Diagnosis of Alzheimer ’ s Disease using Electric Signals of the Brain A Grand Challenge

“I have recently been told that I am one of the millions of Americans who will be afflicted with Alzheimer’s Disease. ” wrote the 40th president of the United States, Ronald Reagan, diagnosed with Alzheimer’s Disease (AD) at the age of 83. Presently, one American develops AD in every 68 seconds, and by 2050 the rate is expected to increase to 33 seconds [1]. AD particularly affects the elderly population. In the United States, over 10% of people over age 65 and 50% of people over age 85 are affected by AD, and its prevalence is expected to triple within the next 50 years [2]. AD causes degeneration of the nervous system, leading to loss of memory, and reduced intellectual and social skills. No known cure exists for AD, however, progress is being made in drugs that slow its progression. As AD patients are elderly, their medical treatment is complex and costly compared to other diseases. Moreover, providing medical care for the AD patients is a difficult task where the care givers undergo a large physical and emotional stress. In the preclinical stage of AD known as mild cognitive impairment (MCI) or predementia, the symptoms are not measurable enough, often ignored, and mistaken with the normal consequences of aging. Around 6% to 25% of the people affected with MCI progress to AD every year. The two first stages of AD, known as mild and moderate AD, are characterized by symptoms such as confusion, loss of language, and long-term memory loss. These cognitive deficits are so severe that it makes the patient withdraw from the social and family life, and become more dependent. In the final stage, known as severe AD, the personality deteriorates completely and the patients become entirely dependent on their caregivers. Once diagnosed positive, the average life expectancy of the patients is less than seven years. Between years 2000 to 2008, there was an increase in deaths due to AD by 66% [1]. Diagnosis of AD, particularly early diagnosis, is important for several reasons [3]. Most of the symptomsdelaying medicines are effective when used in the early stage of the disease. Early diagnosis also allows effective treatment of psychiatric symptoms such as depression, which indirectly reduces the personal and societal costs of the disease. A positive early diagnosis gives the patients and their family the necessary time to understand the disease, to decide on the life and financial burdens of the disease, and to arrange for the future needs and care of the patients. There is no specific test to diagnose AD directly, instead doctors often diagnose AD based on various tests to eliminate other possible causes [4]. These tests include simple physical and neurological examination, blood and spinal fluid tests, mental status tests, and neuropsychological tests. Increasingly, brain imaging techniques such as computerized tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) are being explored for diagnosing AD. Apart from the mental and neuropsychological examinations, other examinations are either invasive or possess radiation dose (CT/PET), and/or are costly. There is a growing demand for AD diagnosis methods that are noninvasive, fast, inexpensive, and reliable. Electroencephalography has the potential to become such diagnostic tool for AD. We will now briefly elaborate on electroencephalography. The nerve cells, known as neurons, form the fundamental building blocks of the human brain, communicating among themselves (and other cells in the brain) by electrical and chemical signaling. The electrical signals among the neurons gives rise to an electric field on the scalp, which can be measured noninvasively, and this recording is referred to as electroencephalogram (EEG). EEG is considered as “window of the mind,” as neurological diseases typically affect EEG in some specific ways. In recent years, many researchers have started investigating the potential use of EEG for diagnosing AD (see [3] for a review). EEG recording systems have become relatively inexpensive, compact, and mobile. Consequently, EEG can be recorded at the point of care (e.g., at home) at low cost, and hence EEG may potentially be used as a tool to screen a large population for the risk of AD. Though EEG signals often contain a wealth of information, the changes in EEG associated with AD are often not sensitive enough to show a clear differentiation, especially at early stages of AD. Significant research efforts are being made in improving the sensitivity of EEG in order to make it an effective tool for diagnosing AD. According to the literature (see [3] for a review), AD perturbs EEG in three major ways. First, the EEG of AD patients becomes slower, in other words, more power in the EEG spectrum is concentrated at lower frequencies. Second, AD EEG contains fewer fluctuations, and hence it is considered less complex compared to healthy EEG. Third, EEG signals from different regions of the brain are less correlated in AD patients