Wearable Sensors Market Forecasts, Technologies & Players

Wearable Sensors 2016-2026: Market Forecasts, Technologies, Players

IDTechEX, Date of Publication: Apr 4, 2016, 255 Pages

This report provides detailed descriptions of the sensor types that dominate wearable technology products today, and emerging sensor types that will dominate in the future. Many product types have risen through the peak of the wearable technology hype curve in the last five years before beginning the slide to disillusionment. The common feature with all of them is the prominence of sensor options as the key enabler for their most useful functions.

Sensors collect data about the physical and chemical properties of the body and local environment, and use it to feed algorithms which output insightful information. With coverage of all of the prominent incumbent sensors and the most promising emerging options, the report concludes that there will be 3 billion wearable sensors by 2025, with over 30% of them being new types of sensors that are just beginning to emerge.

Wearable Sensors Market Size

The report groups sensors in prominent categories, as follows:

  • Inertial measurement units (IMUs - including accelerometers, gyroscopes, magnetometer and barometers)
  • Optical sensors (including optical heart rate monitoring, PPG and cameras)
  • Wearable electrodes
  • Chemical sensors
  • Flexible stretch/pressure/impact sensors
  • Temperature sensors
  • Microphones
  • Other emerging wearable sensors

For each sensor, the technologies and major players are described, backed up by detailed interviews and company profiles of key bodies in each sector. The report also views the big picture, discussing the implications of sensor fusion and the relative merits of each sensor type for various applications. This extensive primary research is used to produce detailed market forecasts for each sensor type over the next decade. Market data is provided for the growth of each sensor type, and is used to illustrate key trends that are observable in various application sectors.

Wearable Sensors market growth

Growth rates summary for each sensor type

Sensor trends are tied to key market sector trends for wearable technology, building on extensive analysis of 800 active players in the wearable technology space. Many of the most prominent wearable technology trends are closely tied to the properties and limitations of sensor systems. Case studies are used to illustrate the most prominent examples, including regulatory implications for healthcare systems, ease of commoditisation in infotainment devices and the possibilities presented by sensor fusion.

Sensors are the most diverse component type in wearable devices, and they also enable the key functions that will make wearable devices be worn. Advances with wearable sensors are a vital driver for the future of wearable technology. Their incorporation alongside new energy harvesting and storage techniques, efficient power management systems and low power computing, in form factors that will be increasingly flexible, fashionable and invisible will drive significant growth in the wearable technology market over the next 10 years.

This report purchase includes 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.

Wearable Sensors 2016-2026: Market Forecasts, Technologies, Players


1.1. Monitoring the human body - sensors for wearable devices, arranged by signal type
1.2. Standing out from the wearables crowd
1.2.1. The story so far: IMUs dominate
1.2.2. New sensor options enabling greater market penetration
1.2.3. Sensor fusion
1.3. Key market sectors
1.3.1. Healthcare: the largest opportunities for new sensors
1.3.2. Infotainment: already prominent, but most prone to commoditization
1.3.3. Commercial, industrial, military use: some of the best use cases


2.1. Scope and definitions
2.1.1. What is a sensor?
2.1.2. Defining 'wearable sensors'
2.2. Market size for sensors in wearable technology
2.2.1. Revenue forecast (in USD)
2.2.2. Units forecast
2.3. Forecasts by sensor category
2.3.1. Inertial measurement units
2.3.2. Wearable electrodes
2.3.3. Optical sensors
2.3.4. Stretch, pressure and related flexible sensors
2.3.5. Chemical sensors
2.3.6. Other sensors


3.1. Introduction to MEMS
3.1.1. A brief history of MEMS
3.1.2. Manufacturing techniques
3.1.3. MEMS industry players
3.1.4. The speed of development in the MEMS industry
3.2. Accelerometers
3.3. Gyroscopes
3.3.1. Overcoming power consumption challenges with gyroscopes
3.4. Magnetometers
3.4.1. Magnetometer suppliers
3.5. Pressure sensors
3.5.1. Uses in wearable devices
3.5.2. Pressure sensor suppliers
3.6. Trends with IMUs in consumer electronics
3.6.1. STMicroelectronics
3.6.2. InvenSense
3.6.3. Apple: case study from the iPhone
3.7. IMUs: here to stay, despite some limitations


4.1. Resistive force sensors
4.1.1. Printing inks onto textiles to make an array pressure sensor
4.1.2. Textile FSRs
4.2. Capacitive pressure sensors
4.2.1. How they work
4.2.2. Capacitive stretch sensors in clothing
4.2.3. Stretchable capacitive harvesting up to 1 kW?
4.2.4. Research with emerging materials
4.3. Other types of pressure sensor


5.1. Measuring biopotential
5.1.1. The medical procedures: ECG, EEG, EMG
5.1.2. How the circuit is constructed
5.2. Electrode properties
5.2.1. Challenges and solutions with dry electrodes
5.2.2. Emerging electrode materials
5.3. Bioimpedance
5.3.1. Galvanic skin response
5.3.2. Bioelectrical impedance analysis (BIA)
5.4. Case study: marketing the potential of bioimpedance sensors
5.4.1. The Jawbone UP3
5.4.2. HealBE
5.5. Gastric electrolyte
5.5.1. Proteus Digital Health
5.6. Wearable electrode players
5.6.1. New product designs
5.6.2. Players in the medical sector
5.6.3. Beyond medical uses: commercial devices measuring biopotential


6.1. Medical applications: optical heart rate monitoring
6.1.1. Transmissive PPG
6.1.2. Reflective PPG
6.1.3. "Circumission" PPG
6.1.4. Design considerations
6.1.5. Valencell: ear OHRMs
6.1.6. Other players
6.2. Infotainment applications: mo-cap with cameras
6.2.1. Comparison of 3D imaging technologies
6.2.2. Time of flight
6.2.3. Structured light
6.2.4. Microsoft Kinect and the Hololens
6.3. Wearable cameras
6.3.1. Established players exploiting profitable niches
6.3.2. Camera smartwatches
6.3.3. Applications in safety and security
6.3.4. Other wearable camera examples


7.1. How chemical sensors work
7.1.1. Device construction
7.1.2. The use of electrodes
7.2. Analyte source selection
7.2.1. Going beyond blood
7.2.2. Reliability vs practicality
7.2.3. Time dependence
7.2.4. The advantages of less invasive techniques
7.3. Case study: glucose monitoring and diabetes treatment
7.3.1. The incumbent, invasive, non-wearable solution: screen printed electrodes
7.3.2. Glucose test strips
7.3.3. Making test strips: screen printing vs. sputtering
7.3.4. Technical challenges
7.3.5. Minimally-invasive glucose monitoring: a wearable solution
7.3.6. Abbott Diabetes Care: minimally-invasive monitoring solution
7.3.7. Emerging wearable solutions are far from perfect
7.3.8. Progress towards a reliable non-invasive solution
7.3.9. The ultimate goal: "closing the loop" for diabetes treatment
7.4. Emerging chemical sensors for other analytes
7.4.1. Wearable patches by Electrozyme
7.4.2. Sweat sensing: University of Cincinnati Novel Devices Lab
7.4.3. Cholesterol sensor
7.4.4. Tuberculosis testing
7.4.5. Drug screening
7.4.6. Using nanomaterials to enhance sensor performance


8.1. Types of gas sensors
8.1.1. Pellistors
8.1.2. Infrared
8.1.3. Electrochemical
8.1.4. Chemiresistors
8.1.5. Electronic nose (e-nose)
8.2. All-printed gas sensors with solid electrolytes
8.2.1. SPEC sensor
8.2.2. Solidsense
8.3. Emerging wearable applications of gas sensors
8.3.1. Breath sensing
8.3.2. Research on acetone breath analysis


9.1. Temperature
9.1.1. Temperature sensor technologies
9.1.2. Wearable temperature sensor examples
9.2. Sound
9.2.1. MEMS microphones
9.2.2. Electret microphones
9.2.3. Bioacoustics


10.1. The huge sensor fusion opportunity
10.1.1. Case study: heart rate monitoring
10.1.2. Case study: gaining useful data from skin patches
10.1.3. Case study: analysing the voice without measuring sound
10.2. Application case study: head impact sensors
10.3. Application case study: care of the elderly, and integration with the wider internet of things


11.1. adidas
11.2. APDM
11.3. BeBop Sensors
11.4. Bioling (formerly Electrozyme LLC)
11.5. Cetemmsa
11.6. Clothing+
11.7. Firstbeat Technologies Ltd
11.8. GlaxoSmithKline
11.9. Hexoskin
11.10. Hivox Biotek
11.11. IMEC
11.12. Infi-tex
11.13. Johnson & Johnson Innovations
11.14. Medical Design Solutions
11.15. Medtronic Inc
11.16. Ohmatex ApS
11.17. Proteus Digital Health
11.18. PST Sensors
11.19. Sarvint Technologies, Inc.
11.20. Seiko Epson Corporation
11.21. Sensing Tex
11.22. Sensoria
11.23. Smartlife Technology Ltd
11.24. Stretchsense
11.25. Thalmic Labs
11.26. Valencell Inc
11.27. Vivalnk
11.28. Vocalzoom
11.29. Ybrain Inc.


2.1. IDTechEx categorization of wearable sensors
2.2. Market size for each wearable sensor type from 2016-2026, in USD millions
2.3. Forecast: number of units sold for each sensor type, 2016-2026
2.4. Market size for wearable inertial measurement unit sensors, 2016-2026 (USD millions)
2.5. Market size for wearable electrodes, 2016-2026 (USD millions)
2.6. Market size for wearable optical sensors, 2016-2026 (USD millions)
2.7. Market size for stretch, pressure and related flexible sensors, 2016-2026 (USD millions)
2.8. Market size for wearable chemical sensors, 2016-2026 (USD millions)
2.9. Market size for other wearable sensors, 2016-2026 (USD millions)
3.1. The largest MEMS and other micro-fabricated device players, by 2013 sales
3.2. Magnetometer types for the consumer electronics industry.
4.1. Materials options for capacitive pressure sensors for use in wearable electronics, and especially clothing
5.1. The good, the bad and the ugly: some marketing claims made by companies making consumer BIA devices
5.2. Calorie intake data as measured by the GoBe fitness tracker, showing large errors
6.1. Comparison of different technologies for 3D imaging
7.1. Selectivity and associated signal transduction techniques in chemical sensors
7.2. Assessment of the different chemical and biomarker sources of the body that can be measured. The traffic light system describes performance of each fluid choice in the header categories, and the three most common substances are bo
7.3. Some of the most pressing technical challenges for printed glucose test strips
8.1. Types of gas sensors
10.1. Comparison between typical sensor outputs and sensor fusion outputs


1.1. General trends in product designs lead to wearable solutions that are increasingly invisible and functional
1.2. Texas Instruments show the breakdown of a basic wearable device by component type
1.3. Sensor fusion example in inertial measurement units
1.4. The largest global industry sectors are converging to wearable technology
2.1. Multiple definitions of a sensor
2.2. Market forecast for wearable technology sensors, 2016-2026 (in USD millions)
2.3. Number of units sold for wearable sensors, 2016-2026
2.4. Market forecast for wearable inertial measurement unit sensors, 2016-2026 (USD millions)
2.5. Market forecast for wearable electrodes, 2016-2026 (USD millions)
2.6. Market forecast for wearable optical sensors, 2016-2026 (USD millions)
2.7. Market forecast for stretch, pressure and related flexible sensors, 2016-2026 (USD millions)
2.8. Market forecast for wearable chemical sensors, 2016-2026 (USD millions)
2.9. Market forecast for other wearable sensors, 2016-2026 (USD millions)
3.1. Scanning Electron Microscope image of a Bosch MEMS accelerometer. Each of the long beam-like structures are around 3 micrometers thick.
3.2. Etching shapes from (a) anisotropic, (b) isotropic and (c) IRE processes
3.3. Technique for constructing a simple MEMS cantilever
3.4. How a typical MEMS accelerometer works
3.5. The detailed miniature structure of a MEMS accelerometer
3.6. The typical structure and operating principle of a MEMS gyroscope
3.7. The structure of a Hall Effect magnetometer. This is the AK8975/3 from AKM, found in many products, including the iPhone 4. Other versions offer slightly different performance (power, sensitivity, etc.), but the design remains sim
3.8. Operating structures and principles for four of the five main types of magnetometer used in consumer electronics. (1) GMR (2) Hall effect, (3) MTJ, (4) AMR
3.9. Assessment of the five most common magnetometer types.
3.10. MEMS pressure sensor structure
3.11. STMicroelectronics' global manufacturing sites for MEMS sensors, as of 2013
3.12. Waves of MEMs sensor proliferation
4.1. Printed piezoresistive force sensor construction
4.2. Force sensor construction variant
4.3. BeBop's multi-layer printed ink on fabric sensors
4.4. The waveform detection method in BeBop's pressure sensors.
4.5. Force sensitive resistors have been used to measure foot impacts in research for many years, without successful transfer to commercial products
4.6. The Sensoria Anklet, that attaches magnetically and electrically to the top of the sock containing FSRs. 30% of the anklet volume is taken by a 120 mAh Li-polymer battery.
4.7. Capacitive stretch sensors from StretchSense. The left hand image shows their fabric design, released at the end of 2014. The right hand image shows an example hand motion detection application using StretchSense's first generatio
4.8. MATFLEXEND basics compared to traditional capacitive harvesting
4.9. Partners
4.10. Capacitive harvesting the new way
4.11. Potential for high energy
4.12. Electrode options
4.13. Elastomer harvester details
4.14. Other applications
4.15. Stanford university are developing capacitive pressure sensors using carbon nanotubes and silicone
4.16. Stanford Engineering team's pressure sensor
5.1. The method for making electrophysiological measurements (including ECG, EMG and EEG). For wearable technology, electrodes are mounted on the surface of the skin, but for many medical applications, electrodes are typically intrusiv
5.2. Traditional Ag/AgCl electrodes are commodity items, and the most common electrode type by far in the medical sector.
5.3. Gunma University research into stretchable conductive pastes for use with textiles, using silver fillers in a elastomeric binder
5.4. Impedance data from stretchable conductive ink electrodes developed at Gunma University, Japan. For the key frequency range of biological signals, the dry electrodes still show several times higher impedance than wet electrode equ
5.5. Electronic tattoos by researchers at Seoul National University. It shows single crystalline silicon components encapsulated with polyurethane.
5.6. Seoul National University, Korea, present date about their work in epidermal electronics. They found that conformal integration of devices onto the human skin can provide higher S/N ratios than fabric-based systems. They have expe
5.7. EPDM electrode form, and an example headset application from IMEC & the Holst Centre
5.8. Polygraphs use GSR alongside other techniques to characterise emotional response to questions in order to determine whether the subject is lying
5.9. The basic electrical modelling of biological cells in bioimpedance studies.
5.10. The Simband, from Samsung and developed in work with Imec, is a reference design for a wrist-based device containing many sensors, including electrodes for BIA. This figure represents BIA in action.
5.11. Jawbone present their capabilities, but are not heavily marketing the bioimpedance capability of their new device
5.12. The Jawbone UP3 contains electrodes capable of measuring bioimpedance
5.13. The GoBe calorie counting fitness tracker from HealBe
5.14. The structure and function of Proteus' ingestible sensor. The Ingestible chip transmits information via electric fields that can be detected by a skin patch receiver
5.15. Proteus' wearable patch that receives information from the ingestible sensor. It also can be used to detect other body parameters, and acts as a useful sensor platform. The chip structure and size are also shown.
5.16. How the Proteus ingestible sensor product looks. The tiny sensor can be ingested with medicine, and then data about the physiological response is transmitted via electric field to the patch, before moving to data.
5.17. Thalmic Labs' Myo armband, showing the EMG sensing.
5.18. Examples from the extensive range of chest strap heart rate monitors
5.19. Heart rate monitoring clothing product examples
5.20. Heart rate monitoring patch product examples
5.21. Examples of commercial EEG prototypes and products
5.22. Examples of commercial EMG products
6.1. A wrist mounted pulse oximeter
6.2. How reflective PPG works
6.3. Samsung Simband reference design includes several different wavelengths (characterised by different colours) of optical sensors in the wristband for measuring heart rate by PPG, and potentially other biometrics.
6.4. Circumission PPG, presented by Munich start-up Cosinuss
6.5. Health evaluation kit, produced by Texas Instruments, incorporating the APM Korea OHRM
6.6. The typical chipset required for time-of-flight 3D imaging
6.7. Structured light 3D imaging in the first generation Microsoft Kinect, shown under a night vision camera
6.8. GoPro cameras have seen widespread in extreme sports
6.9. The first edition of the Samsung Galaxy Gear Smartwatch had a camera, but it was removed for later editions
6.10. OnCall body cameras, designed for use by emergency services on the job
6.11. Wearable camera products from Narrative (left) and Autographer (right) have seen differing success
6.12. Both chest- (left) and head- (right) mounted cameras have been trialled in professional rugby union, with footage used for media coverage, match analysis and training purposes
7.1. University of Cincinnati New Devices Lab's table showing biomarker concentrations in the sweat. This provides an excellent summary of the types of species that can be detected, and typical concentration ranges.
7.2. Time delays for typical blood analyte concentration readings, by device type. Extra distribution time for sweat and interstitial measurements mean that even the theoretical minimum time delay (where reading time = 0) is still gre
7.3. The advantages of continuous glucose monitoring: allows the user to gain a much more accurate description of their blood sugar profile over time.
7.4. Example of a reader measuring the glucose level from a test strip.
7.5. Glucose meter for iPhone. The iBGStar was developed by AgaMatrix and commercialised exclusively by Sanofi in 2012.
7.6. No generic design: test strips vary from manufacturer to manufacturer.
7.7. Advantages of printing vs. sputtering on a scale of 1 to 5 (higher is better).
7.8. Evolution of sample volume needed
7.9. The accuracy of implantable glucose sensors, measured compared to the glucose test strips standard over 14 days of wear
7.10. The structure of the chemical sensing element in Abbott's blood glucose sensors. Glucose oxidase enzymes are attached to an electrode surface using covalent bonding in a cross-linked polymer network containing osmium complexes. Th
7.11. Glucose detection method in the Abbott glucose sensors. Glucose is oxidized by the glucose oxidase enzyme, and the electrons released are transported via covalently bonded Osmium complexes in a polymer network to the electrode, wh
7.12. Glucose sensing contact lens
7.13. Tattoo sensor for non-invasive glucose measaurement
7.14. The electrode structures used in the glucose sensing skin patch
7.15. Pancreum make a wearable 'artificial pancreas' device. The aim of these developments is to produce fully automated wearable monitoring and treatment options for diabetics.
7.16. Various types of electrochemical measurement techniques
7.17. Wearable device prototype, showing the disposable sensor patch
7.18. Sensor fabrication is based on screen printing
7.19. Sensor construction from the University of Cincinnati's work in patch chemical sensors. They use a ionophore membrane to selectively absorb sodium ions, with a Pd/Cu working electrode and a Ag/AgCl reference electrode.
7.20. Later iterations of their skin patch include potentiometric readings (bioimpedance) to measure properties of the skin. They have now incorporated sensors for 7 analytes, with more functionality, better accuracy and low costs.
7.21. Other groups within the department have developed bio-functionalised gold electrodes enabling pico-molar concentration measurements of blood analytes
7.22. Smart Integrated Miniaturised Sensor (SIMS)
7.23. DRUGSENSOR for drug screening
7.24. Comparison between unmodified and CNT coated SPE.
7.25. The Omega 3 system, consisting of a reader and a microfluidic cartridge.
7.26. Nanostructured copper
8.1. Metal-oxide gas sensor
8.2. An electronic nose is a recognition system, not a sensor technology
8.3. KWJ Engineering technology roadmap
8.4. Characteristics of the CO sensor
8.5. Sensor response to different levels of carbon monoxide
8.6. Photograph of a wafer containing 48 sensors.
9.1. TempTraq™ is a wearable intelligent Bluetooth thermometer in the form of a soft patch that continuously and comfortably monitors body temperature for 24 hours.
9.2. The structure of a MEMS microphone
9.3. The structure of an electret microphone
9.4. Bioacoustic sensing, as demonstrated by Microsoft's Skinput platform
10.1. One of the most common and earliest examples of sensor fusion in wearables: inertial measurement units
10.2. Sensor fusion in the Simband from Samsung combines optical and electrical HRM to deduce blood pressure
10.3. Sweat rate measurement used to calibrate chemical sensor readings in skin patches.
10.4. Sweat gland models developed to aid research into skin patch chemical sensors
10.5. Use of accelerometers to measure voice disorders in humans
10.6. Black box biometrics' announced their military monitoring system at CES 2015
10.7. X2 Biosystems make a concussion sensor skin patch that is designed for use in sports
10.8. Home monitoring systems will integrate wearable devices, but are still several years from mass adoption

Date of Publication:
Apr 4, 2016
File Format:
PDF via E-mail
Number of Pages:
255 Pages
Type the characters you see in the picture above.