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市場調查報告書

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1824163

情感運算市場：2025-2030 年預測

Global Affective Computing Market - Forecasts from 2025 to 2030

出版日期: 2025年08月23日 | 出版商:

Knowledge Sourcing Intelligence | 英文 149 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

情感運算市場規模

情感運算市場預計將從 2025 年的 763.1 億美元成長到 2030 年的 1,921.89 億美元，複合年成長率為 20.29%。

情感運算是電腦科學、心理學和認知科學的跨學科融合，致力於開發能夠分析、處理和回應人類情感的系統。這項技術也稱為人工智慧，它建立智慧運算系統，透過即時檢測和回應非語言情緒訊號（例如手勢、生理反應和行為模式）來增強人機互動。

技術基礎設施和市場動態

此領域涵蓋超越傳統人機互動範式的全面情緒辨識能力。情感運算系統能夠跨越多種模態偵測和解讀情緒狀態，使機器能夠對人類的情緒情境做出適當的反應，或刻意影響情緒狀態。

這個快速發展的跨學科領域研究技術如何促進人類情感理解，情緒狀態如何影響人機交互，以及系統如何利用情緒訊息來提升其運作能力。該技術透過複雜的感知和情感響應策略，檢驗人機交互，從而創造更直覺、響應更靈敏的技術環境。

市場擴張反映出各行各業對能夠處理詐欺偵測和增強安全性的虛擬助理的需求日益成長。情感運算擴大支持安全實現，例如透過情緒和行為模式識別來限制授權使用者存取的聲控生物識別系統。

主要成長要素

強化情感溝通體系

根本的市場驅動力源自於情感運算的架構能力，它能夠促進人機之間的情感交流。雖然人類天生就能交流情感，但機器需要先進的運算能力才能從發送者和接收者的觀點識別和解讀這些情感訊號。

各種組織正在開發工具，使機器能夠識別情緒交流的模式，從而使人類更有意識地表達情緒。目前的自動偵測系統能夠透過生理通道辨識多種人類情緒，而情感運算系統則透過使用者輸入中斷機制來運作。

多模態情感交流是一個積極發展的領域，組織正在探索整合多種感官輸入的綜合情感識別系統，以提高準確性和可靠性。

醫療產業應用

醫療保健領域代表了情感運算最先進和最具商業性可行性的應用，早期的創新旨在協助醫療保健專業人員，特別是支持與智慧障礙和有特殊護理需求的患者的溝通。

人工智慧與醫療保健的融合正在推動重大發展，各大公司正致力於擴大人工智慧在醫療保健服務中的貢獻。先進的病患監測系統採用臉部編碼演算法進行持續患者觀察，為醫療專業人員提供即時情緒和行為洞察。

然而，醫療保健行業的採用需要比其他行業更長的核准後流程，這可能會延遲新技術在零售市場的可用性，儘管它具有臨床療效。

研發投入

持續的研發投入，支撐著輔助個人（尤其是社交和情緒技能嚴重受損者）的科技市場不斷成長。電腦能夠傳遞非語言的情緒訊息，創造溝通機會，從而平衡殘障人士和神經病變人士的互動能力。

利用先進的情感人工智慧技術，各公司正在開發幫助自閉症兒童學習情緒表達識別和情境情緒映射的方法。這些先進的開發工具有助於培養社交情緒技能，同時拓展情感運算市場的用例。

市場限制與技術挑戰

機器學習和建模的局限性

模型建構過程提出了與人工智慧系統中的情緒映射相關的一個關鍵挑戰：大多數可用數據來自人工實驗室環境，限制了我們對情緒對現實世界應用中的決策和行為的影響的理解。

持續進行的情緒影響調節過程的研究和開發，為有效的人工情緒智慧系統的開發帶來了不確定性。組織在開發實用的情感運算解決方案時，必須應對這些基本的建模挑戰。

情緒模式辨識涉及複雜的機器學習，需要複雜的演算法來解釋不同環境和文化背景下人類情緒表達的細微差別。

戰略市場展望

情感運算市場正處於人工智慧技術發展與情感識別技術系統日益成長的需求的交匯點。要想取得成功，需要在複雜的情感識別能力與實際實施挑戰之間取得平衡，同時滿足日益擴張的全球市場中醫療保健、安全和人機互動應用的需求。

本報告的主要優點

深刻分析：獲得深入的市場洞察，重點關注客戶細分、政府政策和社會經濟因素、消費者偏好、垂直行業和其他細分市場，涵蓋主要地區和新興地區。
競爭格局：了解主要企業所採用的策略策略，並了解正確策略的市場滲透潛力。
市場促進因素和未來趨勢：探索動態因素和關鍵市場趨勢以及它們將如何影響未來的市場發展。
可行的建議：利用洞察力來制定策略決策，在動態環境中開闢新的業務流和收益。
受眾廣泛：對於新興企業、研究機構、顧問、中小企業和大型企業來說，既有利又划算。

它有什麼用途？

產業與市場洞察、商業機會評估、產品需求預測、打入市場策略、地理擴張、資本投資決策、法律規範與影響、新產品開發、競爭影響

分析範圍

歷史資料（2022-2024）和預測資料（2025-2030）
成長機會、挑戰、供應鏈前景、法規結構、客戶行為和趨勢分析
競爭對手定位、策略和市場佔有率分析
按部門和地區（國家）分類的收益成長和預測分析
公司概況（策略、產品、財務資訊、主要趨勢等）

介紹
北美洲
- 依技術
- 按硬體
- 按最終用戶產業
- 按國家
  - 美國
  - 加拿大
  - 墨西哥
南美洲
- 依技術
- 按硬體
- 按最終用戶產業
- 按國家
  - 巴西
  - 阿根廷
  - 其他
歐洲
- 依技術
- 按硬體
- 按最終用戶產業
- 按國家
  - 英國
  - 德國
  - 法國
  - 西班牙
  - 其他
中東和非洲
- 依技術
- 按硬體
- 按最終用戶產業
- 按國家
  - 沙烏地阿拉伯
  - 阿拉伯聯合大公國
  - 其他
亞太地區
- 依技術
- 按硬體
- 按最終用戶產業
- 按國家
  - 中國
  - 日本
  - 印度
  - 韓國
  - 台灣
  - 其他

第9章競爭格局及分析

主要企業和策略分析
市佔率分析
企業合併、協議、商業合作
競爭對手儀表板

第10章：公司簡介

Smart Eye AB
Realeyes
nViso SA
Microsoft Corporation
Intel Corporation
Qualcomm Technologies, Inc.
Kairos

第11章附錄

貨幣
先決條件
基準年和預測年時間表
相關人員的主要利益
分析方法
簡稱

圖表列表

表格列表

簡介目錄

Product Code: KSI061610583

Affective Computing Market Size:

The Affective Computing Market is expected to grow from USD 76.310 billion in 2025 to USD 192.189 billion in 2030, at a CAGR of 20.29%.

Affective computing represents a multidisciplinary convergence of computer science, psychology, and cognitive science focused on developing systems capable of analyzing, processing, and responding to human emotions. Also known as artificial emotional intelligence, this technology creates intelligent computational systems that enhance human-machine interaction through real-time detection and response to nonverbal emotional signals including gestures, physiological responses, and behavioral patterns.

Technology Foundation and Market Dynamics

The field encompasses comprehensive emotion recognition capabilities that extend beyond traditional human-computer interaction paradigms. Affective computing systems detect and interpret emotional states through multiple modalities, enabling machines to respond appropriately to human emotional contexts and potentially influence mood states deliberately.

This rapidly expanding interdisciplinary domain examines how technology facilitates human affect understanding, how emotional states influence human-technology interactions, and how systems can leverage emotional information to enhance operational capabilities. The technology transforms human-computer interaction through sophisticated sensing and affective response strategies that create more intuitive and responsive technological environments.

Market expansion reflects growing demand for virtual assistants capable of fraud detection and enhanced security applications across various industries. Affective computing increasingly supports security implementations including voice-activated biometric systems that restrict access to authorized users through emotional and behavioral pattern recognition.

Primary Growth Drivers

Enhanced Emotional Communication Systems

A fundamental market driver stems from affective computing's structural capability to facilitate emotional communication between humans and machines. While humans naturally convey emotions, machines require sophisticated computational power to recognize and interpret these emotional signals from both sender and receiver perspectives.

Various organizations develop tools enabling more deliberate human emotional expression while allowing machines to identify patterns in emotional communication. Current automatic detection systems achieve identification rates for distinguishing multiple human emotions through physiological channels, with affective computing systems operating through user input interruption mechanisms.

Multi-modal emotional communication represents an active development area where organizations explore comprehensive emotional recognition systems that integrate multiple sensory inputs for enhanced accuracy and reliability.

Healthcare Industry Applications

The healthcare sector demonstrates some of the most advanced and commercially viable affective computing applications. Early innovations target medical personnel assistance, particularly technologies supporting communication with mentally challenged individuals and patients requiring specialized care.

Artificial intelligence integration in medicine drives significant development efforts, with companies focusing on expanding AI contributions to healthcare delivery. Advanced patient monitoring systems employ facial coding algorithms for continuous patient observation, providing healthcare professionals with real-time emotional and behavioral insights.

However, healthcare sector implementation faces extended post-approval processes compared to other industries, potentially delaying retail market availability of new technologies despite their clinical effectiveness.

Research and Development Investment

Substantial ongoing investment in research and development supports market expansion, particularly for technologies assisting individuals with significantly impaired social-emotional skills. Computers enable nonverbal emotional information transfer, creating communication opportunities that level interaction capabilities between neurotypical and neurodiverse individuals.

Companies develop methodologies helping children with autism learn emotional expression recognition and situational emotional mapping through advanced emotion AI technologies. These sophisticated development tools contribute to social-emotional skill building while expanding affective computing market applications.

Market Constraints and Technical Challenges

Machine Learning and Modeling Limitations

Model-building processes present significant challenges related to emotional mapping in artificial intelligence systems. Most available data originates from artificial laboratory settings, creating limitations in understanding emotion's impact on decision-making and behavior in real-world applications.

Ongoing research debates regarding processes that mediate emotional impacts create uncertainty in developing effective artificial emotional intelligence systems. Organizations must address these fundamental modeling challenges while developing practical affective computing solutions.

Machine learning complexities associated with emotional pattern recognition require sophisticated algorithms capable of interpreting nuanced human emotional expressions across diverse contexts and cultural backgrounds.

Strategic Market Outlook

The affective computing market operates at the intersection of advancing AI capabilities and growing demand for emotion-aware technology systems. Success requires balancing sophisticated emotional recognition capabilities with practical implementation challenges while addressing healthcare, security, and human-computer interaction applications across expanding global markets.

Key Benefits of this Report:

Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, and other sub-segments.
Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape future market developments.
Actionable Recommendations: Utilize the insights to exercise strategic decisions to uncover new business streams and revenues in a dynamic environment.
Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

Historical data from 2022 to 2024 & forecast data from 2025 to 2030
Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, and Trend Analysis
Competitive Positioning, Strategies, and Market Share Analysis
Revenue Growth and Forecast Assessment of segments and regions including countries
Company Profiling (Strategies, Products, Financial Information, and Key Developments among others.

Segmentation

By Technology

Touch-Based Affective Computing
Touchless Affective Computing

By Hardware

Sensors
Cameras
Storage Devices & Processors
Wearable Devices
Others

By End-User Industry

Healthcare
Media & Entertainment
Government & Defense
Communication & Technology
Leisure & Hospitality
Automotive
Others

By Geography

North America
USA
Canada
Mexico
South America
Brazil
Argentina
Others
Europe
United Kingdom
Germany
France
Spain
Others
Middle East and Africa
Saudi Arabia
UAE
Others
Asia Pacific
China
Japan
India
South Korea
Taiwan
Others

1. EXECUTIVE SUMMARY

2. MARKET SNAPSHOT

2.1. Market Overview
2.2. Market Definition
2.3. Scope of the Study
2.4. Market Segmentation

3. BUSINESS LANDSCAPE

3.1. Market Drivers
3.2. Market Restraints
3.3. Market Opportunities
3.4. Porter's Five Forces Analysis
3.5. Industry Value Chain Analysis
3.6. Policies and Regulations
3.7. Strategic Recommendations

4. TECHNOLOGICAL OUTLOOK

5. GLOBAL AFFECTIVE COMPUTING MARKET BY TECHNOLOGY

5.1. Introduction
5.2. Touch-Based Affective Computing
5.3. Touchless Affective Computing

6. GLOBAL AFFECTIVE COMPUTING MARKET BY HARDWARE

6.1. Introduction
6.2. Sensors
6.3. Cameras
6.4. Storage Devices & Processors
6.5. Wearable Devices
6.6. Others

7. GLOBAL AFFECTIVE COMPUTING MARKET BY END-USER INDUSTRY

7.1. Introduction
7.2. Healthcare
7.3. Media & Entertainment
7.4. Government & Defense
7.5. Communication & Technology
7.6. Leisure & Hospitality
7.7. Automotive
7.8. Others

8. GLOBAL AFFECTIVE COMPUTING MARKET BY GEOGRAPHY

8.1. Introduction
8.2. North America
- 8.2.1. By Technology
- 8.2.2. By Hardware
- 8.2.3. By End-User Industry
- 8.2.4. By Country
  - 8.2.4.1. USA
  - 8.2.4.2. Canada
  - 8.2.4.3. Mexico
8.3. South America
- 8.3.1. By Technology
- 8.3.2. By Hardware
- 8.3.3. By End-User Industry
- 8.3.4. By Country
  - 8.3.4.1. Brazil
  - 8.3.4.2. Argentina
  - 8.3.4.3. Others
8.4. Europe
- 8.4.1. By Technology
- 8.4.2. By Hardware
- 8.4.3. By End-User Industry
- 8.4.4. By Country
  - 8.4.4.1. United Kingdom
  - 8.4.4.2. Germany
  - 8.4.4.3. France
  - 8.4.4.4. Spain
  - 8.4.4.5. Others
8.5. Middle East and Africa
- 8.5.1. By Technology
- 8.5.2. By Hardware
- 8.5.3. By End-User Industry
- 8.5.4. By Country
  - 8.5.4.1. Saudi Arabia
  - 8.5.4.2. UAE
  - 8.5.4.3. Others
8.6. Asia Pacific
- 8.6.1. By Technology
- 8.6.2. By Hardware
- 8.6.3. By End-User Industry
- 8.6.4. By Country
  - 8.6.4.1. China
  - 8.6.4.2. Japan
  - 8.6.4.3. India
  - 8.6.4.4. South Korea
  - 8.6.4.5. Taiwan
  - 8.6.4.6. Others