TY - GEN
T1 - Video minor stroke extraction using learning vector quantization
AU - Rahman, Aviv Yuniar
AU - Sumpeno, Surya
AU - Purnomo, Mauridhi Hery
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/18
Y1 - 2017/10/18
N2 - Video is very beneficial for health consultations, monitoring, disease identification, customer satisfaction survey efforts on fitness, health information in youtube. However, if the video health tips from youtube are untrue, the information will harm the person. Additionally, it will create the emotion youtube users who are looking for health information. Negative emotions cause effects blood pressure to rise. The impact of high blood pressure is such as stroke. In many developing countries found stroke, especially minor stroke disease which can attack several times a week. If it is not treated immediately, it will result in more severe disability. Handling stroke detection should be begun when the patient was thought to be affected. If it is done early, stroke treatment will reduce damage to organs caused. It requires early detection and treatment of stroke rehabilitation automatically. Therefore we propose the video object extraction minor stroke. The results of the segmentation process can be used to improve the detection performance of stroke in future studies. In addition, segmentation is used to maximize the prediction process of healing and rehabilitation of stroke patients in subsequent studies. This study uses a minor stroke extracted video object using LVQ which has been modified. Tests are using a variation of the constant (K) from 0.1 to 5. The results for the best accuracy are with a value 68.76 % of K = 4.3.
AB - Video is very beneficial for health consultations, monitoring, disease identification, customer satisfaction survey efforts on fitness, health information in youtube. However, if the video health tips from youtube are untrue, the information will harm the person. Additionally, it will create the emotion youtube users who are looking for health information. Negative emotions cause effects blood pressure to rise. The impact of high blood pressure is such as stroke. In many developing countries found stroke, especially minor stroke disease which can attack several times a week. If it is not treated immediately, it will result in more severe disability. Handling stroke detection should be begun when the patient was thought to be affected. If it is done early, stroke treatment will reduce damage to organs caused. It requires early detection and treatment of stroke rehabilitation automatically. Therefore we propose the video object extraction minor stroke. The results of the segmentation process can be used to improve the detection performance of stroke in future studies. In addition, segmentation is used to maximize the prediction process of healing and rehabilitation of stroke patients in subsequent studies. This study uses a minor stroke extracted video object using LVQ which has been modified. Tests are using a variation of the constant (K) from 0.1 to 5. The results for the best accuracy are with a value 68.76 % of K = 4.3.
KW - LVQ
KW - minor stroke
KW - stroke
KW - stroke detection
KW - video health
KW - video object extraction
KW - video object segmentation
UR - http://www.scopus.com/inward/record.url?scp=85039948437&partnerID=8YFLogxK
U2 - 10.1109/ICoICT.2017.8074687
DO - 10.1109/ICoICT.2017.8074687
M3 - Conference contribution
AN - SCOPUS:85039948437
T3 - 2017 5th International Conference on Information and Communication Technology, ICoIC7 2017
BT - 2017 5th International Conference on Information and Communication Technology, ICoIC7 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Information and Communication Technology, ICoIC7 2017
Y2 - 17 May 2017 through 19 May 2017
ER -