Week 10: November 14
_
Current Status of Project:
We are building the software for our signals analysis in MatLab and are simultaneously designing the Android interface for our program. Having completed a significant portion of our analysis segment, we will be using a recently acquired MatLab-to-Java converter to translate our code into Android-based Java. We have identified the diseases that will be analyzed as well as devised preliminary schemes as to how to detect these various types of diseases. These schemes will be tested in the coming days.
Work Completed in the Last Week:
As previously mentioned, we have written the preliminary code for our project in MatLab and in Java. In the process, we have come to a consensus on analyzing our signal in 10 second intervals over an extended overall signal duration. Once these diagnoses are obtained, the program will compute a weighted average of which diagnosis is the most prevalent for the signal duration and will output that diagnosis to the patient. Also, the smaller time interval will make the signal more discernible and in the process, eliminate excess noise. This process will essentially work as a confidence interval and will give a diagnosis with a certain degree of certainty. Our group also determined that we would be allowing the user to change the sampling rate to suit their convenience – since the data will be sent to their hard drives, they can choose to sample more or less frequently based on how much space is available on their hard drives.
Work Planned for next week:
Anything needed from mentor/client or TA or instructor to continue work:
We are building the software for our signals analysis in MatLab and are simultaneously designing the Android interface for our program. Having completed a significant portion of our analysis segment, we will be using a recently acquired MatLab-to-Java converter to translate our code into Android-based Java. We have identified the diseases that will be analyzed as well as devised preliminary schemes as to how to detect these various types of diseases. These schemes will be tested in the coming days.
Work Completed in the Last Week:
As previously mentioned, we have written the preliminary code for our project in MatLab and in Java. In the process, we have come to a consensus on analyzing our signal in 10 second intervals over an extended overall signal duration. Once these diagnoses are obtained, the program will compute a weighted average of which diagnosis is the most prevalent for the signal duration and will output that diagnosis to the patient. Also, the smaller time interval will make the signal more discernible and in the process, eliminate excess noise. This process will essentially work as a confidence interval and will give a diagnosis with a certain degree of certainty. Our group also determined that we would be allowing the user to change the sampling rate to suit their convenience – since the data will be sent to their hard drives, they can choose to sample more or less frequently based on how much space is available on their hard drives.
Work Planned for next week:
- Finish writing MatLab and Java
code for the two parallel projects
- Merge the two codes using our
newly acquired MatLab-to-Java converter
- Test the MatLab code to across
various cardiac diseases
- Begin writing the final paper and
preparing the final presentation
Anything needed from mentor/client or TA or instructor to continue work:
- None at this time