Artifact Removal in Physiological Signals - Practices and Possibilities
نویسندگان
چکیده
The combination of reducing birth rate and increasing life expectancy continues to drive the demographic shift toward an aging population. This, in turn, places an ever-increasing burden on healthcare due to the increasing prevalence of patients with chronic illnesses and the reducing income-generating population base needed to sustain them. The need to urgently address this healthcare "time bomb" has accelerated the growth in ubiquitous, pervasive, distributed healthcare technologies. The current move from hospital-centric healthcare toward in-home health assessment is aimed at alleviating the burden on healthcare professionals, the health care system and caregivers. This shift will also further increase the comfort for the patient. Advances in signal acquisition, data storage and communication provide for the collection of reliable and useful in-home physiological data. Artifacts, arising from environmental, experimental and physiological factors, degrade signal quality and render the affected part of the signal useless. The magnitude and frequency of these artifacts significantly increases when data collection is moved from the clinic into the home. Signal processing advances have brought about significant improvement in artifact removal over the past few years. This paper reviews the physiological signals most likely to be recorded in the home, documenting the artifacts which occur most frequently and which have the largest degrading effect. A detailed analysis of current artifact removal techniques will then be presented. An evaluation of the advantages and disadvantages of each of the proposed artifact detection and removal techniques, with particular application to the personal healthcare domain, is provided.
منابع مشابه
Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique
Background: The electrocardiogram artifact is a major contamination in the electromyogram signals when electromyogram signal is recorded from upper trunk muscles and because of that the contaminated electromyogram is not useful.Objective: Removing electrocardiogram contamination from electromyogram signals.Methods: In this paper, the clean electromyogram signal, electrocardiogram artifact and e...
متن کاملEEG Artifact Removal System for Depression Using a Hybrid Denoising Approach
Introduction: Clinicians use several computer-aided diagnostic systems for depression to authorize their diagnosis. An electroencephalogram (EEG) may be used as an objective tool for early diagnosis of depression and controlling it from reaching a severe and permanent state. However, artifact contamination reduces the accuracy in EEG signal processing systems. Methods: This work proposes a no...
متن کاملReview of State of Art in Electrooculogram Artifact Removal from Electroencephalogram Signals
Electroencephalogram (EEG) is a time varying brain electrical activity, highly sensitive and gives a coarse view of neural activity. It has been used to study cognitive processes and the physiology of the brain. EEG recordings are distorted by physiological and nonphysiological signals causing problems to the clinicians, neuropsychologist and researchers for analysis, interpretation and diagnos...
متن کاملImplementing a Smart Method to Eliminate Artifacts of Vital Signals
Background: Electroencephalography (EEG) has vital and significant applications in different medical fields and is used for the primary evaluation of neurological disorders. Hence, having easy access to suitable and useful signal is very important. Artifacts are undesirable confusions which are generally originated from inevitable human activities such as heartbeat, blinking of eyes and facial ...
متن کاملAutomatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information
Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society
دوره 16 3 شماره
صفحات -
تاریخ انتشار 2012