Week 8

Lecture

In this weeks Lecture i learned about Telemedicine, Telecare and Patient Monitoring System.

Telemedicine

Telemedicine is the use of ICT to provide and support healthcare when distance separates the participants.The objective of telemedicine to provide specialized health care consultation to patients in remote locations and to facilitate video-conferencing among health care experts for better treatment& care.

Telecare

Telecare is aservice that enables people, especially older and more vulnerable individuals, to live independently in their own home. Telecare enables an older person to remain living at home, helps ease the challenges of daily living and improve the sense of security and self confidence

Patient Monitoring System

Patient Monitoring is repeated or continuous observations or measurements of the patient, his or her physiological function, and the function of life support equipment, for the purpose of guiding management decisions, including when to make therapeutic interventions, and assessment of those interventions

In this lecture i have learned alot about the wide range of care that is available and how ICT is improving it. I think the future of ICT in healthcare will grow and grow and so this will improve the healthcare for not just the elderly but everyone.

Tutorial

This week there was no tutorial and we were asked to read about Data Mining Applications in Healthcare which we will discuss in week 9 and 10. I looked at this book and found it very intreseting and will help my Health Informatics studies and knowledge of it.

Practical

In this weeks practical we learned about datasets and repositories and used WEKA toll to help us. A few open repositories provide datasets for academics/researchers to use and researchers deposit datasets for others to use. We were given a few tasks to complete using WEKA and found this enjoying to do and intresting finding out the facts from the data.

Number of instances = 336

Number of attributes = 8

Data Set Characteristics = Multivariate

Attribute Characteristics = Real

Associated Tasks = Classification

Missing Values = No

Task 3

Do the values correspond to those you noted in task 2

–Number of attributes / instances

yes 

Do the values correspond to those you noted in task 2

–Number of attributes / instances

yes

 we used the following dataset.  http://archive.ics.uci.edu/ml/datasets/Localization+Data+for+Person+Activity

  Creating and adding arf fheader information

Does WEKA read your file? Any problems? If yes return to your data file and see if you can spot any syntax errors.

Yes i got the following error as i did not the correct information inserted.

When i corrected my errors i ran the program and got the following information.

This graph show the data found and how many times each event occured. An example for using this would be using a pressure pad at an elderly persons home to check how many times they leave the house and all this data is then put in a graph like this to make viewing information easier. I enjoyed this practical alot and learned so much from it that will help me in future assignments.

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