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市場調查報告書
商品編碼
1871971
智慧型穿戴腦電圖設備:全球市場佔有率和排名、總收入和需求預測(2025-2031年)Smart Wearable EEG Device - Global Market Share and Ranking, Overall Sales and Demand Forecast 2025-2031 |
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2024 年全球智慧型穿戴腦電圖設備市場規模估計為 1.58 億美元,預計到 2031 年將達到 5.82 億美元,在預測期(2025-2031 年)內複合年成長率為 19.8%。
本報告對近期有關智慧型穿戴腦電圖設備的關稅調整和國際策略反制措施進行了全面評估,包括跨境產業佈局、資本配置模式、區域經濟相互依存關係和供應鏈重組。
智慧型穿戴腦電圖(EEG)設備是消費級穿戴設備,用於測量腦電波。它們使用放置在前額的腦電圖感測器來檢測大腦活動並記錄電活動。然後,該穿戴式設備與程式和應用程式配合使用,將數據轉化為對用戶有用的資訊。
全球主要的智慧穿戴式腦電圖(EEG)設備製造商包括InteraXon、Neurosky、Macrotellect和Emotiv。前四大公司佔了約80%的市場。亞太地區是智慧穿戴式腦電圖設備最大的市場,市佔率超過45%。按產品類型分類,頭戴式設備佔據最大市場佔有率,約佔51%;預計到2028年,頭帶式設備將成為最大市場佔有率,約佔51%。依應用領域分類,科學研究和教育是最大的應用領域,約佔55%。
智慧型穿戴腦電圖設備的主要市場促進因素包括:
科技進步:核心驅動力
先進的感測器和演算法
軟性電子技術:微型無線感測器(例如REMI)克服了傳統設備體積龐大的局限性,可實現居家長期監測。 REMI感測器在時域和頻域均檢驗出較高的相關性(0.86-0.94),其癲癇發作檢測性能與有線設備相當。 69%的使用者認為配戴舒適。
人工智慧演算法創新:深度學習模型(CNN、LSTM、 變壓器)在腦電訊號處理方面表現優異。例如:
【癲癇檢測】CNN-LSTM 組合模型在公開資料集上實現了三分類 98% 的準確率和二分類 100% 的準確率。
情緒辨識:基於 CNN-RNN 的模型能夠從腦電訊號中實現多情緒分類,並應用於心理健康監測和互動式系統。
資料處理能力提升
即時監測和預警:人工智慧演算法實現對腦電訊號的即時分析,並在診斷睡眠障礙和帕金森氏症方面提供即時回饋。
個人化醫療:透過將使用者的基因資訊與臨床症狀結合,人工智慧將客製化治療方案,促進精準醫療的發展。
消費者需求:日益增強的健康意識
醫療保健需求飆升
疲勞和睡眠問題:在中國青少年和高壓力人群中,分別有 59.1% 和 57.1% 的人患有疲勞問題,而高壓力人群中有 42.9% 的人患有記憶問題,這推動了對睡眠監測設備的需求。
心理健康問題:過度壓力已成為中青年族群面臨的主要心理問題。腦電圖設備可透過情緒辨識技術(例如,DEAP資料集)提供心理健康監測和介入。
擴展應用場景
醫療診斷:對癲癇、睡眠障礙等疾病進行家庭監測和早期診斷。
非醫療領域:
教育:注意力訓練(例如,腦機介面以提高學習能力)。
遊戲互動:腦電圖控制設備(例如,SSVEP、P300 訊號驅動的虛擬角色操作)。
電競最佳化:FocusBand 使用腦電圖 (EEG) 來最佳化玩家的專注力並提高競技表現。
政策支持:促進高層設計
國家戰略方向
「健康中國2030」計畫概述:將健康定位為優先發展策略,並推廣穿戴式裝置在疾病預防和健康管理的應用。
智慧醫療產業發展行動計畫(2021-2025):明確老年照護場所智慧型裝置的標準及其針對老年人的設計,促進科技的廣泛應用。
行業標準和規範
醫療設備監管:國家食品藥物管理局將推進醫療領域穿戴式裝置的合格評定,以確保訊號品質和臨床療效。
消費促進政策:2023年國務院《恢復與擴大消費措施》將明確規定支持穿戴式裝置消費,並為電子產品創造新的應用情境。
技術整合與創新
深化腦機介面:將腦電圖 (EEG) 與擴增實境/虛擬實境 (AR/VR) 結合,創造更自然的互動體驗。
多模態數據整合:整合心率和皮膚電訊號等多維數據,以提高診斷準確性。
市場挑戰
資料隱私與安全:腦電圖資料包含敏感的健康訊息,需要加密和加強合規控制。
需要臨床檢驗:某些設備在複雜病例中的準確性仍需進行廣泛的臨床檢驗。
政策改善方向
健康保險覆蓋範圍:促進將穿戴式腦電圖設備納入健康保險覆蓋範圍,減少使用者採用的障礙。
國際標準的協調統一:全球技術標準和認證流程的協調統一將促進跨境市場擴張。
智慧型穿戴腦電圖(EEG)設備的市場成長受到技術創新、健康意識提升、政策利好、製造商創新以及消費者認知水平提高的驅動。隨著人工智慧演算法的最佳化、感測器效能的提升以及政策的完善,這些設備將進一步融入醫療、教育、娛樂等多種場景,從而形成以使用者為中心的健康管理生態系統。
本報告旨在按地區/國家、類型和應用對全球智慧穿戴腦電圖設備市場進行全面分析,重點關注總銷售量、收入、價格、市場佔有率和主要企業的排名。
本報告以銷售量和收入(百萬美元)為單位,對智慧穿戴式腦電圖(EEG)設備的市場規模、估值和預測進行了呈現,以2024年為基準年,並涵蓋了2020年至2031年的歷史數據和預測數據。定量和定性分析將幫助讀者制定業務和成長策略,評估市場競爭,分析自身在當前市場中的地位,並就智慧穿戴腦電圖設備做出明智的商業決策。
市場區隔
公司
按類型分類的細分市場
應用領域
按地區
The global market for Smart Wearable EEG Device was estimated to be worth US$ 158 million in 2024 and is forecast to a readjusted size of US$ 582 million by 2031 with a CAGR of 19.8% during the forecast period 2025-2031.
This report provides a comprehensive assessment of recent tariff adjustments and international strategic countermeasures on Smart Wearable EEG Device cross-border industrial footprints, capital allocation patterns, regional economic interdependencies, and supply chain reconfigurations.
A Smart Wearable EEG Device is a consumer-grade wearable device for electroencephalography. The device records the electrical activity of the brain by using EEG sensors placed along the forehead to detect brain activity. The wearable device then communicates with a program or app to interpret the data into valuable information for the user.
Global key manufacturers of Smart Wearable EEG Device include InteraXon, Neurosky, Macrotellect, Emotiv, etc. Global top four manufacturers hold a share about 80%. Asia-Pacific is the largest market of Smart Wearable EEG Device, holds a share over 45%. In terms of product, the headset holds a larger segment, with a share about 51%, but it is predicted that by 2028, the headband would holds a larger segment of about 51%. And in terms of application, the largest application is research and education, with a share of about 55%.
The main market drivers of smart wearable EEG devices include the following:
Technological progress: the core driving force
Sensor and algorithm upgrade
Flexible electronic technology: micro wireless sensors (such as REMI) break through the bulky limitations of traditional devices and achieve long-term monitoring at home. REMI sensors have been verified by high correlation in the time domain/frequency domain (0.86-0.94), and their performance is comparable to that of wired devices in epileptic seizure detection, and 69% of users recognize their comfort.
AI algorithm breakthrough: Deep learning models (CNN, LSTM, Transformer) perform well in EEG signal processing. For example:
Epilepsy detection: The CNN-LSTM combination model achieves 98% ternary classification accuracy and 100% binary classification accuracy on public data sets.
Emotion recognition: The CNN-RNN-based model realizes multi-emotion classification through EEG signals and is applied to mental health monitoring and interactive systems.
Data processing capability improvement
Real-time monitoring and early warning: AI algorithms realize real-time analysis of EEG signals, such as providing instant feedback in the diagnosis of sleep disorders and Parkinson's disease.
Personalized medicine: Combining user genetic information with clinical symptoms, AI customizes treatment plans to promote the development of precision medicine.
Consumer demand: Awakening of health awareness
Demand for health management surges
Fatigue and sleep problems: Among Chinese teenagers and high-pressure people, 59.1% and 57.1% have fatigue problems, and 42.9% of high-pressure people suffer from memory loss, which drives the demand for sleep monitoring equipment.
Mental health concerns: Excessive stress has become a major psychological problem for young and middle-aged people. EEG equipment provides mental health monitoring and intervention through emotion recognition technology (such as DEAP dataset).
Application scenario expansion
Medical diagnosis: Home monitoring and early diagnosis of diseases such as epilepsy and sleep disorders.
Non-medical scenarios:
Education: Attention training (such as brain-computer interface to improve learning efficiency).
Games and interactions: Brain control equipment (such as SSVEP, P300 signal-driven virtual character control).
E-sports optimization: FocusBand optimizes players' concentration through EEG to improve competitive performance.
Policy support: top-level design promotion
National strategic orientation
Outline of the "Healthy China 2030" Plan: Put health in the priority development strategy and promote the application of wearable devices in disease prevention and health management.
Action Plan for the Development of Smart Health Care Industry (2021-2025): Clarify the standard construction and aging-friendly design of smart devices in the elderly care scene and promote the popularization of technology.
Industry standards and specifications
Medical device supervision: The State Food and Drug Administration promotes compliance certification of wearable devices in the medical field to ensure signal quality and clinical effectiveness.
Consumption encouragement policy: The State Council's "Measures on Restoring and Expanding Consumption" in 2023 clearly supports the consumption of wearable devices and creates new scenarios for the application of electronic products.
Technology integration and innovation
Deepening of brain-computer interface: EEG is combined with AR/VR to achieve a more natural interactive experience.
Multimodal data integration: Integrate multi-dimensional data such as heart rate and skin electrical signals to improve diagnostic accuracy.
Market challenges
Data privacy and security: EEG data involves sensitive health information, and encryption and compliance management need to be strengthened.
Clinical verification needs: The accuracy of some devices in complex cases still needs large-scale clinical verification.
Policy refinement direction
Medical insurance coverage: Promote the inclusion of wearable EEG devices in the scope of medical insurance reimbursement to lower the threshold for users to use.
International standard unification: Coordinate global technical standards and certification processes to promote cross-border market expansion.
The market growth of smart wearable EEG devices is driven by technological innovation, health awareness, policy dividends, manufacturer innovation and consumption upgrades. In the future, with the optimization of AI algorithms, the improvement of sensor performance and the refinement of policies, the equipment will further penetrate multiple scenarios such as medical care, education, and entertainment, forming a user-centered health management ecosystem.
This report aims to provide a comprehensive presentation of the global market for Smart Wearable EEG Device, focusing on the total sales volume, sales revenue, price, key companies market share and ranking, together with an analysis of Smart Wearable EEG Device by region & country, by Type, and by Application.
The Smart Wearable EEG Device market size, estimations, and forecasts are provided in terms of sales volume (Units) and sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Smart Wearable EEG Device.
Market Segmentation
By Company
Segment by Type
Segment by Application
By Region
Chapter Outline
Chapter 1: Introduces the report scope of the report, global total market size (value, volume and price). This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.
Chapter 2: Detailed analysis of Smart Wearable EEG Device manufacturers competitive landscape, price, sales and revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 5: Sales, revenue of Smart Wearable EEG Device in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.
Chapter 6: Sales, revenue of Smart Wearable EEG Device in country level. It provides sigmate data by Type, and by Application for each country/region.
Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.
Chapter 9: Conclusion.