Alzheimer's Disease Diagnostics Market Forecast to Reach USD 15.57 Billion by 2030

The global Alzheimer's disease diagnostics market is a rapidly expanding field, driven by the increasing prevalence of dementia in an aging population. While traditional diagnostic methods like brain imaging and cerebrospinal fluid analysis are well-established, Electroencephalography (EEG) is emerging as a powerful, non-invasive, and cost-effective alternative. This article explores the potential of EEG in the market, the challenges it faces, and a proposed solution to maximize its impact.
The Alzheimer's disease diagnostics market was valued at USD 8.33 billion in 2024 and is projected to reach USD 15.57 billion by 2030, growing at a CAGR of 11.03% from 2025 to 2030. North America is a dominant market, holding a 47.63% share in 2024.

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The Problem: Diagnostic Challenges in Alzheimer's
Despite the market's growth, significant problems persist in Alzheimer's diagnostics. The gold-standard diagnostic tools, such as MRI and PET scans, are often costly and not widely accessible, especially in developing nations. Furthermore, the interpretation of results can be subjective. Another major challenge is the difficulty in diagnosing Alzheimer's at its earliest stages, as cognitive changes can be subtle and mimic other conditions. Many current methods are only effective in later stages of the disease when a significant decline has already occurred.

The Solution: Quantitative EEG (qEEG)
Quantitative EEG, or qEEG, presents a compelling solution to these problems. It offers a way to quantify neurophysiological changes associated with Alzheimer's disease by analyzing brainwave patterns. Research shows that EEG can detect changes such as spectral slowing (increased activity in delta and theta bands and decreased activity in alpha and beta bands) and reduced signal complexity. This can be used to distinguish between healthy subjects, patients with mild cognitive impairment (MCI), and those with Alzheimer's. Studies have demonstrated a classification accuracy of over 90% in some cases, highlighting its potential for early and accurate detection. The high temporal resolution of EEG also makes it valuable for monitoring disease progression and the effectiveness of treatments. By integrating qEEG with machine learning algorithms, the interpretation of brain signals can be automated, reducing human error and providing a more objective diagnosis.

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US Tariff Implications on the Market
The US market, being a key driver of the global diagnostics industry, is not immune to external factors. Tariffs on imported medical devices and components can significantly increase production costs and consumer prices. The medical device industry, which includes diagnostic equipment like EEG machines, is heavily dependent on complex global supply chains. Recent trade policies have introduced tariffs on goods from major trading partners, potentially leading to higher costs for healthcare providers and patients. These tariffs can create a barrier to entry for innovative, non-US manufactured diagnostic technologies, and may even lead to companies moving manufacturing to the US to avoid them. This could also affect the affordability and accessibility of new diagnostic tools.

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