Owing to this, various vendors in the market are increasingly launching several forms of API that are related to emotion detection and analysis, even from key vendors such as Google, Microsoft, and Amazon. Furthermore, the launch of multi-modal solutions, which include the integration of speech, text, and facial recognition and increasing the role of muscle activity, brain activity, skin conductance, and hear t rate monitoring to deliver better emotional intelligence of the human has significantly led to huge customer awareness about the technology. Key areas where emotion detection and recognition are expected to gain traction include: entertainment (majorly gaming), transpor tation (autonomous cars), healthcare (various kinds of diagnostics), and retail (to enhance customer experience). For instance, recently Holst Centre (in the Netherlands) launched the prototype of a new electroencephalogram (EEG) headset, which is intended to measure cognitive processes in the brain and emotions. This headset can be used for gaming, learning, and therapeutic applications. The automotive industry is expected to be another major adopter of the technology over the coming years. With the advent of autonomous cars, ADAS, and connected cars, the incorporation of IoT and sensors is on the rise; automotive vendors are expected to incorporate EDR primarily for safety.

1. INTRODUCTION

2. RESEARCH METHODOLOGY

3. EXECUTIVE SUMMARY

4. MARKET INSIGHT

5. MARKET DYNAMICS

6. MARKET SEGMENTATION

7. KEY VENDOR PROFILES

8. INVESTMENT ANALYSIS

9. MARKET OPPORTUNITIES AND FUTURE TRENDS