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市場調査レポート
商品コード
1764803
ニューロサイエンスの市場規模、シェア、成長分析、コンポーネント別、技術別、エンドユーザー別、地域別 - 産業予測、2025年~2032年Neuroscience Market Size, Share, and Growth Analysis, By Component (Instruments, Consumables), By Technology (Brain Imaging, Neuro-Microscopy), By End-user, By Region - Industry Forecast 2025-2032 |
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ニューロサイエンスの市場規模、シェア、成長分析、コンポーネント別、技術別、エンドユーザー別、地域別 - 産業予測、2025年~2032年 |
出版日: 2025年07月04日
発行: SkyQuest
ページ情報: 英文 192 Pages
納期: 3~5営業日
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ニューロサイエンスの世界市場規模は2023年に405億米ドルとなり、予測期間(2025年~2032年)のCAGRは5.1%で、2024年の425億7,000万米ドルから2032年には633億7,000万米ドルに成長する見通しです。
世界のニューロサイエンス市場は、消費者行動のシフト、政府の取り組み、技術の進歩によって大きな成長が見込まれています。世界各国の当局は、スマートヘルスケアと認知診断を強化するため、ニューロデジタルインフラストラクチャへの投資を進めています。シンガポールでは、2024年までに本格展開されるウェアラブル脳波計とニューロフィードバック装置を組み込んだ全国的な神経データ分析プラットフォームによって、スマートヘルス構想が例証されています。これらのデバイスは、さまざまなヘルスケア環境における脳波活動やストレスレベルに関するリアルタイムの神経学的データを収集します。STエンジニアリングとニューロスカイのような官民パートナーシップの台頭により、2025年までメンタルヘルス問題のスクリーニングとモニタリングがさらに進むと予想されます。一方、機械学習とAIは超個人化治療を可能にし、5Gの普及は遠隔神経モニタリング機能を強化し、タイムリーな介入を向上させ、医療技術の持続可能性を促進します。
Global Neuroscience Market size was valued at USD 40.5 billion in 2023 and is poised to grow from USD 42.57 billion in 2024 to USD 63.37 billion by 2032, growing at a CAGR of 5.1% during the forecast period (2025-2032).
The global neuroscience market is poised for significant growth driven by shifts in consumer behavior, government initiatives, and technology advancements. Authorities worldwide are investing in neuro-digital infrastructure to enhance smart healthcare and cognitive diagnostics. In Singapore, the Smart Health initiative is exemplified by a nationwide neural data analytics platform incorporating wearable EEG and neurofeedback devices, set for full deployment by 2024. These devices gather real-time neurological data on brainwave activity and stress levels in various healthcare settings. The rise of public-private partnerships, such as those between ST Engineering and NeuroSky, is expected to further advance screening and monitoring for mental health issues through 2025. Meanwhile, machine learning and AI are enabling hyper-personalized therapies, and the proliferation of 5G is enhancing remote neuro-monitoring capabilities, improving timely interventions and promoting sustainability in medical technology.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Neuroscience market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global Neuroscience Market Segments Analysis
Global Neuroscience Market is segmented by Component, Technology, End-user and region. Based on Component, the market is segmented into Instruments, Consumables and Software & Services. Based on Technology, the market is segmented into Brain Imaging, Neuro-Microscopy, Stereotaxic Surgeries, Neuro-Proteomic Analysis, Neuro-Cellular Manipulation and Others. Based on End-user, the market is segmented into Hospitals, Diagnostic laboratories and Research and Academic Institute. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.
Driver of the Global Neuroscience Market
The global neuroscience market is being significantly influenced by the integration of artificial intelligence (AI) and machine learning technologies in brain health management. These innovations enable real-time analysis of neural data, allowing for early recognition of patterns and customized cognitive therapy solutions that have transformed the field. Additionally, AI-driven applications, such as natural language processing (NLP) and computer vision algorithms, enhance the accuracy with which physicians interpret complex brain imaging and neurophysiological signals compared to traditional methods. The rise in popularity of AI-integrated brain-computer interfaces (BCIs) is also shaping neurorehabilitation, prosthetic control, and communication enhancements for patients with severe brain injuries.
Restraints in the Global Neuroscience Market
The Global Neuroscience market faces significant constraints due to the substantial financial investment required for acquiring, installing, calibrating, and maintaining advanced neuroscience technologies. Cutting-edge tools such as functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG) systems, electrocorticography (ECoG), brain-computer interfaces (BCIs), and high-resolution neuroimaging platforms demand considerable resources, making them costly for research institutions and healthcare facilities. This financial barrier can limit accessibility and hinder widespread adoption of these critical technologies, potentially slowing advancements in neuroscience research and clinical applications. As a result, the high costs associated with these sophisticated tools pose a notable challenge to the industry's growth.
Market Trends of the Global Neuroscience Market
The Global Neuroscience market is experiencing a significant transformation driven by the integration of AI-powered precision diagnostics and programmatic decision-making. Similar to how programmatic advertising reshaped digital marketing, AI-driven analytics are enhancing neuroscience diagnostics through predictive modeling, automated neural image processing, and advanced EEG interpretation. This shift enables real-time, data-informed decisions, which optimize treatment protocols, streamline clinical workflows, and enhance diagnostic accuracy by adapting strategies based on immediate neural feedback. As a result, leading healthcare providers and med-tech innovators now regard widespread AI integration as a vital strategy for improving patient outcomes and increasing the efficiency of clinical interventions within the neuroscience sector.