Discuss about the Performance Evaluation of Empirical Decomposition.
It has been seen that Epilepsy is becoming a matter of concern as currently more than 50 million of people are suffering from epilepsy which is more than the population of the country Spain (Jukic & Subasi, 2017). People are suffering from the seizure attacks which are exposing them in front of various types of harms as when they are having seizure attacks they become vulnerable and that can bring in various problems to them (Bandarabadi et al., 2015). Currently there are no such devices that can forecast when the patients can expect to get a seizure attack and knowing them is becoming more important day by day as the fear of having seizure attacks can potentially harm a person’s lifestyle.
For the patients who are suffering from epilepsy, the terrifying scenario of having seizure attacks is their daily concern that affects their day to day living. In this regard, it is a matter of fact that of the individuals can get a forecast, or a real time prediction of the time when they will be exposed to such attacks, that might be pretty helpful for the patients who are suffering from epilepsy (Alickovic, Kevric & Subasi, 2018). Epilepsy is an electric problem that takes place in the brains. Under normal circumstances human brain continuously sends signals and individuals who suffer from epilepsy, their brains experience an extra burst of electricity while sending signals and that causes an electric storm that manifests in seizures (Xiang et al., 2015). Therefore, Australian researcher Mark Cook has been continuously investing time to build a device that can effectively help to forecast when the patients can expect to get a seizure attack; as that can effectively make the lifestyle of the patients who suffer from epilepsy a bit easier.
It has been observed that the daily lifestyle of the patients who suffer from epilepsy gets affected due to the seizure attacks they receive. This is because these attacks can potentially get them into trouble if they are not at home or under odd circumstances. The people who experience seizure attacks often gets vulnerable to many harms when they suffer from seizure attacks under not home conditions (Fujiwara et al., 2016). Not only that, if a person experiences a seizure attack all alone, the person can lose his or her life also in that point of time by not receiving any help from others. Therefore, understanding the importance of the issue, Mark Cook, an Australian researcher is trying to device a machine that can effectively forecast the time of the seizure attacks for the patients who suffer from epilepsy. Mark Cook stated that he is expecting that this device will have the capability to reduce the stigmas associated with this disorder and he aims to change the way people look at this disorder.
Definition of the problem
It is seen that to make innovative ideas and materialize those in an easier way, some effective measures should be taken. The business organizations who operate in the medical sector can offer their medical staffs to share their innovative ideas with the authority and then the management or the board of directors can choose some of the ideas for the betterment of the medical sector as well as for the humankind (Ramgopal et al., 2014). In this regard, it can be said that the ideas which will seem to be helpful for the medical sector and for the humankind will be given importance and the authoritative stakeholders of the medical sector will look forward and help to work on that or those ideas (Yadollahpour & Jalilifar, 2015). For an example, when Mark Cook came up with his idea of devising a machine that can bring a remarkable change in the medical sector by predicting the time when the epilepsy patients can expect to have a seizure attack. His innovative idea was selected and he received adequate funds from the University of Australia and the federal government of the nation to continue working on his innovative ideas.
There are many manufacturing companies that operate in the medical sector that will come forward if the experiment of Mark Cook gets successful. It is a matter of fact that Mark Cook is working on a project that can effectively help the people who are suffering from epilepsy by forecasting the expected time for their seizure attacks (Brinkmann et al., 2016). There lies the significance of this research and therefore, federal government and many other organizations are coming forward to fund this innovative project.
It has been observed that technological advancements in contemporary times has given a major boost to the medical sector and that has provided benefits to the humankind in many ways. It has been seen that Mark Cook realized the situation that the patients who suffer from epilepsy undergoes and therefore he initiated to devise a machine that can forecast the time of the seizure attacks. As the medical sector of Australia is blessed with adequate funds and rapid technological advancements, Mark Cook will not have to face any challenges and he could easily get significant amount of funds to work on the project.
The innovative idea of devising a machine that can forecast the time of seizure attacks to the patients who are suffering from epilepsy can effectively help the medical world and more than 50 millions of patient across the worlds who are suffering from epilepsy. It has been observed that the management of numerous organizations who are operating in the medical sector has already agreed that they will manufacture the machines in cheap pricing so that they can help the humankind to get the benefits from the machines.
Evidence of the problem
The machine that can predict the times of the seizure attacks of the patients who suffer from epilepsy can effectively help a huge population with assuming the time of their seizure attacks and they will be live their life in a more relaxed manner (Moshé et al., 2015). That can effectively increase the safety and security of a large number of people and that is the major benefit that the federal government of Australia can expect from the innovative project.
With the frequent press meets and innovative ideas the medical sector of Australia is providing various benefits to the mass population of the country and it can be said that when the this devise can bring in remarkable changes in the medical sector and can be counted as one of the major breakthroughs in medical science in the last couple of decades. This will also enhance more researches in this field.
There are numerous interdependent features related to the development of innovative and novel ideas within the medical sector of Australia. Among them the topic of the research of Mark Cook has gained an enormous positive feedback from the all layers of the government and the medical sector and his research has been acknowledged as one of the groundbreaking research work already as it is a very relevant and serious topic of research that can benefit up to 50 millions of people who are suffering from epilepsy.
The topic of the research of Mark Cook has received some major positive feedbacks as his machine will be able to benefit up to 50 millions of people who are suffering from epilepsy. Mark Cook stated in a press meet that he will make sure that the production costs of the machine will be on the lower end so that all the people who are suffering from epilepsy can afford it. Quality of the machine, accuracy of the machine and reducing the production costs; these are the main aspects on which Mark Cook is emphasizing.
Mark Cook will be gathering relevant information and ideas from the medical sectors of all the different parts of the globe and implement them while devising the machine to improve its accuracy and the quality of the product. After making the machine successfully, Mark Cook will be guiding top manufacturing companies to manufacture the product in industrial quantity accurately.
- The manufacturer companies should focus on the quality of the product
- The manufacturer company will have to make sure that the readings of the devise are accurate
- The production costs should be on the lower end so that a large section of the patients can afford this medical devise.
- Mark Cook can approach federal government of Australia for assistance in the preliminary stages
- The manufacturer companies should focus on reducing the costs by utilizing eco-friendly materials that can be reused for making more devices.
- Mark Cook should always look for the areas of improvements in the device he is devising
- Mark Cook should focus on reducing the production costs
- The manufacturer companies should emphasize on making the devices accurate and of higher quality
- The manufacturer companies should deploy a highly skilled labor force to manufacture this type of devices
In this context, the primary stakeholders will be Mark Cook, the government of Australia and the manufacturer business organizations that will manufacture and market the product. The patients who are suffering from epilepsy disease are significant stakeholders of this project as well.
Timing considerations
This particular devise if gets success, it can effectively benefit up to 50 millions of people across the world by assuming the expected date when they will experience the seizure attacks due to epilepsy.
- This project and manufacturing this device will not affect the balance of the environment
- The manufacturer companies will always use latest eco friendly technologies while manufacturing this machine
- This machine will benefit a lot of people and help the labor force as the people who suffer from epilepsy cannot continue their regular professional life fearing the seizure attacks
- The manufacturing process will effectively create job opportunities
Considering the abovementioned points it can surely be said that this project can effectively help 50 millions of people across the world. Apart from that manufacturing this product can create significant amount of job opportunities.
risk |
management |
Financial risk |
The manufacturer companies should make an effective plan |
Entrance of more competitors |
Continuous process of innovation should be maintained |
The innovation of Mark Cook can personalize the readings of the assumptions regarding determining the expected time of getting seizure attacks for the people who suffer from epilepsy and can effectively bring in remarkable changes in the medical sector.
- The managements of the manufacturer companies should focus on the experience of the customers to improve the quality of the machines
- The managements of the manufacturer companies should focus on reducing the production costs
- The board of directors of the manufacturer organizations should supervise of the operational areas to ensure the quality of the products
- The customers or the epilepsy patients should be informed regarding the operations and functions of the device by providing a brochure
- There will be performance measurement tools for ensuring the quality of the machines
- The manufacturer companies should abide by the rules and regulations set by the federal government of Australia
Reference List
Alickovic, E., Kevric, J., & Subasi, A. (2018). Performance evaluation of empirical mode decomposition, discrete wavelet transform, and wavelet packed decomposition for automated epileptic seizure detection and prediction. Biomedical Signal Processing and Control, 39, 94-102.
Andrzejak, R. G., Rummel, C., Mormann, F., & Schindler, K. (2016). All together now: Analogies between chimera state collapses and epileptic seizures. Scientific reports, 6, 23000.
Bandarabadi, M., Teixeira, C. A., Rasekhi, J., & Dourado, A. (2015). Epileptic seizure prediction using relative spectral power features. Clinical Neurophysiology, 126(2), 237-248.
Brinkmann, B. H., Wagenaar, J., Abbot, D., Adkins, P., Bosshard, S. C., Chen, M., ... & Pardo, J. (2016). Crowdsourcing reproducible seizure forecasting in human and canine epilepsy. Brain, 139(6), 1713-1722.
Fujiwara, K., Miyajima, M., Yamakawa, T., Abe, E., Suzuki, Y., Sawada, Y., ... & Sasano, T. (2016). Epileptic seizure prediction based on multivariate statistical process control of heart rate variability features. IEEE Transactions on Biomedical Engineering, 63(6), 1321-1332.
Hosseini, M. P., Soltanian-Zadeh, H., Elisevich, K., & Pompili, D. (2016, December). Cloud-based deep learning of big eeg data for epileptic seizure prediction. In Signal and Information Processing (GlobalSIP), 2016 IEEE Global Conference on(pp. 1151-1155). IEEE.
Jukic, S., & Subasi, A. (2017). A MapReduce-based rotation forest classifier for epileptic seizure prediction. arXiv preprint arXiv:1712.06071.
Karoly, P. J., Freestone, D. R., Boston, R., Grayden, D. B., Himes, D., Leyde, K., ... & Cook, M. J. (2016). Interictal spikes and epileptic seizures: their relationship and underlying rhythmicity. Brain, 139(4), 1066-1078.
Morimoto, M., Satomura, S., Hashimoto, T., Ito, E., & Kyotani, S. (2016). Oxidative stress measurement and prediction of epileptic seizure in children and adults with severe motor and intellectual disabilities. Journal of clinical medicine research, 8(6), 437.
Moshé, S. L., Perucca, E., Ryvlin, P., & Tomson, T. (2015). Epilepsy: new advances. The Lancet, 385(9971), 884-898.
Rakers, F., Walther, M., Schiffner, R., Rupprecht, S., Rasche, M., Kockler, M., ... & Schwab, M. (2017). Weather as a risk factor for epileptic seizures: a case?crossover study. Epilepsia, 58(7), 1287-1295.
Ramgopal, S., Thome-Souza, S., Jackson, M., Kadish, N. E., Fernández, I. S., Klehm, J., ... & Loddenkemper, T. (2014). Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy. Epilepsy & behavior, 37, 291-307.
Sharma, R., & Pachori, R. B. (2015). Classification of epileptic seizures in EEG signals based on phase space representation of intrinsic mode functions. Expert Systems with Applications, 42(3), 1106-1117.
Wang, N., & Lyu, M. R. (2015). Extracting and selecting distinctive EEG features for efficient epileptic seizure prediction. IEEE journal of biomedical and health informatics, 19(5), 1648-1659.
Xiang, J., Li, C., Li, H., Cao, R., Wang, B., Han, X., & Chen, J. (2015). The detection of epileptic seizure signals based on fuzzy entropy. Journal of neuroscience methods, 243, 18-25.
Yadollahpour, A., & Jalilifar, M. (2015). Seizure prediction methods: a review of the current predicting techniques. Biomedical and Pharmacology Journal, 7(1), 153-162.
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