folder thumb: thumb detection, a catkin package
• QTNumberGame.py: QTrobot number game code
• pictures: some pictures in the projects
• videos: some demos of the projects
• rosbag2video.py: rosbag to video
• all demos:
  https://cloud.tsinghua.edu.cn/f/4632cf929c404e64b7f5/
  https://cloud.tsinghua.edu.cn/f/14dc333b78b84bff9940/
  https://cloud.tsinghua.edu.cn/f/24b9d468d50e4f2db711/
  https://cloud.tsinghua.edu.cn/f/fc48acfbe1714f45a605/
  https://cloud.tsinghua.edu.cn/f/a3fd22773387484cb18f/
  

• install some dependies

sudo apt-get install build-essential freeglut3 freeglut3-dev

• install astra camera ros packages (for using depth images)

sudo apt-get install ros-kinetic-astra-camera ros-kinetic-astra-launch

• install libuvc (for rgb images)

cd ~
git clone https://github.com/ktossell/libuvc
cd libuvc
mkdir build
cd build
cmake ..
make && sudo make install

• install libvuc-ros (for rgb images)

cd ~/catkin_ws/src
git clone https://github.com/ktossell/libuvc_ros
cd ..
catkin_make 

• Install opencv-3.4.6 and follow the instruction
• Download folder "thumb" to your catkin workspace
• Change opencv location in CMakeLists.txt, remember it's the build folder. Example:

set(OpenCV_DIR /home/sangerlab/Downloads/opencv-3.4.6/my_build)

• cd to your catkin workspace

catkin_make
soure devel/setup.bash

• Now you can run the camera. If you want to connect with QTrobot, you need to do this first:
• connect to QT104 wifi
• export ROS_MASTER_URI=http://192.168.100.1:11311 (or write it into your ~/.bashrc file and source it)
• export ROS_IP=YOUR IP ADDRESS (example:export ROS_IP=10.42.0.250) (or write it into your ~/.bashrc file and source it)

roscore (if you are connecting with QTrobot, you don't need to do this)
rosrun libuvc_camera camera_node
roslaunch astra_launch astra.launch 
rosrun thumb get_image
rosrun thumb get_state.py

• Tips:
  • In case that rosrun libuvc_camera camera_node get the error message like this:
    
    you should do like this:
    • first replug the camera (very important!)
    • then do sudo chmod a+rw ...(the dev name)
  • you must run as the same order as this tutorial
    

• QTrobot has two computers. The head computer runs ROS CORE and ROS MASTER, and ROS_MASTER_URI is http://192.168.100.1:11311
• If you want to connect body computer to another computer, you need to let the two computer both connected to QT104 wifi
• To run this project, you should first run the camera, and then run QTNumberGame.py
• I have record some gestures in the head computer's folder:numbergame/talking2 compared to folder QT.

• For video data, you just need run
  rosbag record TOPIC_NAME
  For example:
  rosbag record /image_raw
  Then run rosbag2video.py to transform bagfile to video:
  rosbag2video.py BAGFILE_NAME
  
• For other kind of topics, you just need to use rosbag record TOPIC_NAME