کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6902268 | 1446500 | 2017 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Stress Detection in Working People
ترجمه فارسی عنوان
تشخیص استرس در افراد کار
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
چکیده انگلیسی
Stress detector classifies a stressed individual from a normal one by acquiring his/her physiological signals through appropriate sensors such as Electrocardiogram (ECG), Galvanic Skin Response (GSR) etc,. These signals are pre-processed to extract the desired features which depicts the stress level in working individuals. Support Vector Machine (SVM) and K-Nearest Neighbour (KNN) are investigated to classify these extracted feature set. The result indicates feature vector with best features having a strong influence in stress identification. An attempt is made to determine the best feature set that results in maximum classification accuracy. Proposed techniques are applied on benchmark SWELL-KW dataset and state-of-art results are obtained.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 115, 2017, Pages 359-366
Journal: Procedia Computer Science - Volume 115, 2017, Pages 359-366
نویسندگان
S. Sriramprakash, Vadana D Prasanna, O.V. Ramana Murthy,