Chat with us, powered by LiveChat ウエアラブルセンサー 2021-2031年: IDTechEx

ウエアラブルセンサー 2021-2031年: IDTechEx

ウェアラブルセンサーの市場が2025年までに年間50億ドルを超える規模に

ウエアラブルセンサー 2021-2031年

技術、有力企業および市場見通しを含む世界の業界展望に関する包括的な調査


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このレポートは、今日のウェアラブルデバイスにおいて利用されているあらゆるタイプのセンサー技術に関する包括的な概要を提供しています。またウェアラブルのハードウェアに着目した10年に及ぶ調査に基づき、現在および将来の技術の選択肢、今日の各種センサーの商業的展望、ならびにそれぞれのタイプのセンサーや最終市場に従事する有力企業を網羅しています。
IDTechExの調査レポート『ウエアラブルセンサー 2021-2031年』では、ウェアラブル電子製品に使用されるセンサーの技術、市場動向、競合状況を包括的に解説しています。このレポートは、IDTechExのアナリストチームが5年以上の調査を経てまとめたもので、多くの関連技術と市場分野における並行した専門知識を活用しています。レポートでは、業界の状況を特徴づける10の主要なカテゴリーにまたがる17種類のセンサーをカバーしています。また、バリューチェーン全体から50社以上のキープレイヤーとの一次コンテンツ(インタビュー、写真、訪問など)を含め、100社以上の企業の活動を解説しています。最後に、本レポートでは、50種類以上の異なるウェアラブル技術製品タイプに対するIDTechExの並行予測に加えて、インタビュー、照合された財務統計、業界動向から得られた独自の一次データを活用して、各タイプのウエアラブルセンサーの詳細な定量的な市場予測を提供しています。
 
多くのウエアラブル電子製品の中で、重要な価値提案を提供するのはセンサーです。例えば、スマートウォッチやフィットネス・トラッキングは、フィットネス・トラッキングと活動データの提供を中心に構築されており、徐々にメディカルとの関連性の高いメトリクスへと移行しています。仮想、拡張、複合現実デバイス(VR、AR、MR)は、ユーザーがコンテンツや環境と対話できるようにするために、カメラ、慣性計測装置、深度センサー、圧力センサーなどを組み合わせた一連のセンサーに依存しています。電子皮膚パッチ、ヒアラブル、スマート衣料、その他の関連製品でも同様です。それぞれが製品機能の重要な部分として身体や周囲の環境とのインターフェースが可能な一連のコアセンサーに依存しています。
 
IDTechEx's research in wearables tracks the progress of over 50 wearable electronic product types. Within each of these products, a key focus of the research is in understanding and characterising the core hardware behind the products, with sensors as a key part (alongside energy storage, communications, and other essential features). This report looks at the key sensor components in each of these wearable product categories, focusing on 17 different sensor types. The combination of the detailed wearable product forecasting and understanding of the sensor landscape and suppliers enables very detailed forecasting for wearable sensors, in terms of revenue, pricing, and volume, with historic data from 2010-2019 and forecasts from 2020-2031.
 
 
IDTechEx forecast for the wearable sensor market in 2022. Source: IDTechEx report: Wearable Sensors 2021-2031
IDTechEx describes the wearable sensors market in three waves. This idea, coined back in 2016, has stood the test of time and remains true to this day. The first wave includes sensors that have been incorporated in wearables for many years, often being originally developed for wearable products over previous decades. A second wave of wearable sensors came following huge technology investment in smartphones. Many of the sensors from smartphones could be easily adapted for use in wearable products; they could be "made-wearable". Finally, with the growing maturity of the wearable technology market over the past decades, many sensors are now designed from the ground up with wearable products in mind. Many of these "made-for-wearable" sensors are already well established in the market today, with more generations of new sensors being commercialised to fuel the next generations of wearable products.
 
 
Wearable sensors in three waves. Source: IDTechEx Report: Wearable Sensors 2021-2031
The wearable technology market was worth nearly $70bn in 2019, having doubled in size since 2014. Sensors have provided the core features for many of these different products throughout this rise, and they will continue to be critical into future generations of products. The COVID-19 pandemic in 2020 has brought additional focus to sensors, including tracking early onset of conditions, facilitation of wearables for contact tracing, and remote patient monitoring for patients in isolation. Parallel trends see smartwatches driving towards medical metrics, hearables adding more sophisticated sensor options, skin patches successfully commercialising in new applications and many industrial, military and security applications maturing. As such, wearable sensors remain a fundamental enabling component for the entire wearable technology industry, and obtaining a clear understanding of their capabilities and potential is essential for any player within the entire value chain.
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アイディーテックエックス株式会社 (IDTechEx日本法人)
担当: 村越美和子 m.murakoshi@idtechex.com
Table of Contents
1.EXECUTIVE SUMMARY
1.1.Introduction to wearable sensors
1.2.Sensors enable key product value propositions
1.3.10 major wearable sensor categories (by function)
1.4.17 types of wearable sensor used today
1.5.Wearable sensors in three waves
1.6.The first wave: "The originals"
1.7.The second wave: "Made-wearable" sensors
1.8.The third wave: "Made-for-wearable" sensors
1.9.Historic data (2010-2020): Wearable sensors (revenue)
1.10.Market forecast (2021-2031): Wearable sensors (revenue)
2.INTRODUCTION
2.1.Origins and early potential in wearables
2.2.Shifting hype in wearables as markets evolve
2.3.Key metrics for wearables: Search terms
2.4.Key metrics for wearables: Funding trends
2.5.Key metrics for wearables: Patent trends
2.6.Historic market data by sector
2.7.Wearables in 2020
2.8.Sensors enable key product value propositions
2.9.Definitions
2.10.Common wearable sensors deployed today
2.11.Sensors on the body: what do we want to measure?
2.12.Appropriate data for the desired outcome
2.13.Appropriate data: Example
2.14.Example: effort and reward in heart monitoring
2.15.Example: Useful data at different levels of inference
2.16.Sensor fusion is essential and expected
2.17.Different product types from the same sensors
2.18.Wider industry context for each sensor type
2.19.Wearable sensors in three waves
3.SENSOR TYPES
3.1.Inertial measurement units
3.1.1.IMUs - Introduction
3.1.2.MEMS - Background
3.1.3.MEMS - Manufacturing techniques
3.1.4.MEMS - Becoming a commodity
3.1.5.MEMS Accelerometers
3.1.6.MEMS Gyroscopes
3.1.7.Digital compasses
3.1.8.Magnetometer types
3.1.9.Magnetometer types (figure)
3.1.10.Magnetometer suppliers and industry dynamic
3.1.11.Magnetometer suppliers by type
3.1.12.MEMS Barometers
3.1.13.Pressure sensors in wearable devices
3.1.14.Example: Interview with Bosch Sensortec
3.1.15.Limitations and common errors with MEMS sensors
3.1.16.MEMS manufacturers: characteristics and examples
3.1.17.Case study: ST Microelectronics
3.1.18.Case study: InvenSense
3.1.19.Apple: iPhone sensor choice case study
3.1.20.Conclusion: IMUs are here to stay, with some limitations
3.2.Optical sensors
3.2.1.Optical sensors - introduction
3.2.2.Optical sensors - Heart rate
3.2.3.Photoplethysmography (PPG) - Basic background
3.2.4.Transmission and reflectance
3.2.5.Reflectance-mode PPG for fitness wearables
3.2.6.Key players
3.2.7.Valencell
3.2.8.Valencell - more product examples
3.2.9.Well Being Digital Ltd. (WBD101)
3.2.10.CSEM
3.2.11.Philips
3.2.12.cosinuss°
3.2.13.APM
3.2.14.Georgia Tech
3.2.15.Optical sensors - Pulse oximetry and other cardiac metrics
3.2.16.Wearable pulse oximetry via a smartwatch
3.2.17.Smartwatch pulse oximetry: Examples
3.2.18.Examples: Garmin
3.2.19.Medical device examples: Oxitone
3.2.20.How pulse oximetry data is used
3.2.21.Other related approaches
3.2.22.Reveal Biosensors
3.3.3D imaging and depth sensors
3.3.1.3D imaging and motion capture
3.3.2.Application example: Motion capture in animation
3.3.3.Stereoscopic vision
3.3.4.Time of flight
3.3.5.Structured light
3.3.6.Comparison of 3D imaging technologies
3.3.7.Example: Leap Motion (now Ultraleap)
3.3.8.Example: Microsoft; from Kinect to Hololens
3.3.9.Example: Intel's RealSense™
3.3.10.Example: Occipital
3.3.11.Commercial 3D camera examples
3.4.Wearable Cameras
3.4.1.Cameras in wearable devices
3.4.2.Established players exploiting profitable niches
3.4.3.Applications in safety and security
3.4.4.Other applications: Enhancing sports media
3.4.5.Cameras in smartwatches?
3.4.6.Social applications: drivers and challenges
3.4.7.Example: Spectacles by Snap Inc.
3.4.8.Other applications: Automatic digital diary
3.5.Optical sensors - other examples
3.5.1.Optical chemical sensors
3.5.2.Example - Delektre
3.5.3.Implantable optical glucose sensors
3.5.4.Optical method for non-invasive glucose sensing
3.5.5.Start-up example: eLutions
3.5.6.Related platform: UV exposure indicators
3.5.7.Speech recognition using lasers - VocalZoom
3.5.8.Infrared spectroscopy
3.5.9.Example: Temperature from NIR spectroscopy
3.5.10.Example: Alcohol detection by NIR spectroscopy
3.5.11.Example: Lactate detection by NIR spectroscopy
3.5.12.Example: Body hydration
3.6.Electrodes
3.6.1.Introduction
3.6.2.Applications and product types
3.6.3.Biopotential - ECG, EEG, EMG
3.6.4.Introduction - Measuring biopotential
3.6.5.Introduction - The circuitry for measuring biopotential
3.6.6.Introduction - Electrocardiography (ECG, or EKG)
3.6.7.Examples - devices for cardiac monitoring
3.6.8.Introduction - Electroencephalography (EEG)
3.6.9.Examples - Consumer EEG products and prototypes
3.6.10.Introduction - Electromyography (EMG)
3.6.11.Examples - Consumer EMG products and prototypes
3.6.12.Bioimpedance / skin conductance
3.6.13.Introduction - Bioimpedance
3.6.14.Technology overview - Galvanic skin response (GSR)
3.6.15.Device examples
3.6.16.Skin conductance: Terminology and approaches
3.6.17.Skin conductance change under stress
3.6.18.GSR algorithms: Managing noise and other errors
3.6.19.GSR algorithms: Data interpretation challenges
3.6.20.GSR algorithms: signal processing
3.6.21.GSR algorithms: Conclusions and outlook
3.6.22.Commercial devices for hydration monitoring
3.6.23.Example: InBody
3.6.24.Electrode materials and properties
3.6.25.Technology overview - electrode properties
3.6.26.Wet vs dry electrodes
3.6.27.Wet electrodes
3.6.28.Disposable Ag/AgCl electrodes
3.6.29.Electrodes: Traditional approaches
3.6.30.Skin patches with disposable electrodes
3.6.31.Skin patches with integrated electrodes
3.6.32.Dry electrodes
3.6.33.Introduction - Dry electrodes
3.6.34.Example - Textile electrodes
3.6.35.Examples of e-textiles electrodes
3.6.36.E-textile material use over time
3.6.37.E-textile material use in 2020
3.6.38.E-textile products with conductive inks
3.6.39.Emerging options
3.6.40.Emerging options - Microneedle electrodes
3.6.41.Example: Tyndall National Institute
3.6.42.Example: Sun Yat-Sen University
3.6.43.Company examples - approaches to wearable electrodes
3.6.44.DuPont
3.6.45.Henkel - new electrode materials
3.6.46.Nissha GSI Technologies
3.6.47.Quad Industries
3.6.48.Screentec OY
3.6.49.Holst Centre: Comments on electrode performance
3.6.50.Toyobo
3.6.51.Nanoleq
3.7.Force / pressure / stretch sensors
3.7.1.Different modes for sensing motion
3.7.2.What is piezoresistance?
3.7.3.Early examples of wearable textile FSRs: socks
3.7.4.Percolation dependent resistance
3.7.5.Quantum tunnelling composite
3.7.6.QTC® vs. FSR™ vs. piezoresistor?
3.7.7.Printed piezoresistive sensors: Anatomy
3.7.8.Pressure sensing architectures
3.7.9.Thru mode sensors
3.7.10.Shunt mode sensors
3.7.11.Force vs resistance characteristics
3.7.12.Textile-based pressure sensing
3.7.13.Knitting as a route to textile sensors
3.7.14.Example: Knitted conductors by Gunze, Japan
3.7.15.Strain sensor examples: BeBop Sensors
3.7.16.Large-area pressure sensors
3.7.17.Force sensor examples: Sensing Tex
3.7.18.Textile-based applications of printed FSR
3.7.19.Force sensor examples: Vista Medical
3.7.20.Pressure sensitive fabric (Vista Medical)
3.7.21.SOFTswitch: Force sensor on fabric
3.7.22.Examples: Sensoria
3.7.23.Technological development of piezoresistive sensors.
3.7.24.Curved sensors with consistent zero (Tacterion)
3.7.25.Piezoelectricity: An introduction
3.7.26.Piezoelectric polymers
3.7.27.Printed piezoelectric sensor
3.7.28.Printed piezoelectric sensors: prototypes
3.7.29.High-strain sensors (capacitive)
3.7.30.How they work
3.7.31.Printed capacitive stretch sensors
3.7.32.Use of dielectric electroactive polymers (EAPs)
3.7.33.Key players in DE EAP commercialisation today
3.7.34.Players with EAPs: Parker Hannifin
3.7.35.Players with EAPs: StretchSense
3.7.36.Other examples: Polymatech
3.7.37.C Stretch Bando: Progress on stretchable sensors
3.7.38.Players with EAPs: Bando Chemical
3.7.39.C Stretch Bando: Progress on stretchable sensors
3.7.40.Other strain sensors (capacitive & resistive)
3.7.41.Strain sensor examples: Polymatech
3.7.42.Strain sensor example: Yamaha and Kureha
3.7.43.Hybrid FSR/capacitive sensors
3.7.44.Research with emerging advanced materials
3.7.45.Other novel types of pressure sensor
3.8.Temperature sensors
3.8.1.Two main roles for temperature sensors in wearables
3.8.2.Types of temperature sensor
3.8.3.Approaches and standards for medical sensors
3.8.4.Examples: Blue Spark
3.8.5.Core body temperature
3.8.6.Ear-based core body temperature measurements
3.8.7.Measuring core body temperature: new approaches
3.9.Microphones
3.9.1.Using sound to investigate the body
3.9.2.Types of microphones
3.9.3.Example: MEMS microphones
3.9.4.The need for waterproof, breathable encapsulation
3.9.5.Example: Electret microphones
3.9.6.Bioacoustics
3.9.7.Bioacoustics using IMUs
3.9.8.Microphones and AI for respiratory diagnostics
3.9.9.Microphones in social and clinical trials
3.9.10.Examples: Microphones for sleep apnea
3.10.Chemical sensors
3.10.1.Introduction: Chemical sensing
3.10.2.Selectivity and signal transduction
3.10.3.Analyte selection and availability
3.10.4.Optical chemical sensors
3.10.5.Example: Analytes in the sweat
3.10.6.Glucose monitoring & diabetes management
3.10.7.Introduction - Diabetes management
3.10.8.Diabetes management device roadmap: Summary
3.10.9.Glucose test strips
3.10.10.The case for continuous glucose monitoring (CGM)
3.10.11.CGM is deployed via skin patches
3.10.12.Market share in 2019 (revenue)
3.10.13.Market share in 2019 (volume)
3.10.14.CGM device structure and chemistry
3.10.15.Anatomy of a typical CGM device
3.10.16.CGM sensor chemistry
3.10.17.Comparison metrics for CGM devices
3.10.18.Example: Accuracy of CGM devices over time
3.10.19.Sensor filament structure
3.10.20.Abbott: "Wired enzyme"
3.10.21.Abbott - Device and sensor structure
3.10.22.Abbott - Sensor filament and structure
3.10.23.Abbott - Flux-limiting membranes on the sensor
3.10.24.Dexcom - G4 and G5 sensor design
3.10.25.Dexcom - Changes in G6
3.10.26.Medtronic - also coaxial
3.10.27.Other examples - Medtrum
3.10.28.Others - mixture of approaches
3.10.29.Non-invasive CGM
3.10.30.Example: Indigo
3.10.31.Other applications for wearable chemical sensors
3.10.32.Diagnostics with chemical sensors
3.10.33.Cholesterol
3.10.34.Monitoring blood cholesterol using biosensors
3.10.35.Towards wearable cholesterol monitoring
3.10.36.Alcohol detection
3.10.37.Example: sweat alcohol detection
3.10.38.Lactic acid detection
3.10.39.Lactic acid monitoring for athletes
3.10.40.Traditional lactic acid monitors
3.10.41.Microneedles to analyse lactic acid in interstitial fluid
3.10.42.Other analytes
3.10.43.Increasingly portable diagnosis of bovine and human TB
3.10.44.Wearable diagnostic tests for cystic fibrosis
3.10.45.Example players
3.10.46.Biolinq
3.10.47.Kenzen
3.10.48.Milo Sensors
3.10.49.Eccrine Systems
3.10.50.PARC / UCSD
3.10.51.Stanford and UC Berkeley
3.10.52.Xsensio
3.10.53.Epicore Biosystems
3.11.Gas sensors
3.11.1.Introduction: Wearable gas sensors
3.11.2.Gas sensor industry
3.11.3.Concentrations of detectable atmospheric pollutants
3.11.4.Transition to miniaturised gas sensors
3.11.5.Comparison between classic and miniaturised sensors
3.11.6.Comparison of miniaturised sensor technologies
3.11.7.Technology requirements for wearable gas sensors
3.11.8.Metal oxide semiconductors (MOS) gas sensors
3.11.9.Miniaturisation of MOS Gas Sensors
3.11.10.Suppliers for MOS sensors
3.11.11.Electrochemical (EC) gas sensors
3.11.12.Flat electrochemical sensors
3.11.13.Miniaturisation of electrochemical gas sensors
3.11.14.Suppliers for Electrochemical sensors
3.11.15.Electronic nose (e-Nose)
3.11.16.Algorithms and software to solve the multiple gas detection
3.11.17.Some of the commercial eNose
3.11.18.HiCling
3.11.19.Technology for Social Impact / Grameen Intel
3.11.20.H2S Professional Gas Detector watch
3.11.21.Future opportunities with wearable gas sensors
3.12.GPS
3.12.1.Prominent wearable GPS devices
3.12.2.Challenges with GPS power consumption
3.13.Other examples and case studies
3.13.1.Gastric electrolyte
3.13.2.Example: Proteus Digital Health
4.MARKET FORECASTS
4.1.Forecasting: Introduction and definitions
4.2.Definitions and categorisation for sensor types
4.3.Wearable sensors: Sales volumes (historic data, 2010-2019)
4.4.Wearable sensors: Sales volumes (market forecast, 2020-2031)
4.5.Wearable sensors: Sales volumes (historic data and forecast)
4.6.Wearable sensors: Total revenue (historic data, 2010-2019)
4.7.Wearable sensors: Total revenue (forecast, 2020-2031)
4.8.Wearable sensors: Total revenue (historic data and forecast)
4.9.Wearable sensors: Price per unit (historic data and forecast)
4.10.Wearable sensors: Price per unit (historic data and forecast)
4.11.Waves of wearable sensors: Supporting data
 

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レポート概要

スライド 368
フォーキャスト 2031
発行日 Sep 2020
ISBN 9781913899134
 

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