Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Fall-related injuries may have huge and enduring impact on older people, resulting in chronic pain, disabled mobility and reducing the quality of life. Fall injuries is becoming a worldwide problem among older people and as a result, the measurement of balance ability for older people is of great importance.
In this master thesis, a system used to measure balance ability will be introduced. The system allows participants to perform a series of balance tasks with the help of Wii balance board (WBB) which is a low-cost, commercial gamming instrument. Previous work has showed the possibility and reliability of using WBB to measure the balance ability for older people.
Mean sway velocity (MSV) is used to measure the tandem stance test. Five-Repetition Sit-to-Stand (STS) test is measured by STS time. Since the system has high requirements on the input validity, input validation is also a main part of this thesis. Matlab is used to check the output validity of the program.
For the tandem stance test, our results (mean = 7.87) are much larger than the results from previous work (mean = 4.27). The results indicate that experimental factors such as standing posture and testing time have great impact on the average MSV results for tandem stance test.
For the five-repetition Sit-to-Stand test, our young participant did 9.97 seconds on average which is close to previous work (8.2 for average young people without balance disorders)
The results from output validation test for tandem stance show that the correctness of the program is highly reliable.
We found standing postures and testing time is very sensitive to MSV. To conduct a tandem stance test, the hardware should also be considered to be one of the main factors that affects MSV. Testing results again indicate STS time is a good measurement for STS test. In our input validation test for tandem stance, we also found an effective and sensitive interval for the arguments which can be considered to be a good discriminator to distinguish between valid and invalid inputs.