เซนเซอร์ผิวหนัง 2020-2030: เทคโนโลยี ตลาด ผู้เล่น การคาดการณ์

เซนเซอร์สำหรับการวัดปริมาณของความชุ่มชื้นผิว, ริ้วรอย, ริ้วรอย, รูขุมขน, ความมัน, ความยืดหยุ่น ฯลฯ โอกาสในเครื่องสำอางและผลิตภัณฑ์ดูแลผิวรวมถึงสมาร์ทค้าปลีก, อีคอมเมิร์ซ, Hyper-personalization, ปริมาณตนเอง, ข้อมูลในโลกจริง และอื่น ๆ

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Skin sensors are routinely used in the cosmetics industry, playing essential roles in studies of safety and efficacy. However, despite the importance of and public focus on skin health and appearance, skin sensor technologies have rarely spilled over into wider use by the public. For example, though consumers moisturize their skin, and some even use anti-wrinkle cream, few people utilize moisture sensors to measure their skin hydration, nor do they measure changes in their wrinkles. With the shrinking of electronics and the advancement of smartphones and smartphone cameras, the availability of skin sensors is now spreading.
 
Digital disruption has reached the cosmetics industry, and companies are seeking ways to augment or even replace their retail counters with digital solutions. This process has been accelerated by the COVID-19 pandemic, which has already forced the closure of retailers, spas, etc. for several months. While online sales can bridge some of the gap, there is still a long way to go - traditionally, less than 10% of sales in the cosmetic industry come from online. To drive online sales, software services such as virtual try-on and skin analysis have been developed to provide similar education and product recommendation services of a brick and mortar store. Such technologies have been demonstrated to increase conversion rates and basket sizes.
 
 
Skin sensors for analysis of moisture, wrinkles, sebum, color, etc. can take many different forms such as cameras, probes, smart mirrors, films, facial imaging booths, smart phone accessories, and more.
 
In tandem with digitization comes the demand for personalization. Consumers are increasingly dissatisfied with existing skin analysis solutions and look to electronics, gadgets, and even genetic tests to provide quantifiable results using scientific measurements. Furthermore, an emerging trend is hyper-personalized skin care, which can range between bespoke bottles formulated for a specific person, daily customized skin care based on current skin condition and local weather, to 3D face masks that address specific problem areas on the face. Such products invariably rely on skin sensors to measure parameters such as skin moisture, wrinkles, sebum, elasticity, redness, dark spots, and more to provide the necessary data for personalization.
 
To stay ahead of the curve in the highly competitive cosmetics market, information and insights are required. Results gathered during clinical trials are difficult to replicate in the real world, and often lead to disappointed customers. Skin sensors play a crucial role here - both in helping the consumer quantify changes that are imperceptible to the naked eye, but also with the possibility of sending valuable data back into research and development for the next generation of products.
 
Technologies covered in this report
This report focuses on the skin parameters typically measured for the cosmetics industry and assesses the range of skin sensor technologies used to analyse them. Techniques range from gold standard techniques used in the laboratory to modifications used by companies to bring the technology to the consumer, to future skin sensors. IDTechEx has analyzed the technologies sued by over 36 players in the skin sensor market, focusing on the following parameters:
 
  • Skin hydration/moisture
  • Wrinkles, fine lines, pores
  • Sebum, including acne
  • Color, including dark spots, redness and overall skin tone
  • Skin elasticity/firmness
 
Technologies profiled in the report include:
 
  • Capacitance
  • 3D photography
  • UV light
  • Multispectral imaging
  • Genetic testing
 
While the report does not focus on medical applications, it does include a chapter on the emerging field of AI in skin cancer diagnosis.
 
Players, markets, and forecasts in this report
The report provides an overview of players in the skin sensors market and breaks down into target segments:
 
  • Research & development
  • Marketing in retail settings
  • Marketing in the consumer home
 
IDTechEx conducted primary research and profiled 16 companies developing skin sensors across the 3 applications. While R&D players stay comfortable in their niche with capability to deliver in retail settings, companies focusing on retail and consumer home settings are diversifying and creating innovative new technologies and business models.
 
With the changing landscape around the world, the market for skin sensors for the cosmetics industry is set to experience rapid growth in the next few years. This report presents a 10-year market forecast from 2020 to 2030 of the skin sensors in cosmetics market, with breakdown into R&D, marketing, and consumer applications.
Analyst access from IDTechEx
All report purchases include up to 30 minutes telephone time with an expert analyst who will help you link key findings in the report to the business issues you're addressing. This needs to be used within three months of purchasing the report.
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1.EXECUTIVE SUMMARY
1.1.Report Scope
1.2.Megatrends Driving Skin Sensor Technologies
1.3.Skin Sensor Devices Take Many Forms
1.4.Skin Parameters Analyzed
1.5.Technology Advancements and Trends
1.6.Deep learning (DL) makes automated image recognition possible
1.7.The Rise of Microbiome Research
1.8.Key Market Segments for Skin Sensor Technologies
1.9.Skin Sensors in Research & Development
1.10.Skin Sensors as a Marketing Tool
1.11.Skin Sensors for Consumers at Home
1.12.Marketing: Business Models
1.13.Beauty Tech at CES 2020
1.14.Market Forecast 2020 - 2030
1.15.Market Forecast: Marketing
2.INTRODUCTION
2.1.Report Scope
2.2.Skin Structure
2.3.Epidermis
2.4.Dermis
2.5.Skincare as Protection Against the Environment
2.6.Skincare in the Race Against Time
2.7.Upselling Through Personalization
2.8.Moving Sales Online
2.9.Megatrends Driving Skin Sensor Technologies
3.SKIN PARAMETERS AND MEASUREMENT TECHNIQUES
3.1.1.Chapter Overview
3.1.2.Skin Sensor Devices Take Many Forms
3.1.3.Image Requirements
3.1.4.Hydration/Moisture
3.1.5.Hydration: Capacitance
3.1.6.Hydration: Capacitance Examples
3.1.7.Hydration: Bioelectrical Impedance Analysis
3.1.8.Hydration: Players and Methods
3.1.9.Hydration: Discussion
3.1.10.Hydration: Examples of Optical Measurements
3.1.11.Wrinkles and Pores
3.1.12.Wrinkles and Pores: Parallel Polarized Light
3.1.13.Wrinkles and Pores: 3D Photography
3.1.14.Wrinkles and Pores: Image Analysis
3.1.15.Wrinkles and Pores: Players and Methods
3.1.16.Wrinkles and Pores: Discussion
3.1.17.Sebum
3.1.18.Sebum: Sebutape
3.1.19.Sebum: Examples of Film-Based Devices
3.1.20.Sebum: UV
3.1.21.Sebum: Other Optical Means
3.1.22.Sebum: Players and Methods
3.1.23.Color
3.1.24.Color: Multispectral Imaging
3.1.25.Color: White Light
3.1.26.Color: Canfield Scientific RBX Technology
3.1.27.Color: UV
3.1.28.Color: Example of Hyperspectral Imaging
3.1.29.Melanin: Players and Methods
3.1.30.Hemoglobin: Players and Methods
3.1.31.Color: Skin Tone
3.1.32.Elasticity/Firmness
3.1.33.Elasticity: Contact-Based Methods
3.1.34.Elasticity: Image-Based Method
3.1.35.Elasticity: Players and Methods
3.1.36.Other Common Parameters
3.2.Emerging Parameters in Skin Sensors
3.2.1.Genetic Testing
3.2.2.Genetic Testing: Categories
3.2.3.Genetic Testing: Players
3.2.4.Microbiome
3.2.5.The Rise of Microbiome Research
3.2.6.Skin Sensor Technologies: Summary and Outlook
3.3.Artificial Intelligence
3.3.1.What is artificial intelligence (AI)? Terminologies explained
3.3.2.Algorithm training process in a single layer
3.3.3.Towards deep learning by deepening the neutral network
3.3.4.Deep learning (DL) makes automated image recognition possible
3.3.5.Image recognition AI is based on convolutional neural networks (CNNs)
3.3.6.AI - Disrupting Skin Cancer Detection
3.3.7.Skin cancer
3.3.8.Skin cancer: Key players
3.3.9.Skin cancer: Machine learning algorithms
3.3.10.Skin cancer: The ABCDE criteria
3.3.11.Skin cancer: Dermoscopic melanoma recognition (2018)
3.3.12.Skin cancer: Dermoscopic melanoma recognition and its challenges
3.3.13.Skin cancer: SkinVision
3.3.14.Skin cancer: MetaOptima
3.3.15.Skin cancer detection AI: Performance comparison
3.4.Skin Sensors for Advanced Wound Care
3.4.1.Trends in Wound Monitoring
3.4.2.Bacterial Detection: Point-of-Care Visualization
3.4.3.Bacterial Detection: Rapid Diagnostics
3.4.4.Hyperspectral Technology: HyperMed
3.4.5.Near-Infrared: Kent Imaging
3.4.6.Thermography: WoundVision
3.4.7.Bioimpedance: Bruin Biometrics
3.4.8.3D Imaging: Infrared from Tablets
3.4.9.3D Imaging: Imaging in Stereo
3.4.10.3D Imaging: Point Tracking
3.4.11.3D Imaging: Laser Lines
3.4.12.Smartphone Apps
3.4.13.Smartphone Apps: Swift Medical
3.4.14.Trends in Wound Monitoring
3.4.15.Relationship with Cosmetics Industry
4.MARKET ANALYSIS AND COMPANY PROFILES
4.1.Key Market Segments
4.2.Players and Market Segments
4.3.Skin Sensors in Research & Development
4.4.Research & Development: Key Players
4.5.Courage + Khazaka Electronic
4.6.Cortex Technology
4.7.Miravex
4.8.Miravex: Antera 3D
4.9.Research & Development: Business Models
4.10.Skin Sensors as a Marketing Tool
4.11.Marketing - High end players
4.12.Facial Imaging
4.13.PIE
4.14.Skin Sensors for Consumers at Home
4.15.Improvements in Cameras and Phones Critical for Success
4.16.Skin Sensors Drives Ecommerce
4.17.FitSkin
4.18.Skin Sensors Benefit All
4.19.Cutitronics
4.20.Haut.AI
4.21.Sequential Skin
4.22.Marketing: Business Models
4.23.Skin Sensor Technologies and the Subscription Model
4.24.How Have Brands Responded?
4.25.CES 2020
4.26.Beauty Tech at CES 2020
4.27.HiMirror
4.28.HiMirror: HiMirror Slide
4.29.lululab
4.30.lululab: Lumini Home
4.31.Revieve
4.32.Revieve: Partnership with CareOS
4.33.Perfect Corp
4.34.Procter and Gamble: Opté
4.35.L'Oréal: Perso
5.MARKET FORECASTS
5.1.Methodology
5.2.Market Forecast 2020 - 2030
5.3.Market Forecast: Research & Development
5.4.Market Forecast: Marketing
5.5.Market Forecast: Consumers
 

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