1. Introduction

Photobiomodulation (PBM), also known as light therapy, in our case with near-infrared (NIR) light, has shown promising results for therapeutic applications, particularly in brain health. However, accurately measuring NIR light is complex, with variations in measurement devices creating significant challenges. At Neuronic, we’ve encountered this firsthand while measuring the Neuradiant 1070 device, observing that different equipment yields varying results. This article details our findings, providing insight into the capabilities and limitations of spectrometers and underscores the importance of precise, standardized measurements for reliable research.
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The Complexity of Light

Light is a captivating phenomenon that has intrigued some of the greatest minds in history, including Isaac Newton and Albert Einstein. Newton’s pioneering work in optics revealed that white light is composed of a spectrum of colors, a concept that remains astonishing even in the context of our modern understanding. The idea that red, orange, yellow, and green light can combine to create white light defies intuitive comprehension, highlighting the extraordinary nature of light itself.

Equally remarkable is the ability of modern instruments to measure photons, the smallest units of light energy. Unlike objects with mass, photons travel at what we term "the speed of light" because they are inherently massless. As physicist Brian Cox suggests, this could be more accurately described as "the speed of massless particles," underscoring the unique properties of photons. Einstein’s Nobel Prize-winning work in 1905 further advanced our understanding of light, conceptualizing it as a stream of particles capable of transferring energy by ejecting electrons from materials. This groundbreaking insight shaped modern physics. These revelations illustrate light's elegance and complexity, making its measurement a scientific and technical challenge of the highest order.

Light, an interplay of energy, fields, and particles, exists as electromagnetic radiation. A photon, the smallest “packet” of light energy, moves as a disturbance through the electromagnetic field at light speed, emitted when charged particles, like electrons, change energy levels. These photons travel as waves, creating the light we perceive.

Though massless, photons carry momentum, enabling interactions with matter. When photons strike atoms, they can transfer energy to electrons, causing effects such as vision and photosynthesis. Electromagnetic radiation—including visible light, radio waves, and near-infrared light—consists of streams of photons oscillating through space as waves. This dual nature gives electromagnetic radiation both wave and particle properties, characterized by wavelength (nm) and energy (Joules). Before we delve further into our findings, we have made a list of some of the key terminology that is essential to know in measuring light. 

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2. Differentiating Spectrometers: Understanding Key Measurement Tools

Spectrometers: These tools provide detailed spectral information, measuring irradiance and wavelength. This insight into light characteristics is essential for understanding the emission profile in PBM applications.

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These instruments were chosen to compare how different measuring devices affect result accuracy. The higher-end spectrometer typically provides more reliable data. This comparison forms part of our effort to establish standardized, quality-controlled measurements at Neuronic.

What Do Spectrometers Measure? 

Light consists of a specific spectrum, with each wavelength carrying a distinct amount of energy. Take the sun, for instance; we know that it emits varying wavelengths, including ultraviolet light, visible light, and NIR light; over 50% of the sun’s energy is infrared light (Kochevar, 1987).

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A spectrometer reveals the wavelengths of light emitted by a source and quantifies the energy associated with each (typically measured in irradiance). Spectrometers measure the interaction between photons and electrons within a sensor. Photons excite electrons to generate a signal, which helps spectrometers provide irradiance and peak wavelength data. Please see below an example image of what a typical graph would look like when measuring light. 

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How Did We Measure Light?

It turns out that trying to measure a helmet filled with LEDs is not as simple as one may think. When we think about light scattering, the impact of the curvature of the helmet, the material of the helmet, the placement of the LEDs, and the clear plastic, we already have an abundance of factors that all play a role in determining how we measure light. Keeping this in mind, we chose spectrometers to measure the irradiance for the Neuradiant 1070, as we can measure the varying positions of the device. For those well-versed in this field, a question may arise about the decision not to use an integrating sphere for our measurements. We opted against this approach due to the impracticality of accurately evaluating a spatially large and complex light-emitting structure like ours. Integrating spheres also has the potential to capture light scattered in unintended directions, leading to inaccurate results. Furthermore, the helmet's LEDs are specifically oriented toward the center. In the absence of a human head, a significant amount of light would be absorbed by the opposite side of the helmet rather than being absorbed as it would naturally by the head. This would further distort the measurement outcomes.

We must discuss precisely how we measured the near-infrared light with the spectrometer. The spectrometers have varying diffusers, which help the scattered light go into the sensor uniformly. In our case, we also took the time to measure a 90-degree diffuser and a 180-degree diffuser for the high-end spectrometer, whilst for the mid-range spectrometer, we had a 10 mm cosine corrector designed to provide a uniform response from all angles of light. While the exact angle is not specified, cosine correctors can approximate an ideal cosine response, meaning their sensitivity decreases proportionately to the cosine of the incident of light angle. What this implies is that even before taking a single measurement, variations in irradiance results will arise due to differences in diffusers.

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Placement of spectrometers

We wanted to obtain two key measurements. The first key measurement is the irradiance of the direct LED. For this, we place the 90-degree diffuser and the mid-range spectrometer directly above an LED with a 1 mm gap between the diffuser and the LED. We can then calculate the total irradiance of the LEDs by finding the average irradiance of multiple LED measurements and multiplying it by the number of LEDs (256). The other key measurement is the irradiance of LEDs with the spectrometer placed on top of the clear plastic (irradiance of helmet). We collected measurements at multiple sites to find the average irradiance for each spectrometer. From this, we can calculate the total power output of the device by multiplying the average irradiance by the surface area of the LED section of the helmet (560 cm²). This would record the ‘realistic measurement’ of how much irradiance actually interacts with tissue as it incorporates the diffraction of light and the clear plastic.

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3. Results and Measurements

1. Direct LED Results 

This section highlights the irradiance results for both spectrometers placed directly above multiple LEDs. We did not measure the 180-degree diffuser for the high-end spectrometer, as on preliminary measurements, it did not provide accurate results that were this close to the LED.

Mid-range spectrometer

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Graph 3 shows the recorded irradiance's density for all the LEDs measured. The mean irradiance recorded with the mid-range spectrometer was 11.16 mW/cm² with 1.35 standard deviations. The lowest irradiance obtained was 7.46 mW/cm² whilst the highest irradiance recorded was 13.83 mW/cm².

High-end spectrometer - 90-degree diffuser

The high-end spectrometer also had a variance in irradiance measurements per LED. Results identified a range of irradiance, from 7.5 mW/cm² to 13.5 mW/cm² and an average irradiance of 10.5 mW/cm².

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2. Irradiance of Helmet Results

Three sites were used to obtain irradiance measurements of the helmet. We measured at multiple sites due to the device's variance dependent upon the location. These factors include changes in the distance between the LED and the plastic, differences in the amount of LEDs in a given area, and differences in the curvature of the helmet. The spectrometer was placed in multiple places in these sites to obtain an average. Table 5 compares irradiance measurements in the spectrometer and diffusers used. 

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Results of the average irradiance indicate that the diffuser is a significant factor in results. The 180° diffuser had the highest average irradiance (1.94 mW/cm²) because it could take in more light than the other 90-degree diffuser (1.62 mW/cm²) and the cosine corrector (1.4 mW/cm²). As mentioned previously, there were different measurements in irradiance across each site, further emphasizing the importance of obtaining multiple measurements.

Overview of Results

1. Direct LED

The results indicated that when we measured an LED directly, it had an irradiance of 10.8 mW/cm².  To calculate the total power of all LEDs within the Neuradiant 1070 (256 LEDs), multiply the average direct LED irradiance (10.8 mW/cm²) by the amount of LEDs (256) which would result in a total power output of 2764 mW. This is possible, as we know that the total LED power is being absorbed by the diffuser.

2. Helmet

The data obtained from all three sites showed an average irradiance of 1.65 mW/cm². We can calculate the total power by multiplying this measurement by the helmet's average irradiance (1.65 mW/cm²) and its surface area (560 mW/cm²). The total power output is 924 mW.

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Variation of Total Power measurements: Direct LED vs Helmet

The total power output of the helmet is just over one-third of the calculated power from the direct LED measurement. A key limitation when measuring the LED directly is that we can account for all emitted light. However, as the diffuser is placed further away, the light's diffraction angle exceeds the diffuser's capture angle (e.g., 90-degree diffuser), resulting in less measurable light. This highlights both a limitation of the diffuser itself and a significant source of variation between different diffuser measurements. Additionally, other factors can influence the results—for example, transparent plastic can affect measurements by 3–5%. Ultimately, we are still working to fully understand the discrepancy in total power measurements. While the theoretical total power might be 2764 mW, reduced by 3–5% to account for the influence of the transparent plastic, our measured total power using the helmet is 924 mW. To maintain accuracy and avoid overstating the device's actual power, we will adopt the 924 mW measurement as the definitive value. This approach ensures a conservative and realistic representation of the device's performance, providing a more reliable basis for further analysis and application.

Practical Application of Results

From the measurements, we can calculate the total joules (energy) of a session with the device. For this demonstration, we can use one of our pre-set protocols, GLOW, which is a 10-minute session of continuous light. To work out the total energy needed for this, We use the total power (924 mW), convert this number to watts (0.924 W), then multiply this by 600 seconds (10 minutes), which gives a calculation of 554 J. From this, we can measure the fluence (J/cm²) by dividing 554 J by the surface area of the helmet (560 cm²) which gives a fluence of 1 J/cm².

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4. Challenges in Measuring Irradiance: Key Factors

Multiple factors beyond device choice influence irradiance measurements in NIR light therapy. Below are some core variables that impact measurement accuracy:

1. Distance from Light Source

Even small shifts in position, moving the diffuser 1 mm to the side or adjusting it by 1 cm, can alter readings. Light disperses as it travels, and diffraction spreads the light waves, reducing irradiance at greater distances. Controlling the distance from the light source is essential for repeatable measurements.

2. Spot Size and Lens Shape

The “spot size effect” is another crucial factor. Changes in diameter by even 1 mm can significantly alter irradiance measurements. Concave lenses can concentrate light, narrowing the spot size, whereas convex disperses light.

3. Time and LED Efficiency

Over prolonged use, LEDs emit more heat, reducing light output and affecting irradiance. The efficiency loss due to heating can range widely, but for many LEDs, efficiency drops by roughly 5-20% when they operate continuously without sufficient cooling. The exact percentage depends on factors like the specific LED design, thermal management, ambient temperature, and current drive levels. Standardized time intervals between measurements can help mitigate this effect, but each measurement setup requires careful timing to ensure accurate results.

4. Diffuser Variations

As mentioned before, we recorded the results using different diffusers. Diffusers, designed to capture light evenly, vary in degrees (10° vs 90° vs. 180°), with wider diffusers capturing more scattered light. However, this can dilute the measurement and reduce intensity. Selecting the appropriate diffuser for the application and controlling environmental factors is crucial for reliable readings. It is important to note that different spectrometers use different diffusers, making it difficult to compare results. 

5. Shape and Configuration of the Device

While single LEDs can be measured relatively easily in controlled lab conditions, such as in integrating spheres, accurately measuring devices with multiple LEDs or lasers presents significant challenges. In multi-LED or multi-laser devices, the light output varies across the surface, with each LED or laser adding to the overall irradiance differently. This complexity makes capturing an accurate, uniform irradiance measurement difficult, as different angles, spacing, and output intensities affect the combined light field. Standardizing measurement techniques for these devices is essential but challenging, particularly when aiming to replicate real-world application settings.

The Importance of Transparent Reporting in Measurement Methods

One significant obstacle to replicating research in PBM & NIR light therapy is the inconsistent reporting of measurement methods and calibration practices. Many studies need more comprehensive detail on the equipment used, such as spectrometer types, power meters, and diffuser configurations, as well as specifics on how measurements were conducted. This lack of transparency makes it challenging for others to replicate findings accurately, potentially leading to discrepancies across studies.

A critical concern is that researchers frequently rely on manufacturers' irradiance and power output data without independently verifying these figures using their own calibrated equipment. While manufacturers’ specifications provide a starting point, device variations and the complexity of irradiance measurements mean that independently verified data is essential to ensure reliability.

As Neuronic’s findings underscore—with intensity readings varying by up to 20x or by as much as 95% across different devices—researchers must be equipped to independently measure light output to improve transparency and replicability in the field. Ensuring detailed reporting on calibration, measurement setup, and instrument specifications will enable more accurate comparisons and foster a more robust body of research in light therapy.

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5. Conclusion: Bridging Measurement and Application in PBM

Measuring precisely and reliably in the near-infrared (NIR) light therapy is not only a scientific challenge but also a need for advancing the field of PBM. We measured light with two different spectrometers and three diffusers. Such an experiment is essential to help further understand the necessary development required to standardize how we measure light in PBM research. The results showed how the variations caused by diffusers can affect the different devices. It was promising to see the two spectrometers deliver comparable measurements. Among the key results discussed were direct LED irradiance (10.8 mW/cm²), average helmet irradiance (1.65 mW/cm²), and total helmet power (924 mW), which the performance parameters of the Neuradiant 1070. 

Another essential consideration is comparing irradiance across wavelengths, such as 810 nm and 1070 nm. As discussed, the longer wavelength of 1070 nm carries less energy per photon than shorter wavelengths. This fundamental part of light must be factored into dosage determinations. For instance, a study comparing 810 nm vs 1070 nm using the same irradiances for both wavelengths may not be accurate due to 810 nm having more photonic energy than 1070 nm. This would mean the 1070 nm would need more irradiance (or time) to deliver the same photonic energy. Esteves-Pereira et al., (2024) have been developing a dosage approach honouring Einstein’s work.

The emerging PBM dosimetry approach, coined as Einstein’s calculation of dosage equivalence, incorporates irradiance (mW/cm²) and irradiation time (seconds) to calculate fluence (J/cm²); however, it also considers the selected wavelength and associated photonic energy (eV) to provide photonic fluence (p.J/cm²) (also known as Einstein’s). This method could provide a valuable tool for bridging these differences, enabling researchers to standardize dosage comparisons based on photon energy and wavelength (Esteves-Pereira et al., 2024). For more information, please read Esteves et al.'s (2024) paper, which goes further into detail about Einstein’s and compares dosages dependent upon wavelength. Incorporating these adjustments is vital for ensuring accurate therapeutic dosages and optimizing the effectiveness of PBM treatments. Such nuanced approaches are paving the way for more precise and meaningful research outcomes, bringing the field closer to realizing the full potential of light therapy for health and wellness.

Transparency and accuracy remain core principles of our work at Neuronic. In our early stages, we relied on less sophisticated, cost-effective measurement equipment, which initially reported irradiances as high as 40 mW/cm². However, we later identified that these measurements were skewed by including thermal energy emitted by the source. This experience underscored the importance of utilizing high-quality instruments and refining our methodology to accurately represent our device's capabilities. Providing precise, reliable data is essential for advancing our understanding of NIR light therapy and fostering trust and credibility within the scientific and medical communities.

In conclusion, advancing the science and application of NIR light therapy requires a commitment to rigorous measurement practices, transparent reporting, and the adoption of emerging standards. By combining robust methodologies with clear communication of results, researchers and manufacturers can drive the development of effective, evidence-based applications. While perfecting measurement techniques may be complex, it is a foundational step toward unlocking the immense potential of PBM in improving health outcomes. We are excited to invest in further measurements and equipment to ensure photobiomodulation becomes more standardized and impactful in its application.

References

Blanco, N. J., Maddox, W. T., & Gonzalez‐Lima, F. (2017). Improving executive function using transcranial infrared laser stimulation. Journal of neuropsychology, 11(1), 14-25.

Esteves-Pereira, Thaís Cristina, Nimisha Rawat, René-Jean Bensadoun, Praveen R. Arany, and Alan Roger Santos-Silva. "How do clinicians prescribe photobiomodulation therapy (PBMT)? Harmonizing PBMT dosing with photonic fluence and Einstein." Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology 138, no. 6 (2024): 673-677.

Hamblin, M. R., & Huang, Y. Y. (Eds.). (2019). Photobiomodulation in the brain: Low-level laser (light) therapy in neurology and neuroscience. Academic Press.

Kochevar, L. (1987). Photophysics, photochemistry and photobiology. Dermatology in general medicine.

Rindner, E. S., Haroon, J. M., Jordan, K. G., Mahdavi, K. D., Surya, J. R., Zielinski, M. A., ... & Jordan, S. E. (2022). Transcranial infra