Transcript KINECT REHABILITATION
KINECT REHABILITATION
Stroke Therapy Research Kathryn LaBelle
RESEARCH TOPIC
Can the Kinect’s joint-tracking capability be used in clinical and in-home stroke rehabilitation tools?
OUTLINE
• • • • • • • Background – – Stroke Therapy Kinect Potential of Kinect in Rehabilitation Research Questions Software Data Gathering Data Analysis Conclusions
STROKE THERAPY
• • Stroke survivors can experience: – restricted movement – loss of sense of balance – decreased strength Regained through physical therapy – balance exercises – range of motion activities – coordination practice
MICROSOFT KINECT
• • • Developed for the Xbox 360 gaming console Tracks your movements: you are the controller Sensors 1. Depth Camera and Sensors 2. RGB Camera 3. Microphone array 4. Motorized base
DEPTH IMAGING
• • • • Infra-red projector shines grid of light on the scene, encoded with data.
Light bounces off objects in the scene.
Kinect light sensors receive reflected light.
By analyzing time of flight and distoritions in the encoded data, the Kinect makes a depth map of the scene.
JOINT TRACKING ALGORITHM
• • • Input: depth map Machine learning algorithm – Collected recordings of people using the Kinect – Joint positions marked by hand – Algorithm was fed this “training” data and learned how to correctly identify joints from a depth image Output: x, y, z joint positions
JOINT TRACKING AND STROKE REHABILITATION
• • Clinical applications: – assess patients’ performance – track patients’ progress – pinpoint areas for improvement At-home exercise aids: – provides constructive feedback to patients – give encourgement and motivation – generate summary reports for doctors
RESEARCH QUESTIONS
• • • • • What SDKs and drivers are available for use with a PC?
What type of information can be obtained? What is the quality of the joint data obtained from the Kinect? – Sampling rates – Consistency How resilient is the Kinect’s joint data and performance to variation in testing conditions?
What functionality could be provided in a stroke therapy application that uses the Kinect?
SDK COMPARISON
Raw depth and image data Joint position tracking Save raw data stream to disk Joint tracking without calibration Easy installation Number of joints available Quality of documentation
OpenNI
Yes Yes Yes No No 15 Adequate
Microsoft
Yes Yes No Yes Yes 20 Excellent
SOFTWARE DEVELOPED
• • • • • Display depth video and skeleton Joint positions and instantaneous frames per second written to file Balance board integration Record depth stream to file Obtain joint positions from recording
DATA GATHERING
DATA ANALYSIS
• • • Sampling rates of joint position data Identifying phases of movement from joint positions Consistency and stability of joint positions
SAMPLING RATE
Average Frame Rate (fps) Std Deviation (between trials) Minimum (fps) Maximum (fps)
OpenNI Microsoft
25.0
19.6
5.8
9.8
30.0
2.3
14.1
23.7
IDENTIFYING PHASES OF MOVEMENT
DATA STABILITY
Head Hip
Standard Deviation of Joint Positions while Subject is Motionless Joint
Knee
OpenNI (cm)
0.34
0.42
0.70
Microsoft (cm)
1.8
1.2
1.5
DATA STABILITY: Assisted Tests
• • Clinical therapy often involves an assistant supporting a patient while he performs exercises Test procedure: – subject begins by sitting alone – assistant joins, putting hands on subject’s shoulders – subject stands up
DATA STABILITY: Assisted Tests
DATA STABILITY: Assisted Tests
DATA STABILITY: Assisted Tests
CONCLUSIONS
• • • • • • OpenNI Framework and Microsoft SDK for Windows are best tools to use Can provide significant functionality in a joint-tracking application – track and record joint positions in three dimensions – display image of tracked joints in real time – integrate Kinect with the Wii balance board Sampling rate exceeds acceptable level Phases of movement are easily identifiable from graphs of joint positions Joint position stability is more than adequate with one subject in view Skeleton merging could pose a problem for clinical use of Kinect
FUTURE WORK
• • • Deeper investigation into assisted exercises – Different types of exercises – Position the assistant differently – Determine conditions causing skeleton merging Further development of software Investigate applications in other fields of physical therapy
QUESTIONS?