IOT Based Wireless Monitoring Stroke Patient with Partial Paralysis Assistance
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International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2019 by IJETT Journal | ||
| Volume-67 Issue-5 |
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| Year of Publication : 2019 | ||
| Authors : Pradeep Kumar S,Chandana Gireesh, Riti Dass, Sneha Sinha, Sumit Kumar, Subhra Chakraborty |
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| DOI : 10.14445/22315381/IJETT-V67I5P216 |
Citation
MLA Style: Pradeep Kumar S,Chandana Gireesh, Riti Dass, Sneha Sinha, Sumit Kumar, Subhra Chakraborty "IOT Based Wireless Monitoring Stroke Patient with Partial Paralysis Assistance" International Journal of Engineering Trends and Technology 67.5 (2019):104-110.
APA Style: Pradeep Kumar S,Chandana Gireesh, Riti Dass, Sneha Sinha, Sumit Kumar, Subhra Chakraborty (2019). IOT Based Wireless Monitoring Stroke Patient with Partial Paralysis Assistance International Journal of Engineering Trends and Technology,67(5),104-110.
Abstract
Paralysis or the inability of a muscle to move is one of the most common disabilities resulting from stroke. As many as 9 out of 10 stroke survivors have some degree of paralysis immediately following a stroke. Continued rehabilitation and therapy can help stroke survivors regain voluntary movement even years following their stroke. Our project is a prototype model for a person who is partially paralyzed or has suffered from a partial stroke. We have designed such a system where a partially paralyzed or a stroke person need not depend on an individual for basic needs such as turning on the light or adjusting bed and can communicate with a person in case of emergency just by the motion of his head. He can even ask for immediate help without having to speak. Also, we will be collecting live feedback of the patient’s health parameters and sending an alert message to the patient’s loved ones or his attendant whenever his health parameters show fluctuations from the normal patient’s readings. This data can be very useful for the doctors for making any assumption and giving the right medical aid to the patient as the doctor can have an easy tracking view of the patient’s health improvement over time. Stroke is one of the leading causes of morbidity and mortality in adults, accounting for 17.3 million deaths per year. By 2030, it is estimated that more than 23.6 million stroke patients in United States will die from an indirect result of the stroke. Stroke is a medical emergency. So, the stroke patient’s continuous health analysis, monitoring and immediate catering to his needs as suggested in our prototype model would help reduce the arrival time of a medical caregiver and accordingly decrease the mortality rate.
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Keywords
Stroke, health analysis, health monitoring, health feedback, alert message