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市场调查报告书
商品编码
1824163

情感运算市场：2025-2030 年预测

Global Affective Computing Market - Forecasts from 2025 to 2030
出版日期: | 出版商: Knowledge Sourcing Intelligence | 英文 149 Pages | 商品交期: 最快1-2个工作天内

价格
简介目录

情感运算市场规模

情感运算市场预计将从 2025 年的 763.1 亿美元成长到 2030 年的 1,921.89 亿美元，复合年增长率为 20.29%。

情感运算是电脑科学、心理学和认知科学的跨学科融合，致力于开发能够分析、处理和回应人类情感的系统。这项技术也称为人工智慧，它建立智慧运算系统，透过即时检测和回应非语言情绪讯号（例如手势、生理反应和行为模式）来增强人机互动。

技术基础设施和市场动态

此领域涵盖超越传统人机互动范式的全面情绪辨识能力。情感运算系统能够跨越多种模态侦测和解读情绪状态，使机器能够对人类的情绪情境做出适当的反应，或刻意影响情绪状态。

这个快速发展的跨学科领域研究技术如何促进人类情感理解，情绪状态如何影响人机交互，以及系统如何利用情绪讯息来提升其运作能力。该技术透过复杂的感知和情感响应策略，检验人机交互，从而创造更直观、响应更灵敏的技术环境。

市场扩张反映出各行各业对能够处理诈欺侦测和增强安全性的虚拟助理的需求日益增长。情感运算越来越多地支持安全实现，例如透过情绪和行为模式识别来限制授权使用者存取的声控生物识别系统。

主要成长要素

强化情感沟通体系

根本的市场驱动力源自于情感运算的架构能力，它能够促进人机之间的情感交流。虽然人类天生就能交流情感，但机器需要先进的运算能力才能从发送者和接收者的观点识别和解读这些情感讯号。

各种组织正在开发工具，使机器能够识别情绪交流的模式，从而使人类更有意识地表达情绪。目前的自动侦测系统能够透过生理通道辨识多种人类情绪，而情感运算系统则透过使用者输入中断机制来运作。

多模态情感交流是一个积极发展的领域，组织正在探索整合多种感官输入的综合情感识别系统，以提高准确性和可靠性。

医疗产业应用

医疗保健领域代表了情感运算最先进和最具商业性可行性的应用，早期的创新旨在协助医疗保健专业人员，特别是支持与智能障碍和有特殊护理需求的患者的沟通。

人工智慧与医疗保健的融合正在推动重大发展，各大公司正致力于扩大人工智慧在医疗保健服务中的贡献。先进的病患监测系统采用脸部编码演算法进行持续患者观察，为医疗专业人员提供即时情绪和行为洞察。

然而，医疗保健行业的采用需要比其他行业更长的核准后流程，这可能会延迟新技术在零售市场的可用性，儘管它具有临床疗效。

研发投入

持续的研发投入，支撑着辅助个人（尤其是社交和情绪技能严重受损者）的科技市场不断成长。电脑能够传递非语言的情绪讯息，创造沟通机会，从而平衡残障人士和神经病变人士的互动能力。

利用先进的情感人工智慧技术，各公司正在开发帮助自闭症儿童学习情绪表达识别和情境情绪映射的方法。这些先进的开发工具有助于培养社交情绪技能，同时拓展情感运算市场的用例。

市场限制与技术挑战

机器学习和建模的局限性

模型建构过程提出了与人工智慧系统中的情绪映射相关的一个关键挑战：大多数可用数据来自人工实验室环境，限制了我们对情绪对现实世界应用中的决策和行为的影响的理解。

持续进行的情绪影响调节过程的研究和开发，为有效的人工情绪智慧系统的开发带来了不确定性。组织在开发实用的情感运算解决方案时，必须应对这些基本的建模挑战。

情绪模式辨识涉及复杂的机器学习，需要复杂的演算法来解释不同环境和文化背景下人类情绪表达的细微差别。

战略市场展望

情感运算市场正处于人工智慧技术发展与情感识别技术系统日益增长的需求的交汇点。要想取得成功，需要在复杂的情感识别能力与实际实施挑战之间取得平衡，同时满足日益扩张的全球市场中医疗保健、安全和人机互动应用的需求。

本报告的主要优点

  • 深刻分析：获得深入的市场洞察，重点关注客户细分、政府政策和社会经济因素、消费者偏好、垂直行业和其他细分市场，涵盖主要地区和新兴地区。
  • 竞争格局：了解主要企业所采用的策略策略，并了解正确策略的市场渗透潜力。
  • 市场驱动因素和未来趋势：探索动态因素和关键市场趋势以及它们将如何影响未来的市场发展。
  • 可行的建议：利用洞察力来制定策略决策，在动态环境中开闢新的业务流和收益。
  • 受众广泛：对于新兴企业、研究机构、顾问、中小企业和大型企业来说，既有利又划算。

它有什么用途？

产业与市场洞察、商业机会评估、产品需求预测、打入市场策略、地理扩张、资本投资决策、法律规范与影响、新产品开发、竞争影响

分析范围

  • 历史资料（2022-2024）和预测资料（2025-2030）
  • 成长机会、挑战、供应链前景、法规结构、客户行为和趋势分析
  • 竞争对手定位、策略和市场占有率分析
  • 按部门和地区（国家）分類的收益成长和预测分析
  • 公司概况（策略、产品、财务资讯、主要趋势等）

目录

第一章执行摘要

第二章市场概述

  • 市场概况
  • 市场定义
  • 分析范围
  • 细分市场

第三章 经营状况

  • 市场驱动因素
  • 市场限制
  • 市场机会
  • 波特五力分析
  • 产业价值链分析
  • 政策法规
  • 策略建议

第四章 技术展望

第五章 全球情感运算市场（按技术）

  • 介绍
  • 基于触觉的情感运算
  • 非接触式情感运算

第六章 全球情感运算市场（以硬体计算）

  • 介绍
  • 感应器
  • 相机
  • 储存设备和处理器
  • 穿戴式装置
  • 其他的

第七章全球情感运算市场（依最终使用者垂直划分）

  • 介绍
  • 医疗保健
  • 媒体与娱乐
  • 政府/国防
  • 通讯和技术
  • 休閒与饭店
  • 车
  • 其他的

第八章全球情感运算市场（按地区）

  • 介绍
  • 北美洲
    • 依技术
    • 按硬体
    • 按最终用户产业
    • 按国家
      • 美国
      • 加拿大
      • 墨西哥
  • 南美洲
    • 依技术
    • 按硬体
    • 按最终用户产业
    • 按国家
      • 巴西
      • 阿根廷
      • 其他的
  • 欧洲
    • 依技术
    • 按硬体
    • 按最终用户产业
    • 按国家
      • 英国
      • 德国
      • 法国
      • 西班牙
      • 其他的
  • 中东和非洲
    • 依技术
    • 按硬体
    • 按最终用户产业
    • 按国家
      • 沙乌地阿拉伯
      • 阿拉伯聯合大公国
      • 其他的
  • 亚太地区
    • 依技术
    • 按硬体
    • 按最终用户产业
    • 按国家
      • 中国
      • 日本
      • 印度
      • 韩国
      • 台湾
      • 其他的

第九章竞争格局及分析

  • 主要企业和策略分析
  • 市占率分析
  • 企业合併、协议、商业合作
  • 竞争对手仪表板

第十章：公司简介

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

第十一章 附录

  • 货币
  • 先决条件
  • 基准年和预测年时间表
  • 相关人员的主要利益
  • 分析方法
  • 简称

图表列表

表格列表

简介目录
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

TABLE OF CONTENTS

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

9. COMPETITIVE ENVIRONMENT AND ANALYSIS

  • 9.1. Major Players and Strategy Analysis
  • 9.2. Market Share Analysis
  • 9.3. Mergers, Acquisitions, Agreements, and Collaborations
  • 9.4. Competitive Dashboard

10. COMPANY PROFILES

  • 10.1. Smart Eye AB
  • 10.2. Realeyes
  • 10.3. nViso SA
  • 10.4. Microsoft Corporation
  • 10.5. Intel Corporation
  • 10.6. Qualcomm Technologies, Inc.
  • 10.7. Kairos

11. APPENDIX

  • 11.1. Currency
  • 11.2. Assumptions
  • 11.3. Base and Forecast Years Timeline
  • 11.4. Key benefits for the stakeholders
  • 11.5. Research Methodology
  • 11.6. Abbreviations

LIST OF FIGURES

LIST OF TABLES