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1. |
EXECUTIVE SUMMARY |
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1.1. |
Brain Computer Interfaces - Overview of Report Contents |
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1.2. |
Brain computer interfaces: introduction, report scope and major applications |
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1.3. |
BCIs can broadly be categorized as invasive and non-invasive |
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1.4. |
Market Map of Key Players Developing BCI Technologies with HMI Applications |
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1.5. |
Overview of the competitive landscape for brain computer interfaces as human machine interfaces |
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1.6. |
Drivers for emerging alternative human machine interfaces |
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1.7. |
Emerging human machine interfacing solutions competing with BCIs |
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1.8. |
Overview of the measurement principles of BCI technologies |
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1.9. |
Comparing key benchmarks and performance criteria of BCI technology |
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1.10. |
State of adoption of BCI technologies for HMI applications |
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1.11. |
An opportunity for EEG based BCI in virtual reality? |
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1.12. |
Big-Tech and EEG for BCI |
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1.13. |
SWOT analysis of dry electrodes for EEG and the consumer electronics market |
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1.14. |
Summary and outlook for wearable EEG in BCI applications |
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1.15. |
Main conclusions: Outlook for EEG and Dry Electrodes |
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1.16. |
Comparing fNIRS to other non-invasive brain imaging methods |
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1.17. |
fNIRS: SWOT analysis |
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1.18. |
Summary and outlook for wearable fNIRS in BCI applications |
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1.19. |
Background and context of MEG |
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1.20. |
Major barrier to adoption of MEG for BCI: Shielded Environments |
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1.21. |
Summary and outlook for MEG in BCI applications |
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1.22. |
Invasive neural interfaces: background and context |
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1.23. |
Future trends in invasive neural interface technology development |
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1.24. |
Founding and funding timelines of invasive BCI companies (2012-2024) |
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1.25. |
Key conclusions on invasive brain computer interface technologies |
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1.26. |
SWOT Analysis: Commercial applications of brain computer interfaces |
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1.27. |
Brain-computer interface technology: overall twenty-year market forecast by annual revenue (US$ Millions) |
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1.28. |
The brain computer interface market 'at a glance' |
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2. |
INTRODUCTION |
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2.1. |
Chapter overview |
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2.2. |
Neurons, action potentials and local field potentials (LFPs) |
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2.3. |
Neural interface technology approaches |
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2.4. |
Sensorimotor cortex brain rhythms and their relationship with intentions |
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2.5. |
Overview of the measurement principles of BCI technologies |
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2.6. |
Introducing the role of spatial and temporal resolution in BCIs |
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2.7. |
The relationship between brain structure and BCI hardware penetration depth |
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2.8. |
Comparing key benchmarks and performance criteria of BCI technology |
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2.9. |
Comparing key benchmarks and performance criteria of BCI technology |
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2.10. |
Pros and Cons of Non-invasive Interfaces |
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2.11. |
Pros and Cons of Invasive Interfaces |
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2.12. |
Neurofeedback and brain computer interfacing are distinct but complimentary |
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2.13. |
State of adoption of BCI technologies for HMI applications |
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2.14. |
Market Map of Key Players Developing BCI Technologies with HMI Applications |
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2.15. |
Current and future trends in invasive and non-invasive neural interface technology development |
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2.16. |
Business model considerations: Consumables, reusables and the demand for increased hardware longevity |
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2.17. |
Trends in neurotechnology data acquisition |
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2.18. |
Regulators play a key role bringing brain computer interface technology to market |
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2.19. |
State of the industry: Patent analysis suggests filing numbers have peaked |
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2.20. |
Top 20 assignees for "brain computer interface" patents |
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2.21. |
Comparing patent application trends by BCI technology type |
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2.22. |
Clinical trials with public records remain limited in size |
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2.23. |
The impact of the US NIH BRAIN Initiative |
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2.24. |
Founding and funding timelines of invasive BCI companies (2012-2024) |
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2.25. |
Funding landscape of invasive BCI players - 2024 |
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3. |
ELECTROENCEPHALOGRAPHY (EEG) |
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3.1. |
Introduction to Electroencephalography (EEG) |
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3.1.1. |
Background and context of EEG for brain computer interfaces |
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3.1.2. |
Introduction to electroencephalography (EEG) measurements |
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3.1.3. |
Components of an EEG electrophysiology recording system |
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3.1.4. |
EEG is established, but BCI applications face continued challenges |
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3.1.5. |
The established implementation and application: Electrode caps in a clinical setting for neurological disease diagnosis or traumatic brain injury assessment |
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3.1.6. |
Wider market perspectives: Wearable EEG for sleep monitoring as wellness |
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3.1.7. |
Wider market perspectives: Wearable EEG for emotional state monitoring |
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3.2. |
Dry electrode innovations |
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3.2.1. |
Barriers to wider EEG adoption: Wet electrodes create a pain point |
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3.2.2. |
Comparing properties of wet and dry electrodes |
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3.2.3. |
Dry electrodes: A more durable emerging solution for multiple wearable technologies, where EEG is relatively niche |
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3.2.4. |
Key requirements of wearable electrodes |
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3.2.5. |
Key players in wearable electrodes in e-textiles, skin patches and watches |
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3.2.6. |
Material innovations in dry electrodes for EEG |
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3.2.7. |
Active electrode requirements for dry EEG |
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3.2.8. |
Dry electrodes for EEG |
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3.2.9. |
Main conclusions: EEG and Dry Electrodes |
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3.3. |
Key players and market trends in EEG for BCI |
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3.3.1. |
Wearable EEG is relatively established in the medical space, with BCI not currently a key target market for the biggest players |
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3.3.2. |
Device level integration of EEG for BCI applications: Form-factors and key players using dry electrodes |
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3.3.3. |
Comparing the size of key players offering EEG integrated products |
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3.3.4. |
Founding timelines of non-invasive BCI companies (2012-2024) |
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3.3.5. |
An opportunity for EEG based BCI in virtual reality |
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3.3.6. |
Barriers to wider EEG for BCI adoption: The form-factor advantage vs the channel count compromise |
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3.3.7. |
Patent analysis: EEG as an input arrangement for BCI (IPC G06F3/01) |
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3.3.8. |
Big-Tech and EEG for BCI |
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3.3.9. |
Hearable EEG for seizure prediction seeks FDA approval |
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3.3.10. |
Brain controlled wheelchairs (BCWs) using EEG prevalent in academic research, but not commercialized |
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3.3.11. |
Summary and outlook for wearable EEG in BCI applications |
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4. |
FUNCTIONAL NEAR INFRARED SPECTROSCOPY (FNIRS) |
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4.1. |
Overview of fNIRS technology and key players |
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4.1.1. |
Background and context of functional near infrared spectroscopy (fNIRS) |
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4.1.2. |
Basic principles of fNIRS (1) |
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4.1.3. |
Basic principles of fNIRS (2) |
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4.1.4. |
fNIRS: Disruption or coexistence with EEG? |
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4.1.5. |
Key players in fNIRS |
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4.1.6. |
NIRS application areas, BCI in context |
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4.1.7. |
How can fNIRS be utilized for brain computer interfacing |
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4.2. |
Photodetector innovations with fNIRS applications |
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4.2.1. |
PIN photodiode |
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4.2.2. |
Avalanche photodiode (APD) |
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4.2.3. |
Single-photon avalanche diodes |
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4.2.4. |
Silicon photomultiplier |
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4.2.5. |
SPAD vs SiPM |
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4.2.6. |
Comparison of common photodetectors |
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4.2.7. |
Major photodetector players |
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4.3. |
Summary and market outlook for fNIRS based BCI |
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4.3.1. |
Comparing fNIRS to other non-invasive brain imaging methods |
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4.3.2. |
fNIRS: SWOT analysis |
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4.3.3. |
Summary and outlook for wearable fNIRS in BCI applications |
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5. |
MAGNETOENCEPHALOGRAPHY (MEG) |
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5.1. |
Introduction to Magnetoencephalography (MEG) |
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5.1.1. |
Background and context of MEG |
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5.1.2. |
Basic Principles of MEG |
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5.2. |
Sensor innovations for MEG |
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5.2.1. |
Introduction: Quantifying magnetic fields |
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5.2.2. |
Sensitivity is key to the value proposition for quantum magnetic field sensors |
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5.2.3. |
Classifying magnetic field sensor hardware |
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5.2.4. |
High sensitivity applications in healthcare are quantum computing are key market opportunities for quantum magnetic field sensors |
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5.2.5. |
Superconducting Quantum Interference Devices (SQUIDs) |
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5.2.6. |
Applications of SQUIDs |
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5.2.7. |
Operating principle of SQUIDs |
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5.2.8. |
SQUID fabrication services are offered by specialist foundries |
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5.2.9. |
Key players in commercial applications of SQUIDs including MEG |
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5.2.10. |
Comparing key players with SQUID intellectual property (IP) |
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5.2.11. |
SQUIDs: SWOT analysis |
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5.2.12. |
Optically Pumped Magnetometers (OPMs) |
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5.2.13. |
Operating principles of Optically Pumped Magnetometers (OPMs) |
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5.2.14. |
Applications of optically pumped magnetometers (OPMs) (1) |
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5.2.15. |
Applications of optically pumped magnetometers (OPMs) (2) |
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5.2.16. |
MEMS manufacturing techniques and non-magnetic sensor packages key for miniaturized optically pumped magnetometers |
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5.2.17. |
Comparing key players with OPM intellectual property (IP) |
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5.2.18. |
Comparing the technology approaches of key players developing miniaturized OPMs for healthcare |
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5.2.19. |
OPMs: SWOT analysis |
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5.2.20. |
N-V center magnetic field sensors |
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5.2.21. |
Introduction to N-V center magnetic field sensors |
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5.2.22. |
Operating Principles of N-V Centers magnetic field sensors |
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5.2.23. |
Applications of N-V center magnetic field centers |
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5.2.24. |
Comparing key players in N-V center magnetic field sensor development |
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5.2.25. |
N-V Center Magnetic Field Sensors: SWOT analysis |
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5.3. |
Sector overview: MEG for BCI |
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5.3.1. |
Market opportunities for quantum magnetic field sensors in biomagnetic imaging |
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5.3.2. |
Case Study: Cerca Magnetics |
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5.3.3. |
Case Study: Bosch Quantum Sensing |
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5.3.4. |
Assessing the performance of magnetic field sensors |
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5.3.5. |
Comparing minimum detectable field and SWaP characteristics |
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5.3.6. |
Quantum Magnetometers: Sector Roadmap |
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5.3.7. |
Major barrier to adoption of MEG for BCI: Shielded Environments |
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5.3.8. |
Summary and outlook for MEG in BCI applications |
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6. |
INVASIVE NEURAL INTERFACES FOR BCI |
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6.1. |
Introduction to invasive neural interfaces |
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6.1.1. |
Invasive neural interfaces: Background and context |
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6.1.2. |
Examples of neural electrodes |
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6.1.3. |
Introduction to ECoG |
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6.1.4. |
Overview of LFP waveforms |
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6.1.5. |
How neural probes are typically made |
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6.1.6. |
Pros and Cons of select implanted probe materials |
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6.1.7. |
Considerations for electrode material selection |
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6.1.8. |
Considerations for insulating materials |
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6.2. |
Invasive BCI innovations and key players |
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6.2.1. |
Founding and funding timelines of invasive BCI companies (2012-2024) |
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6.2.2. |
Funding landscape of invasive BCI players - 2024 |
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6.2.3. |
What are development trends in research? |
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6.2.4. |
Blackrock Neurotech - Technology overview |
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6.2.5. |
Blackrock Neurotech - Recent research success for BCI applications |
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6.2.6. |
Blackrock Neurotech - Technology challenges |
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6.2.7. |
Utah Array 2.0 - The Utah Optrode Array |
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6.2.8. |
Neuralink - Technology overview |
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6.2.9. |
Neuralink - Commercialization depends on more successful human trials |
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6.2.10. |
Neuralink - Technology challenges ahead |
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6.2.11. |
Onward Medical - Technology overview (1) |
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6.2.12. |
Onward Medical - Technology overview (2) |
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6.2.13. |
Onward Medical - Seeking to commercialize multiple product lines in the next 1-5 years |
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6.2.14. |
Synchron - Technology overview |
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6.2.15. |
Synchron - More human trials ahead |
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6.2.16. |
Paradromics - Technology overview |
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6.2.17. |
Paradromics - Preparing to begin in-human trials |
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6.2.18. |
CorTec - Technology overview |
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6.2.19. |
Precision - Bidirectional flexible arrays |
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6.2.20. |
Inbrain Neuroelectronics - Bidirectional graphene-based arrays |
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6.2.21. |
NeuroXess - Silktrodes and Surftrodes |
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6.2.22. |
Axoft - A new player looking to compete on electrode biocompatibility and softness |
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6.2.23. |
Braingrade - A focus on BCIs for Alzheimer's |
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6.2.24. |
Key conclusions |
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7. |
KEY COMPETITOR TECHNOLOGIES FOR BRAIN COMPUTER INTERFACES |
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7.1. |
Overview of competitor technologies |
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7.1.1. |
Overview of the competitive landscape for brain computer interfaces as human machine interfaces |
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7.1.2. |
Drivers for emerging alternative human machine interfaces |
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7.1.3. |
Emerging human machine interfacing solutions competing with BCIs |
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7.2. |
Electromyography (EMG) and gesture control |
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7.2.1. |
Introduction to Electromyography (EMG) |
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7.2.2. |
Investment in EMG for virtual reality and neural interfacing is increasing |
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7.2.3. |
Investment in EMG for virtual reality and neural interfacing is increasing |
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7.2.4. |
Consumer trends: Smart-straps could take control in the meta-verse |
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7.3. |
Interfacing with AR/VR - eye tracking and hand tracking |
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7.3.1. |
What are VR, AR, MR and XR? |
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7.3.2. |
Controllers and sensing connect XR devices to the environment and the user |
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7.3.3. |
Beyond positional tracking: What else might XR headsets track? |
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7.3.4. |
Where are XR sensors located? |
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7.3.5. |
Sensors case study: Microsoft's HoloLens 2 |
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7.3.6. |
3D imaging and motion capture |
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7.3.7. |
Application example: Motion capture in animation |
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7.3.8. |
Stereoscopic vision |
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7.3.9. |
Time of Flight (ToF) cameras for depth sensing |
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7.3.10. |
Structured light |
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7.3.11. |
Comparison of 3D imaging technologies |
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7.3.12. |
Microsoft: From Kinect to HoloLens |
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7.3.13. |
Intel's RealSense™: Structured light for 3D motion tracking vs. stereoscopic cameras |
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7.3.14. |
Summary: Positional and motion tracking for XR |
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7.3.15. |
Why is eye tracking important for AR/VR devices? |
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7.3.16. |
Eye tracking sensor categories |
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7.3.17. |
Eye tracking using cameras with machine vision |
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7.3.18. |
Eye tracking companies based on conventional/NIR cameras and machine vision software |
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7.3.19. |
Event-based vision for AR/VR eye tracking |
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7.3.20. |
Eye tracking with laser scanning MEMS |
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7.3.21. |
AdHawk Microsystems: Laser scanning MEMS for eye tracking |
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7.3.22. |
Capacitive sensing of eye movement |
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7.3.23. |
Summary: Eye tracking for XR |
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7.3.24. |
Other novel HMI interfaces |
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7.3.25. |
In-ear muscles could enable the next revolution in brain computer interfacing |
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7.3.26. |
Mouthpad utilizes the tongue as an 'eleventh finger' |
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8. |
MARKET FORECASTS AND APPLICATIONS |
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8.1. |
BCI - Commercial Applications Overview |
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8.2. |
Industry 5.0 and future mobility applications of brain computer interfaces? |
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8.3. |
Commercial status of BCI applications in 2024 |
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8.4. |
SWOT Analysis: Commercial applications of brain computer interfaces |
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8.5. |
Market Forecasts: Scope and methodology |
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8.6. |
Brain computer interface technology: Overall twenty-year market forecast by annual revenue (US$ Millions) |
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8.7. |
Brain computer interface technology: Twenty-year market share forecast by annual revenue |
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8.8. |
Non-invasive brain computer interface technology: Overall twenty-year market forecast by annual revenue (US$ Millions) |
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8.9. |
Invasive brain computer interface technology: Overall twenty-year market forecast by annual revenue (US$ Millions) |
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8.10. |
The brain computer interface market 'at a glance' |
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9. |
COMPANY PROFILES |
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9.1. |
Artinis Medical Systems |
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9.2. |
Axoft |
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9.3. |
Blackrock Neurotech |
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9.4. |
BrainCo — Brain EEG Headband and Robotic Prosthetic Hand |
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9.5. |
Braingrade |
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9.6. |
Cerca Magnetics |
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9.7. |
CorTec-Neuro |
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9.8. |
Datwyler (Dry Electrodes) |
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9.9. |
EarSwitch |
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9.10. |
IDUN Technologies |
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9.11. |
Kokoon |
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9.12. |
Naox Technologies |
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9.13. |
Neuralink |
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9.14. |
NeuroFusion |
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9.15. |
Onward Medical |
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9.16. |
Precision Neuroscience |
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9.17. |
Synchron |
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9.18. |
uCat |
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9.19. |
Wearable Devices Ltd. |
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9.20. |
Wisear |
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