عنوان انگلیسی مقاله:
Suppression of noises using fast independent component analysis (FICA) and signal saturation using fuzzy adaptive histogram equalization (FAHE) for intensive care unit false alarms
ترجمه فارسی عنوان مقاله:
سرکوب سر و صدا با استفاده از تجزیه و تحلیل سریع مؤلفه مستقل (FICA) و اشباع سیگنال با استفاده از تسویه حساب هیستوگرام تطبیقی فازی (FAHE) برای آلارم های دروغین بخش مراقبت ویژه
Sciencedirect - Elsevier - Measurement, 145 (2019) 400-409: doi:10:1016/j:measurement:2019:02:007
V. Ravindra Krishna Chandar a,⇑, M. Thangamani b
In the medical field, fake alarms are classically described as alarms with no clinical or therapeutic effects.
A variety of studies exist in the clinical literature regarding the alarms monitoring in Arterial Blood
Pressure (ABP) Signal and intensive care medicine. In the proposed work measurement of each one of
the ABP, signal values are carried out employing the Fast Independent Component Analysis (FICA), which
detects areas affected with high-frequency noise. When the noises in the samples are eliminated, then
the signal saturation values are decided with the help of the Fuzzy Wavelet Transform (FWT) technique.
Then, the automated feature engineering was carried out utilizing the signal for ABP along with a processed
signal, which has the count of the times of every monitored heartbeat acquired from the ABP signal.
Subsequently, Kullback–Leibler divergence Kernel -Support Vector Machine (KLDK-SVM), Random
Forest (RF), and SVM classifiers were trained so as to generate the classification models. The newly introduced
scheme can be used to help the medical professional and specialists, letting them become more
useful and are responsive to alarms as quickly as possible
Keywords: Machine learning | Medical expert systems | Signal processing | Fast Independent Component Analysis | (FICA) | Fuzzy Wavelet Transform (FWT) | patient |monitoring | Time series analysis | Pattern recognition | Invalid data segments | Data processing