Methods for interval closed-loop adaptive transcranial photobiomodulation

Abstract

A method is provided for brainwave modulation using interval-based closed-loop adaptive transcranial photobiomodulation. The method utilizes biosensors, including electroencephalogram (EEG) sensors, to measure biosignals from the body and process the signals to adapt patterned light pulses to alter the brain's electrical activity. A system in the form of a wearable device, such as a headset, for implementing the method is also provided.

Description

[Technical field]

[0001] Related prior applications This application claims the benefit of priority from earlier filed U.S. Provisional Application No. 63 / 185,234. Images can be viewed under "Original Document."

[0002] The present invention relates to a method for modulating brainwaves using interval closed-loop adaptive transcranial photobiomodulation, in particular, a method for measuring biosignals from the body using biosensors, including electroencephalogram (EEG) sensors, and processing said signals to adapt patterned light pulses to induce photochemical changes in cellular structures and affect electrical activity of the brain. [Background technology]

[0003] Influencing biosignals from the body spans many disciplines and methods, including medicine, therapy, meditation, breathwork, biofeedback, neurofeedback, and biostimulation. Neurostimulation is a type of biostimulation that intentionally modulates nervous system activity. One such method of neurostimulation, known as photobiomodulation (PBM), uses modulated near-infrared light to stimulate the nervous system.

[0004] Photobiomodulation is a type of infrared therapy. Photobiomodulation is a type of infrared therapy. Infrared therapy has positive effects on the skin, metabolic processes, nervous system, and immune system. It has been shown to increase collagen production for healthier skin.

[0005] Photobiomodulation technology can stimulate mitochondria in cells through the propagation of energy. Within mitochondria, cytochrome oxidase has the ability to absorb red and near-infrared light and convert it into the energy adenosine triphosphate (ADT). Transcranial photobiomodulation systems often deliver light at wavelengths between 633 and 810 nanometers, with 810 nanometers being the ideal wavelength due to its ability to penetrate deeper into biological tissue.

[0006] Additionally, transcranial photobiomodulation is a neurotechnology used to modulate or change an individual's brain activity, producing perceptible changes in mental states that can be seen through changes in the brain's electrical activity. EEG states can be defined as the collective electrical activity of the brain over a period of time, which can then be categorized into mental states such as fatigue, focus, stress, creativity, etc.

[0007] Other forms of brain stimulation include, but are not limited to: ·tACS-Transcranial alternating current stimulation method ·tRNS - Transcranial Random Noise Stimulation ·tDCS-Transcranial Direct Current Stimulation

[0008] To date, transcranial photobiomodulation has been performed using static light or constant frequency light pulses. Recently, researchers have begun experimenting with varying the frequency of light within a stimulation session. Using different pulse frequencies has shown to result in different measured and subjectively felt effects reported by subjects. The various effects of pulsed light stimulation have yet to be fully elucidated. However, we propose that the effects are a direct result of varying the time brain cells are exposed to light energy. These effects are therefore a result of both the frequency and duty cycle of the light.

[0009] Existing methods have shown wide variability in results from person to person and over time within the same person, sometimes resulting in decreased brainwave activity and other times increased brainwave activity. Some people have also reported headaches, nausea, dizziness, and lightheadedness with existing tPBM techniques.

[0010] Light-based neurostimulation has been shown to be significantly different from electrical-based stimulation, and techniques used in existing electrical stimulation methods are not directly transferable to this field. Several studies have shown that photobiomodulation has a biphasic dose-response curve known as the Arndt-Schulz law (Figure 4). Low doses above a threshold are ineffective, while high doses result in bioinhibition of energy transfer. Penetration of light into biological tissues has also been shown to vary from person to person based on differences in skin and skull thickness, as well as hair. Importantly, in real-world settings where transcranial photobiomodulation (tPBM) is involved, measuring dose per square centimeter (J / cm2) is neither a direct measure of energy absorption nor a measure of dose to an individual person. The prior art also lacks an understanding of how changes in dose over time affect the Arndt-Schlz biphasic response curve. Prior art devices apply a consistent energy dose output to all subjects. These devices do not account for differences in energy penetration and absorption.

[0011] Some of the devices used have been reported to cause headaches, nausea, dizziness, and lightheadedness. Above the dose absorption limit, EEG power decreases, and the reported side effects are likely the result of exceeding the dose absorption limit for an individual.

[0012] Brain electrical activity is extremely complex. It can vary significantly from person to person, from moment to moment, and at different locations in the brain. Importantly, brain electrical activity, or EEG, can be considered to be a non-stationary signal. Prior art has demonstrated that tPBM techniques can alter EEG activity, but these attempts fail to account for the non-stationarity of the brain. Summary of the Invention

[0013] The present invention demonstrates a significant improvement over the prior art, which lacks the real-time closed-loop feedback mechanism used in the present invention to accommodate different individuals during a session, the same individual across multiple sessions, and non-stationarity of brainwaves. Known approaches fall further short because they either use static light or lack the complex pulse interval patterns defined in this manner. Said patterns are important for personalizing energy over time, independent of LED duty cycle and pulse frequency. Furthermore, the present invention can measure and account for individualized energy absorption rates, solving the prior art problems with headaches, nausea, dizziness, and lightheadedness.

[0014] The results of the tests carried out by the inventors and demonstrated in Figures 2 and 3 clearly show the ability of the present invention to increase targeted electroencephalographic activity, whereas the methods used in the prior art often do not result in a significant change from the pre-stimulation baseline, or even response inhibition, or result in a significant reduction in the power of the targeted electroencephalogram, as shown in Figure 3. The present invention relates to a method for measuring biosignals from the body using a biosensor, including one or more electroencephalogram (EEG) sensors, and processing said signals to adapt light pulses, where the light pulses are used to change the electrical activity of the brain. The biosensor and photobiomodulation light are placed on the body, and the sensor is used to establish a baseline of the biosignals over a period of time. Furthermore, the present invention measures the effect of photobiomodulation and makes adjustments to said stimulation in an automated manner, creating a closed-loop system.

[0015] The method of the present invention provides an improvement over known methods that do not account for non-stationarity in electroencephalographic activity and do not accommodate variations between individuals or over time within the same individual. [Brief description of the drawings]

[0016] [Figure 1] FIG. 1 is a diagram illustrating a mobile device and a computer system connected to a wearable headset according to one embodiment of the present invention. [Diagram 2] FIG. 2 is a graph showing EEG measurements before and after constant frequency transcranial photobiomodulation stimulation in a human. [Diagram 3] FIG. 3 is a graph showing EEG measurements before and after interval closed-loop adaptive transcranial photobiomodulation stimulation for a human, in accordance with an embodiment of the present invention. [Figure 4] FIG. 4 is a graph showing a dose-response curve for photobiomodulation. [Diagram 5] FIG. 5 is a graph showing peak alpha frequency during adaptive closed-loop transcranial photobiomodulation according to an embodiment of the present invention. [Figure 6] FIG. 6 is a graph showing peak alpha frequency without transcranial photobiomodulation. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0017] A detailed description of the invention will now be provided with reference to specific embodiments and the accompanying drawings. In one aspect, the invention provides an EEG sensor and Photobiomodulation (PBM) LEDs 7 in a head-mounted device 1 with headphones 2 and 6 as illustrated in FIG. 1. In the embodiment illustrated in FIG. 1, the headphones of the invention combine EEG (Electroencephalography) sensors 3, 4 and 5 for EEG measurements and a PPG (Phoplethysmography) sensor 8 for heart rate and heart rate variability (HRV) measurements in a wearable head-mounted device with headphones. The PPG sensor 8 may be integrated inside an over-ear headphone design that reduces ambient noise and allows high accuracy. The invention provides a wearable head-mounted headphone set 1 incorporating a biosensor that collects physiological signals from a user. The device includes Bluetooth (wireless) audio and data transmission 12 that may be used to connect the devices 1 and 2 to a control unit, which may be a smartphone or mobile device 9 with a graphic touch screen display 10, said control unit 9 having a wireless wi-fi connection with a remotely located master control unit, which may be a computer 11. Device 1 may also include a rechargeable battery, a speaker, and a microphone.

[0018] The present invention utilizes various photobiomodulation LEDs positioned at FZ, F3, F4, CZ, PZ, P3 and P4 according to the International 10-20 positioning system. The present invention further utilizes EEG recorded from locations including Fz, Cz and Pz according to the International 10-20 positioning system. In other embodiments, additional or alternative LED and EEG sensor placements may be utilized.

[0019] In this method, a target brainwave pattern is selected for a photobiomodulation session. In one embodiment, a person selects a desired pattern based on a desired outcome. In another embodiment, a technician assisting the person can select the target pattern, and in yet another embodiment, the system automatically selects or suggests a target brainwave pattern based on the person's current biometric measurements. Here, the selected pattern represents one or more target frequencies and one or more target locations. For example, the patterns can include 10 Hz at locations Pz, P3, and P4, 40 Hz at locations FZ, F3, F4, CZ, Pz, P3, and P4. The target brainwave pattern can correspond to a target state, such as, for example, calm, focus, or meditation.

[0020] A wearable device with an EEG sensor and tPBM LEDs is then placed on the head. The person initiates the session using the control unit. In one embodiment, the device can detect that it is on the person's head and automatically initiate the session. The device wirelessly transmits biosignal data to the control unit, where the biosignal data includes EEG signal data from one or more locations on the person's brain. The control unit applies various signal processing techniques to the biosignal data. Signal processing may include various techniques known to those skilled in the art, including noise filters (i.e. low pass, high pass, etc.) and analysis techniques (i.e. Fourier transform, wavelet analysis, etc.). The processed data is used to establish the person's baseline levels, including but not limited to average band power and peak band frequency. Here, the EEG bands include delta, theta, alpha, alpha-theta, low beta, mid meta, high beta, and gamma.

[0021] The control unit then determines a light pulse pattern at each light location based on the baseline biometric level and the target brainwave pattern, and the device applies the pulse pattern to the LED. In this method, the light pulse pattern is configured as follows: 1.1 or higher LED position. 2. LED duty cycle. 3.LED power output. 4. Light Pulse Frequency, the light is pulsed on and off at a predetermined frequency. 5. Light Pulse Duration, the light is pulsed at a predetermined frequency for a specified duration. 6. Light pulse gap duration, the light pulse is paused following the light pulse duration. 7. Repetition duration: the sequence of light pulses and gaps is repeated for a specified duration. 8. Rest Interval, after the repeat duration the pattern is paused for a predetermined period of time.

[0022] The control unit and device can adjust the energy dose output over time by varying the LED power output, the LED duty cycle, and by utilizing light pulse gaps and pause intervals. The light pulse gap duration and pause intervals provide the important advantage of giving the human brain time to convert the absorbed energy and stabilize within the individual's dose absorption limits. This further allows for the use of higher energy LEDs that penetrate deeper into biological tissue. Ultimately, this allows for control of dose over time without changing the duty cycle, since the combination of the LED pulse frequency and duty cycle affects the cellular exposure time during each light pulse.

[0023] The device and control unit continuously evaluate the person's biosignals utilizing various signal analysis and classification techniques. In one embodiment, the control unit monitors the person's EEG power and dose-response curve (FIG. 4). Here, the control unit maps the person's energy absorption to the dose-response curve based on the trend and slope of the EEG power levels. Here, the slope of the person's EEG power increases and decreases relative to the dose-response curve.

[0024] In another embodiment, the peak alpha frequency is recorded during the baseline period. In this embodiment, the control unit maps the person's energy absorption to a dose-response curve based on the trend and slope of the peak alpha frequency. An increase to the peak alpha frequency is mapped to the dose-response curve and corresponds to continued absorption of the tPBM stimulation, while a decrease indicates the end of the peak dose-response curve, as the slope of the person's peak alpha frequency changes.

[0025] In yet another embodiment of the present invention, one or more other biomarkers can be used to map and measure the dose-response curve of tPBM stimulation, including heart rate (HR), heart rate variability (HRV), pulse volume, respiratory rate, galvanic skin response (GSR), EEG synchrony, EEG amplitude, relative EEG power, and total EEG power.

[0026] In a preferred embodiment, the control unit adapts the light pulse pattern at each light location based on the dose-response curve, the target brainwave pattern, EEG power, peak band frequency, baseline bioinformation level, and subsequent changes in the bioinformation signal. The system repeats this process during the photobiomodulation session. The control unit increases or decreases the tPBM dose over time based on the dose-response curve detected based on the person's mapped bioinformation levels. The control unit further determines that the person has reached the top of the dose-response curve (FIG. 4), as indicated by the bioinformation levels flattening. In this embodiment, the control unit stops the tPBM session when the top of the dose-response curve is reached. In an alternative embodiment, the device and the control unit may be the same physical device. In another embodiment, the control unit sends the raw signal data to a central master control unit for signal processing. The master control unit may be a central server where the adaptation is based on multiple photobiomodulation sessions. Here, the system learns to adapt to the individual's optimal dose-response curve over time.

[0027] In one embodiment, the present invention can include one or more additional biosensors, such as body temperature, heart rate, heart rate variability, respiration rate, blood oxygen level (SPO2), respiration rate, and blood pressure, which may be used by the system to further inform adaptation of the light stimulation interval.

[0028] In another embodiment, the light pulse pattern can include a range of light pulse frequencies, gaps, and repetition durations. In yet another embodiment, all of the photobiomodulation lights are operated simultaneously using the same light pattern. In another embodiment, each photobiomodulation light can be operated independently or in groups with a given light pattern.

[0029] In yet another embodiment, the system can utilize historical biometric data collected over time in addition to the person's current biometric signal to establish a baseline level. Additionally, the system can learn how an individual responds to changes in light stimulation patterns over time and incorporate these learnings in real-time when adapting light patterns.

[0030] In yet another variation, the system can include a server and database, and learnings from many different users' sessions are used to adapt the light pulse patterns. In this version, the system can include machine learning algorithms that determine how to adapt the light patterns.

[0031] Reference will now be made to various examples and a comparison of the method of the present invention with conventional approaches.

[0032] Referring to FIG. 2, the graph shows that EEG amplitude was significantly reduced using the stimulation method. Data was collected in the 8-12 Hz range (alpha band) at the PZ position of the head based on a 10-20 placement system, where the first 60 seconds of baseline was used to establish the decibel range using a base 10 logarithmic scale. Four minutes of pre-stimulation data was then collected, followed by 10 minutes of constant frequency stimulation using a frequency of 10 Hz, after which four minutes of post-stimulation data was collected. FIG. 2 can be directly compared to FIG. 3.

[0033] Referring to FIG. 3, the graph shows that EEG amplitude was significantly increased using the stimulation method. Data was collected in the 8-12 Hz range (alpha band) at the PZ position of the head based on a 10-20 placement system. Here, the first 60 seconds of baseline was used to establish the decibel range using a base 10 logarithmic scale. Then, 4 minutes of pre-stimulation data was collected, followed by 10 minutes of interval closed-loop adaptive stimulation using a light pulse frequency of 10 Hz, after which 4 minutes of post-stimulation data was collected. FIG. 3 can be directly compared to FIG. 2.

[0034] As previously discussed herein, Figure 4 shows a dose-response curve for photobiomodulation. Thus, the methods of the present invention seek to terminate adaptive transcranial photobiomodulation at or near peak absorption through the use of closed-loop techniques.

[0035] 5 and 6 illustrate the utility and effectiveness of adaptive closed-loop transcranial photobiomodulation according to the inventive methods disclosed herein. As can be seen by examining these graphs, peak alpha frequency is significantly improved using adaptive closed-loop techniques. Peak alpha frequency has been correlated with cognitive performance based on research.

[0036] The disclosure provided herein is intended to provide exemplary embodiments of the claimed invention, but is not intended to be exclusive or exhaustive. Those skilled in the art will recognize that variations of the claimed devices and methods are possible without departing from the scope of the claimed invention.

Claims

1. Measuring a biosignal of an individual using a biosensor; processing the biological signal; and adapting photobiomodulation based on the processed biosignal; providing photobiomodulation to the individual; and generating a biofeedback loop in which the photobiomodulation is adapted to move the biosignals of the individual toward a goal state; 16. A method for adaptive transcranial photobiomodulation, comprising:

2. The biosensor is one or more of an EEG, a PPG sensor, an EKG sensor, and a galvanic skin response sensor; The method of claim 1.

3. The biosignals are measurements of one or more electrical and optical signals that change based on activity from the brain, heart, blood, and skin. The method of claim 2.

4. Measuring the biosignal includes determining a baseline biosignal of the individual. The method according to claim 3.

5. The baseline biosignal may be one or more of band power, peak band frequency, galvanic skin response, blood oxygen level, pulse rate, heart rate, and heart rate variability. The method according to claim 4.

6. providing the individual with a head-mounted wearable device comprising the biosensor, at least one light source for the photobiomodulation light pulses, and a control unit. The method according to any one of claims 1 to 5.

7. the target state is set by a user or technician input to the control unit or is independently selected by the control unit; The method according to claim 6.

8. The adapting of the photobiomodulation to bring the biosignal closer to the target state is accomplished by modulating one or more attributes of the photobiomodulation and evaluating an effect on the measured biosignal. The method of claim 1.

9. The modulated attributes of the photobiomodulation may include one or more of LED position, LED duty cycle, LED power, pulse frequency, pulse duration, pulse gap duration, repetition duration, and pause interval; The method according to claim 8.

10. The adaptation of the photobiomodulation is achieved by referencing changes in baseline metrics and creating a feedback loop to move EEG band power or peak band frequency closer to a target state.

10. The method according to claim 8 or 9.

11. The adaptation of the photobiomodulation is accomplished by referencing changes in baseline indices and creating a feedback loop to bring brain or heart band power, peak band frequency, galvanic skin response, blood oxygen level, pulse volume, heart rate, or heart rate variability closer to a target state.

10. The method according to claim 8 or 9.

12. the head-mounted wearable device further comprising a wireless communication modality enabling control of the head-mounted wearable device by a smartphone or other wireless-enabled device; The method according to claim 6.

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