Tham khảo tài liệu 'biomedical engineering 2012 part 9', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 312 Biomedical Engineering missing ranges we predict missing data based on data continuity. A boundary constraint recovery approach was proposed and tested since the corrupted areas are found mid-stream and can be recovered by using boundary information preceding and subsequent data of the corrupted region. After these elimination and recovery processes are applied to the raw data wavelet data decomposition techniques are executed to extract steady physiological characteristics over periods of hours and days. Since the improvement heavily depends on data characteristics we examined the optimal strategy for each data using different scaling factors and mother wavelet. In order to apply wavelet analysis for detecting long-term pattern changes from the readings as explained in the previous section the followings concerns are addressed. 1 Recovery of missing or corrupted data caused by interruptions in the data gathering process to create necessary data points. 2 Appropriate handling of data noise acquired during the measuring process to provide statistically valid data representative. 3 Selection of a proper wavelet methodology depending on data characteristics since the objective is not to find a specific waveform but to recognize a circadian profile of state change. Data Recovery As mentioned in the former section if fluctuating data are detected and determined to be corrupt those portions must be eliminated and recreated in order to perform a wavelet analysis on the entire range of data. Since wavelet decomposition generally requires a constant interval missing data must be recreated for the sampling purpose. The border extension method was developed for this reason to avoid border distortion of finite length of data. However this is not directly applicable to missing data found mid-stream which we handle here. If data is corrupted due to sensor detachment or other anomaly these points must be eliminated and recreated with the remaining data to ensure the .
