What Is Alzheimer's Disease?

Alzheimer's disease is a progressive neurodegenerative disorder characterized by the accumulation of abnormal protein aggregates in the brain, leading to synaptic loss, neuronal death, and a gradual decline in memory, cognition, and functional capacity. It is the most common form of dementia and accounts for 60 to 70 percent of dementia cases globally. The disease affects regions of the brain responsible for memory and spatial navigation before spreading to involve areas governing language, reasoning, and motor function, rendering it both a clinical challenge and a major target for engineering and computing research in biomedical signal processing, neuroimaging, and assistive technology.

Alzheimer's disease draws on neuroscience, gerontology, molecular biology, and, increasingly, electrical engineering and computer science. Its prevalence rises sharply with age, placing it at the center of gerontological medicine as global populations age. The disease's long preclinical phase, extending 15 to 20 years before symptoms appear, has motivated intensive efforts to identify early biomarkers and to develop diagnostic tools that can detect pathological changes before cognitive decline becomes clinically evident.

Neuropathology and Biomarkers

The defining pathological hallmarks of Alzheimer's disease are extracellular amyloid-beta (Aβ) plaques and intracellular neurofibrillary tau tangles. Aβ plaques form from the aggregation of amyloid-beta peptides, particularly the 42-amino-acid isoform Aβ₄₂, which arise from sequential cleavage of the amyloid precursor protein (APP). Tau tangles form when the microtubule-associated tau protein becomes hyperphosphorylated and misfolds, destabilizing neuronal axons. The hippocampus, a bilateral structure in the medial temporal lobe essential for episodic memory formation, is among the earliest regions affected: volumetric MRI studies consistently show hippocampal atrophy in early Alzheimer's patients years before severe cognitive symptoms appear. A comprehensive review of neuropathology, neuroimaging, and fluid biomarkers in Alzheimer's disease documents how cerebrospinal fluid levels of Aβ₄₂, total tau, and phosphorylated tau (p-tau) reflect the underlying pathology and can be measured years before clinical diagnosis.

Neuroimaging and Computational Detection

Structural MRI provides quantitative measures of brain atrophy, particularly hippocampal and entorhinal cortex volume loss, used to track disease progression and stratify patients in clinical trials. Positron emission tomography (PET) with amyloid- and tau-selective tracers allows direct visualization of plaque and tangle burden in living patients, providing pathological confirmation without autopsy. Plasma biomarkers, especially p-tau217, have emerged as less invasive alternatives to cerebrospinal fluid sampling, with studies showing that plasma p-tau217 detects AD pathology with accuracy comparable to PET imaging. Electroencephalography (EEG) offers a low-cost complement to imaging methods: slowing of EEG rhythms, decreased coherence between regions, and increased delta/theta band power are reproducible correlates of Alzheimer's progression. IEEE research on EEG signal processing using discrete wavelet transform and machine learning has demonstrated automated classification of Alzheimer's patients from healthy controls and patients with mild cognitive impairment using extracted spectral features fed to supervised classifiers.

Treatment Research and Assistive Technology

Pharmacological research has focused on therapies targeting amyloid clearance and tau pathology. Monoclonal antibodies such as lecanemab and donanemab, approved or under review by regulatory agencies, reduce amyloid plaque burden in early-stage patients and slow cognitive decline in clinical trials. On the engineering side, wearable sensors and ambient monitoring systems are being developed to track behavioral and physiological changes associated with disease progression, enabling remote patient monitoring and reducing caregiver burden. Brain stimulation approaches, including transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS), are being investigated to modulate neural circuits affected by the disease.

Applications

Alzheimer's disease research and technology have applications in a range of fields, including:

• Neuroimaging and biomarker analysis for early diagnosis and disease staging
• Wearable and ambient sensor systems for cognitive monitoring and fall detection
• EEG and biosignal processing for automated dementia screening
• Brain-computer interfaces and assistive communication devices for late-stage patients
• Caregiver support platforms and remote patient monitoring systems
• Computational drug discovery and clinical trial design for anti-amyloid therapeutics