Systems and methods for adjusting circadian phase of a patient

Abstract

Disclosed herein are systems and methods for providing a light treatment to a patient in need thereof. The method may include determining a circadian phase of the patient and determining a light treatment based on a desired circadian phase of the patient.

Description

PATENT Atty Docket: 093698-822897 Via Patent Center SYSTEMS AND METHODS FOR ADJUSTING CIRCADIAN PHASE OF A PATIENT CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Application No. 63 / 539,341, filed September 20, 2023, the entire contents of which are incorporated herein by reference in their entirety. FIELD

[0002] The present disclosure relates to systems and methods for determining a circadian phase of a patient and providing a light treatment based on a desired circadian phase of the patient. GOVERNMENT SUPPORT

[0003] This invention was made with government support under W911NF2110183 awarded by the Department of the Army. The government has certain rights in the invention. BACKGROUND

[0004] Modeling how patterns of light and darkness affect circadian phase is important both clinically and organizationally because circadian disruption can compromise health and performance. Limit-cycle oscillator models in various forms have been used to characterize phase changes to a limited set of light interventions. Oscillator based models such as the van der Pol oscillator-based model (Kronauer99) used a well-established framework from experimental psychology whereby the stimulus (S) acts on the organism (O) to produce a response (R). However, the Kronauer99 model only predicts circadian phase within one hour of a patient’s actual circadian phase. This prediction uncertainty causes many problems when attempting to change a patient’s circadian phase using a light treatment.

[0005] Within the last decade, more than 100 new clinical trials have emerged studying the effect of light on various clinical conditions. There is emerging evidence that delivering circadian effective light at the right time plays a role in the health and wellness of patients. Further, there is evidence that circadian light delivery at the right time impacts the therapeutic effectiveness of a drug as light impacts internal circadian rhythm and thus hormonal balance. Page 1 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center

[0006] Therefore, there is a need for systems and methods to accurately specify and administer circadian light treatments. SUMMARY OF INVENTION

[0007] The present application relates to a method of determining a light treatment for a patient in need thereof. The method may include determining a circadian phase of the patient and determining the light treatment to adjust the determined circadian phase. In an aspect, the light treatment includes an amount, a duration, and a clock time relative to the determined circadian phase of light for the light treatment. In an aspect, the method includes administering the light treatment. In an aspect, determining the circadian phase of the patient may include monitoring, using at least one calibrated photometric device, a plurality of light exposures of the patient during at least one monitoring period of 24 hours, and / or determining a biomarker relative to clock time of the patient. In an aspect, the light exposures may be measured as irradiance at a cornea of the patient using any metric traceable to circadian effective light based on CLA. In an aspect, the biomarker determines DLMO and / or CBTmin.

[0008] In an aspect, the at least one calibrated photometric device is a Daysimeter. In an aspect, the at least one photosensor is located on a wrist, a torso, a chest, or a head of the patient. In another aspect, the light treatment is exposure to or protection from circadian effective light. In an aspect, the light treatment predictably changes the determined circadian phase of the patient to a desired circadian phase. In an aspect, the light treatment is outdoor light exposure. In an aspect, the light treatment comprises limiting exposure to light. In another aspect, a photopic illuminance traceable to CLA of “white” light delivered at eye level for the light treatment with electric room lighting is between 0 lux and 1,000 lux. In an aspect, the duration of the light delivered for the light treatment is about 1 hour, about 2 hours, about 3 hours, about 4 hours, about 5 hours, or about 6 hours. In an aspect, the amount of light determines the duration and clock time of the light for the light treatment, or vice versa.

[0009] In an aspect, the amount of light is 700 lux and the duration is 30 minutes. In another aspect, the amount of light is 350 lux and the duration is 1 hour. In an aspect the light treatment is any light or dark exposure having a circadian stimulus (CS) between 0.01 and 0.7. In an aspect, the light treatment is pure blue light provided by a pure blue light LED having a wavelength of peak emission of about 470 nm, a full- Page 2 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center width-half-maximum bandwidth of 20 nm and an irradiance of 0.5 W / m2. In an aspect the light treatment has a CLA of 0 to 1000. In an aspect, the amount of the light is 0 to about 1000 as specified in terms of CLA. In another aspect, the method further includes determining the effect of an amount, duration, and clock time of a light or dark exposure on the patient’s determined circadian phase. In another aspect, the clock time, the duration, and the amount of the light delivered for the light treatment is based on the determined circadian phase of the patient and a desired circadian phase.

[0010] In various aspects, the light treatment re-aligns circadian phase as per patient’s preset goal to potentially improve population specific health outcomes including inflammation, neutropenic fever, and symptom burden of a multiple myeloma patient. In another aspect, the light treatment comprises a 24 hour light / dark exposure plan. In another aspect, the 24 hour light / dark exposure plan comprises a plurality of circadian effective lighting exposures and a plurality of circadian dark exposures. In an aspect, the light treatment comprises light from naturally available daylight or an electrically powered ambient lighting device, as per patient’s preference. In an aspect, the light treatment is provided by a white light having a correlated color temperature of about 2200 K to about 7500 K. In an aspect, the light treatment is provided by a narrowband light source having a peak wavelength of about 380 nm to about 730 nm. In an aspect, the light treatment is tailored and administered at a time of day preferred by the patient from 12 AM to 11:59 PM.

[0011] In various aspects, the light treatment is administered to the patient at eye level. In an aspect, the light treatment comprises a circadian effective light period for 0 hours to 24 hours. In another aspect, the light treatment comprises a circadian dark period for 0 hours to 24 hours. In an aspect, the light treatment improves sleep and mood of patients with Alzheimer’s disease. In an aspect, the light treatment comprises polychromatic white light and / or narrowband light capable of stimulating a circadian system. In another aspect, the clock time is in the morning, the afternoon, the evening, the night, or a combination thereof. In an aspect, the method further includes determining a new circadian phase of the patient at least one day after the light treatment has been administered.

[0012] In another aspect, the light treatment is administered every day beginning at the clock time. In an aspect, the patient has an age of about 1 years old to about 95 years old. In an aspect, the light treatment is provided by a lighting device. In an Page 3 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center aspect, the lighting device is a light box, a light mask, wearable light goggles, and LED strip, or a self-luminous tablet.

[0013] Further provided herein is a non-transitory computer readable medium storing instructions thereon that when executed by at least one processor cause the at least one processor to perform operations to determine a light treatment for a patient in need thereof. The operations may include determining a circadian phase of the patient and determining the light treatment to adjust the determined circadian phase. In an aspect, the light treatment includes an amount, duration, and clock time relative to the determined circadian phase of light for the light treatment. In an aspect, the operations further include administering the light treatment. In another aspect, determining the circadian phase of the patient includes receiving, using at least on calibrated photometric device, a plurality of light exposures of the patient during at least one monitoring period of 24 hours and / or receiving a biomarker relative to clock time of the patient. In an aspect, the light exposures are measured as irradiance at a cornea of the patient using any metric traceable to circadian effective light based on CLA.

[0014] In various aspects, the biomarker relative to the clock time determines DLMO and / or CBTmin. In another aspect, the at least one calibrated photometric device is a Daysimeter. In an aspect, the at least one photosensor is located on a wrist, a torso, a chest, or a head of the patient. In another aspect, the light treatment is exposure to or protection from circadian effective light. In an aspect, the light treatment predictably changes the determined circadian phase of the patient to a desired circadian phase. In an aspect, the light treatment is outdoor light exposures. In another aspect, the light treatment comprises limiting exposure to light.

[0015] In various aspects, a photopic illuminance traceable to CLA of “white” light delivered to at eye level for the light treatment with electric room lighting is between 0 lux and 1,000 lux. In another aspect, the duration of the light delivered for the light treatment is about 1 hour, about 2 hours, about 3 hours, about 4 hours, about 5 hours, or about 6 hours. In another aspect, the amount of light determines the duration and clock time of the light for the light treatment, or vice versa. In an aspect, the amount of light is 700 lux and the duration is 30 minutes. In an aspect, the amount of light is 350 lux and the duration is 1 hour.

[0016] In an aspect, the light treatment is any light or dark exposure having a CS between 0.01 and 0.7. In another aspect, the light treatment is pure blue light provided Page 4 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center by a pure blue LED having a wavelength of peak emission of about 470 nm, a full- width-half-maximum bandwidth of 20 nm and an irradiance of 0.5 W / m2. In an aspect, the amount of the light is 0 to about 1000 as specified in terms of CLA. In an aspect, the operations further include determining the effect of an amount, duration, and clock time of a light or dark exposure on the patient’s determined circadian phase. In an aspect, the clock time, the duration, and the amount of the light delivered for the light treatment is based on the determined circadian phase of the patient and a desired circadian phase. In an aspect, the light treatment re-aligns circadian phase as per patient’s preset goal to potentially improve population specific health outcomes including inflammation, neutropenic fever, and symptom burden of a multiple myeloma patient. In an aspect, the light treatment comprises a 24 hour light / dark exposure plan. In another aspect, the 24 hour light / dark exposure plan comprises a plurality of circadian effective lighting exposures and a plurality of circadian dark exposures. In an aspect, the light treatment comprises light from naturally available daylight or an electrically powered ambient lighting device, as per patient’s preference. In another aspect, the light treatment is provided by a white light having a correlated color temperature of about 2200 K to about 7500 K.

[0017] In various aspects, the light treatment is provided by a narrowband light source having a peak wavelength of about 380 nm to about 730 nm. In another aspect, the light treatment is tailored and administered at a time of day preferred by the patient from 12 AM to 11:59 PM. In an aspect, the light treatment is administered to the patient at eye level. In an aspect, the light treatment comprises a circadian effective light period for 0 hours to 24 hours. In another aspect, the light treatment comprises a circadian dark period for 0 hours to 24 hours. In another aspect, the light treatment improves sleep and mood of patients with Alzheimer’s disease. In another aspect, the light treatment comprises polychromatic white light and / or narrowband light capable of stimulating a circadian system.

[0018] In various aspects, the clock time is in the morning, the afternoon, the evening, the night, or a combination thereof. In an aspect, the operations may include determining a new circadian phase of the patient at least one day after the light treatment has been administered. In an aspect, the light treatment is administered every day beginning at the clock time. In an aspect, the patient has an age of about 1 years old to about 95 years old. In an aspect, the light treatment is provided by a Page 5 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center lighting device. In an aspect, the lighting device is a light box, a light mask, wearable light goggles, and LED strip, or a self-luminous tablet. In an aspect, the operations further include turning on a lighting device to administer the light treatment. In another aspect, the operations further include providing an alert to the patient indicating it is time for the light treatment. In another aspect, the operations further include providing an audible alert to the patient that it is time for the light treatment. In another aspect, the operations further include providing feedback to the patient of the amount of light, duration of light, and clock time of light via a display. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] For a more complete understanding of this disclosure and its features, reference is now made to the following description, taken in conjunction with accompanying drawings, in which like reference numerals denote like elements:

[0020] FIG.1 is a graphical illustration of the 24-hour profiles for melatonin, cortisol, alpha amylase, and core body temperature (CBT) under constant dark conditions, the biomarker clock time profile for dim light melatonin onset (DLMO) and the minimum core body temperature (CBTmin).

[0021] FIG. 2A is a graphical illustration of different narrowband light sources for suppressing nocturnal melatonin and predictions from a two-state circadian phototransduction model at 300 scotopic lux on the retina.

[0022] FIG. 2B is a graphical illustration of the absolute sensitivity for the human circadian system as characterized by light-induced nocturnal melatonin suppression.

[0023] FIG.3A is a bar graph of the mean absolute error (MAE) across four data sets with a modulator and without a modulator.

[0024] FIG.3B is a bar graph of the percent of subjects with MAE < 1 hour across four data sets with and without a modulator.

[0025] FIG.4 is a graphical illustration of the effect of changing CBTmin to an optimum CBTmin across four data sets.

[0026] FIG. 5 is a graphical illustration of changing Process L parameters on MAE across four data sets.

[0027] FIG. 6 is a graphical illustration of changing Process L parameters on percentage of subjects with error < 1 hour across four data sets. Page 6 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center

[0028] FIG.7 is a graphical illustration of changing Process P parameters on MAE across four datasets.

[0029] FIG. 8 is a graphical illustration of changing Process P parameters on percentage of subjects with error < 1 hour across the four datasets.

[0030] FIG. 9A is a graphical illustration of a phase response curve for the Kronauer99 model with photopic illuminance as light stimulus input.

[0031] FIG.9B is a graphical illustration of a phase response curve using circadian stimulus (CS) as light stimulus input.

[0032] FIG.10 is a diagram of a pacemaker model in one example.

[0033] FIG.11 is a flowchart for a method of adjusting the circadian phase of a patient in one example.

[0034] FIG.12 is a diagram of an example computing system in one example. DETAILED DESCRIPTION

[0035] It will be appreciated that for simplicity and clarity of illustration, where appropriate, reference numerals have been repeated among the different figures to indicate corresponding or analogous elements. In addition, numerous specific details are set forth in order to provide a thorough understanding of the examples described herein. However, it will be understood by those of ordinary skill in the art that the examples described herein can be practiced without these specific details. In other instances, methods, procedures, and components have not been described in detail so as not to obscure the related relevant feature being described. Also, the description is not to be considered as limiting the scope of the embodiments described herein. The drawings are not necessarily to scale and the proportions of certain parts may be exaggerated to better illustrate details and features of the present disclosure.

[0036] Several definitions that apply throughout the above disclosure will now be presented. The term “coupled” is defined as connected, whether directly or indirectly through intervening components, and is not necessarily limited to physical connections. The connection can be such that the objects are permanently connected or releasably connected. The term “substantially” is defined to be essentially conforming to the particular dimension, shape or other word that substantially modifies, such that the component need not be exact. The terms “comprising,” Page 7 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center “including” and “having” are used interchangeably in this disclosure. The terms “comprising,” “including” and “having” mean to include, but not necessarily be limited to the things so described.

[0037] As used herein, “about” refers to numeric values, including whole numbers, fractions, percentages, etc., whether or not explicitly indicated. The term “about” generally refers to a range of numerical values, for instance, ± 0.5-1%, ± 1-5% or ± 5- 10% of the recited value, that one would consider equivalent to the recited value, for example, having the same function or result.

[0038] The terms “pacemaker,” “pacemaker prediction,” and “pacemaker model” are used interchangeably in this disclosure to define a model for predicting a circadian phase of a human.

[0039] Disclosed herein is a method of determining a light treatment for a patient in need thereof. The light treatment may be configured to adjust the circadian phase of a patient to a desired circadian phase. Over 90% of human beings spend 90% of their time indoors causing a wide variety of light-dark exposures leading to disrupted behavior and physiology that can be asynchronous with other people in the same location. Provided herein is a method to determine a light treatment for a patient to adjust the circadian phase of the patient.

[0040] The timing of human behavior and physiology is regulated by internal clock mechanisms. Various rhythmic behavioral (e.g., sleep) and physiological (e.g., melatonin) responses will cycle with a period of approximately 24 hours and are known as circadian (approximately daily) rhythms. These rhythms are, in part, regulated by different peripheral clocks in various organs and neural structures. These peripheral clocks each have slightly different intrinsic periods and would be, therefore, asynchronous with differently timed peaks and troughs without a master clock that orchestrates them all so that human behavior and physiology work in concert.

[0041] The master clock located in the suprachiasmatic nuclei (SCN) sends neural signals to other parts of the brain which then send humoral signals to the peripheral clocks. The phase changes in the core body temperature (CBT) are modulated by a rhythmic input from the SCN acting upon the thermoregulatory centers within the hypothalamus, in turn modulating the set point and altering the thresholds for sweating and cutaneous vasodilation. In humans, a circadian rhythm of heat loss from the distal limbs is evident, wherein the daily profiles of skin temperature and blood flow in these Page 8 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center regions peak in the late evening before gradually declining to reach a minimum in the morning. Similarly, the SCN closely regulates melatonin synthesis by the pineal gland. Melatonin levels are high during the night and low during the day in both nocturnal and diurnal animals, as illustrated in FIG. 1. Melatonin down-regulation acts as an extension of the master clock, signaling time of the day to the body.

[0042] This orchestration of peripheral clocks by the SCN enables humans to perform complicated functions at the correct, coordinated times. Indeed, these clocks are necessary for survival. However, without some consistent, repetitive external timing stimulus, or zeitgeber, the SCN would “free run” and every person in society would perform their behavioral and physiological functions at different times. Prey and predators would be unpredictably available, as would reproductive partners. Indeed, without synchronized master clocks, it would be difficult for us to survive as a species. The primary zeitgeber for all terrestrial species is sunrise and sunset, that is, the natural 24-h light-dark cycle.

[0043] The intrinsic period of the SCN varies across individuals. For humans spending most of their time outdoors, these various intrinsic periods will be naturally synchronized by the 24-h light-dark cycle entering the eyes. Indeed, a robust, 24-h light-dark cycle is the primary zeitgeber for human master clocks. For humans who do not spend most of their time outdoors -- that is, for nearly 90% of humans -- light-dark exposure patterns can vary considerably, thus leading to disrupted behavior and physiology that can be asynchronous with other people in the same location. Modeling how light and dark affect circadian timing, particularly irregular or aperiodic patterns of light and dark, is important clinically and organizationally (e.g., the military) because “circadian disruption” can compromise health and performance.

[0044] To model changes in circadian phase, it is necessary to quantitatively address three domains. First, the light stimulus (S) for regulating the timing, or phase of the master clock must be defined. The master clock in humans, itself, does not receive direct light stimulation. The actual neural stimulus to the master clock must be processed by the retinae, converting photons into neural signals that are then conducted to the SCN via the retinohypothalamic tract (RHT). The retina is a complicated structure, combining photoreceptor responses into different neural pathways, one of which reaches the SCN. Thus, a model of retinal phototransduction will aid in a more accurate model of the stimulus (S) as it affects the master clock. Page 9 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center

[0045] Second, it is important that the phase response (R) of the SCN to the light stimulus is measured. Since, however, it is not possible to record the human SCN responses in situ, downstream measures of circadian phase are relied on, such as changes in dim light melatonin onset (ΔDLMO) or changes in minimum core body temperature (ΔCBTmin).

[0046] Between the stimulus and response is the organisms' (O) clock mechanism, which is the central focus of the model for predicting circadian phase of the patient and thereby providing an effective light treatment to the patient.

[0047] It is necessary to define the spectral and absolute sensitivities of the human retina to light as it signals photic information to the SCN. In terms of spectral sensitivity, the photopic luminous efficiency function V(λ) used to define “light” in commercial lighting is inappropriate for characterizing “light” for the circadian system. V(λ) represents the combined action spectrum of the middle-wavelength (M) cone sensitivity and the long- wavelength (L) cone sensitivity of the human macula, peaking at 555 nm. The peak spectral sensitivity of the circadian system, as measured by acute melatonin suppression, is at or near 460 nm. There is no single photoreceptor that peaks at 460 nm, as illustrated in FIG. 2A. Of particular note, the intrinsically photosensitive retinal ganglion cells (ipRCGs), the axions which form the RHT connecting the retina to the SCN, cannot account for the peak spectral sensitivity at 460 nm because the in vivo ipRGC photopigment, melanopsin, exhibits an action spectrum peaking at or near 490 nm (after being filtered by the crystalline lens). Utilizing all five retinal photoreceptors, together with a neural circuit consistent with orthodox retinal neurophysiology, provides a more accurate, but non-linear characterization of the spectral sensitivity of the circadian system. Importantly, the non-linear aspects of observed responses may need a model having different retinal phototransduction circuit pathways depending on the stimulus and resulting in different spectral sensitivity to polychromatic and narrowband light sources. Model predictions of spectral sensitivity at one scotopic (rod spectral sensitivity) light level for both narrowband and polychromatic sources are shown in FIG.2A.

[0048] There are several other aspects of the modeled spectral sensitivity. First, the blue versus yellow (b-y) spectral opponent mechanism, underlying one channel of human color vision, is an important element of the modeled retinal circadian phototransduction circuit. This spectral opponent mechanism results in a two-state model, one state for “cool” sources where the spectral power distribution of the source results in a channel response of b > y, and the other for “warm” sources where the same channel Page 10 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center response is b ≤ y. Thus, there are two spectral sensitivity functions for polychromatic sources shown in FIG. 2A. Second, subadditivity is a characteristic of the circadian phototransduction circuit for “cool” sources as illustrated by the negative lobe in FIG.2A. For example, the response of the circuit to a narrowband light source of 460 nm will be reduced if a 530 nm narrowband light source is added to the photic stimulus. Subadditivity is a direct consequence of the response by the b-y spectral opponent mechanism where adding a “yellow” light to a “blue” light may make the light appear less bright and achromatic (neither blue nor yellow). Equation A1.1 mathematically describes circadian-effective light (CLA 2.0) based on the modeled spectral sensitivity of the human circadian phototransduction circuit, which includes the b-y spectral opponent mechanism shared with the visual system.

[0049] stimulus activating the SCN than nocturnal mammals. To model this behavior, a retinal mechanism called shunting inhibition is used. The high threshold results from rod activation of a specific type of amacrine cell. The modeled electrical shunt limits direct Page 11 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center depolarization of the ipRGC in response to photon absorption and thereby, from sending any neural signals to the SCN. In contrast, rods provide direct input to the ipRGC in nocturnal rodents, resulting in high sensitivity to light of the circadian phototransduction circuit. Another feature of the model is the compression of neural response to light at high levels. FIG.2B illustrates the model predictions for different light levels, ranging from outdoors at night, to residential interiors, to commercial interiors, to outdoors during the day as a function of optical radiation spectrally weighted by CLA 2.0. Equation A1.2 mathematically describes the circadian stimulus (CS) to the human SCN.

[0050] Most pacemaker models use photopic illuminance (lux) as input (S). In instances where only one light source is used, inaccurate characterization of spectral sensitivity is not important because the relative effectiveness of different light sources is irrelevant. Thus, only the amount of light needed to stimulate the pacemaker is relevant, irrespective of the units used to characterize the photic stimulus. Even for instances where different “white” polychromatic lights generated by commercial light sources were used, the error in characterizing V(λ) is small, particularly when the amount of light is quite large with respect to dim baseline conditions. In other words, where “white” lights are used differences in their relative spectral power distribution are less important than differences in their absolute spectral power distribution. Where narrowband light sources are used, however, erroneous characterization of the spectral sensitivity of the system can lead to larger errors.

[0051] For example, the efficacy of a “blue” light for stimulating the SCN can be several orders of magnitude greater than that of a “red” light of the same photopic illuminance at the eye. A direct comparison is made between spectrally weighting the photic stimuli in terms of CLA 2.0, the spectral sensitivity of the circadian phototransduction mechanism in the eye, and in terms of V(λ), the combined spectral sensitivity of the M- and L-cones.

[0052] A function that compresses the raw spectrally weighted irradiance, usually photopic illuminance, as S input may be used in the pacemaker model. As illustrated in FIG. Page 12 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center 2B, CS is a biophysically grounded compressive function of spectrally weighted irradiance, CLA 2.0. Thus, a separate, arbitrary compressive function of spectrally weighted irradiance [e.g., V(λ) or CLA] is obviated. Because CLA 2.0 and CS are grounded in the neurophysiology of the retina, these characterizations of the photic stimulus (S) to the pacemaker (O) are inherently better than a pacemaker model that utilizes an arbitrary compressive function for photopic illuminance or even for irradiance spectrally weighted by a different function such as CLA.

[0053] The daily rhythm of melatonin concentration is currently the most acceptable marker of circadian phase and is widely used because it can be reliably assayed in blood, saliva, or urine. Dim light melatonin onset (DLMO) usually gets precedence over other circadian phase markers because it exhibits relatively greater robustness in the wake of various external influences. For instance, too much carbohydrate intake can significantly affect CBT and heart rate rhythms. Inherent changes to CBT are further essential to trigger master clock mediated immune response to any external threats that may compromise immune health. Cortisol and CBT parameters can also be masked by sleep, stress, and activity. On the other hand, melatonin concentration and secretion remain relatively uninfluenced by these factors. This also accords greater reliability for melatonin, over other circadian markers, to track circadian phase position.

[0054] The method described herein uses novel techniques for pacemaker models known in the art to determine more accurate circadian phase predictions and therefore more effective light treatments to shift circadian phase. In some examples, the pacemaker models known in the art may be modified to use various parameters described herein. The pacemaker model may use CS as photic input (l). The equations for CLA 2.0 and CS are mathematically described above. The importance is the use of circadian effective lighting based on CS to adjust the circadian phase of the patient, as well as making accurate estimates of the relevant clock time of the circadian phase. The pacemaker model described herein can predict the effect of light and dark exposures, as quantified in terms of CS, within 30 minutes of a patient’s actual circadian phase.

[0055] FIG.11 illustrates a method 1100 for determining a light treatment for a patient in need thereof. At block 1102, the method 1100 may include determining a circadian phase of the patient. Determining the circadian phase of the patient may include taking biological samples from the patient to measure the response (R) of the patient. These biological samples may be any biological sample that is operable as a marker for Page 13 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center circadian phase. For example, the biological sample may be blood, saliva, or urine. The biological sample of the patient may be used to determine the daily rhythm of melatonin content. In some examples, dim light melatonin onset (DLMO) may be used as the marker for circadian phase. DLMO may be the preferred marker for determining the circadian phase of the patient. In other examples, the marker for circadian phase of the patient may be cortisol or CBT (core body temperature). In further examples, the marker for circadian phase of the patient may be any biomarker known to determine circadian phase. These circadian phase markers may be used to determine the original (e.g., initial) circadian phase of the patient. In some examples, the DLMO value may be converted to a CBTmin value using the Equation 1: DLMO = CBTmin – 7 hours (1)

[0056] Furthermore, the DLMO may determine the baseline CBTmin of a patient for use in a pacemaker model. The use of a baseline CBTmin in a pacemaker model increases the accuracy of the pacemaker model predictions. In other examples, the initial phase may be estimated using a patient’s sleep / rest pattern.

[0057] The method may include determining a desired circadian phase (e.g., preset goal) for the patient. For example, humans who spend most of their time indoors may have disrupted circadian phases due to inadequate light exposures during daytime or light exposures occurring during the night. These circadian disruptions can have negative effects on health and cognitive performance. The desired circadian phase of a patient may take into account a desired sleep start time and a desired sleep end time. In some examples, the sleep start time and sleep end time may be related to a DLMO which can be input into the pacemaker model described herein (e.g., as a CBTmin value).

[0058] At block 1104, the method 1100 may include determining a light treatment to adjust (e.g., change) the circadian phase of the patient. Determining the light treatment may include inputting the desired sleep start time and desired sleep end time of the patient, as defined in terms of DLMO (or CBTmin using Equation 1), as well as the calculated / measured current CBTmin into a pacemaker model. Once the desired CBTminclock time is determined, CS and thereby CLA2.0 for a light treatment may be determined from the pacemaker model. Variations in CS determine the exact parameters of the light treatment. In some examples, the pacemaker model described herein determines the effect on circadian phase for any type of light exposure or dark Page 14 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center exposure. Therefore, the pacemaker model is operable to determine any number of different light and / or dark exposures necessary to adjust the circadian phase of the patient to a desired phase.

[0059] The CS needed to change the circadian phase of the patient may be used to determine a light treatment having various parameters. In some examples, these parameters may be the amount, duration, and clock time of a circadian effective light. In some examples, the light treatment may further include limiting exposures to circadian effective light at certain times. The light treatment may be tailored to the patient’s social schedule or other preferences. It will be appreciated that a variety of different light treatments may be used depending on the patient’s desired circadian phase. For example, in some patients full 24 hour control of CS may be obtainable, and therefore a 24 hour light treatment plan comprising various lighting characteristics may be administered. For other patients, a light treatment may comprise a singular light event (e.g., a light treatment having a set amount, duration, and clock time). In some examples, a light treatment may include one or more light treatments (e.g., light treatments having a set amount, duration, and clock time).

[0060] The amount, duration, and clock time of the circadian effective light may be related to one another. Therefore, many different light treatment options may be presented to a patient in order to allow the patient to fit the treatment into their daily schedule. For example, a greater amount of light may be administered for a shorter duration to effect a change in the circadian phase of the patient. In an example, the light treatment may comprise administering a plurality of circadian effective lighting exposures and a plurality of circadian dark exposures throughout a 24 hour period. For example, a light treatment may include light having a CS of 0.3 for 2 hours starting at 9 am followed by typical daily light exposures and then circadian dark exposures occurring before a desired sleep start time.

[0061] As readily understood, a patient will be exposed to a plurality of light sources throughout any given day. Therefore, the light treatment may include exposure to a light source having a specific CS (e.g., 0.01 to 0.7) for a specific duration and at a specific clock time to adjust the patient’s circadian phase in view of the patient’s initial phase. In some examples, the pacemaker model may indicate the certain parameters (e.g., CS value, duration, and clock time) to adjust the circadian phase of the patient Page 15 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center given the patient’s initial circadian phase. In some examples, the light treatment may comprise a plurality of CS light exposures throughout a day.

[0062] As illustrated in FIG.2B, CS may be directly related to melatonin suppression. Further, CLA relates directly to a CS value, therefore the pacemaker models’ outputted CS value at a necessary time may correlate to a CLA value which then may be transformed into the desired lighting treatment. For example, being outdoors at night may correspond to a CS of about 0, while being outdoors during the day may correspond to a CS of about 0.7. Being outdoors at night may have a melatonin suppression percentage of about 0%, whereas being outdoors during the day may have a melatonin suppression percentage of about 70%. These two light / dark exposures may comprise the minimum and maximum CS values. In between outdoor light during the day and outdoor light at night are a variety of different CS light values. These different CS light values may provide the basis for the light treatment necessary to adequately suppress melatonin for a duration at a clock time to adjust the circadian phase of the patient. The light treatment may provide the patient with a variety of options including different amounts, durations, and clock times.

[0063] In some examples, the light treatment may be provided by a lighting device, outdoor light, or by limiting light exposure. The lighting device may be any device that provides light. In some examples, the lighting device may be a light mask operable to deliver light directly to a patient’s eyes. The light mask may be operable to deliver light even when the patient’s eyes are closed. In some examples, the lighting device may be configured to provide pulses of light. For example, the lighting device may provide a 1 second pulse of 0.65 CS light every 30 seconds. The pulsing may limit heat buildup while producing similar effectiveness of continuous radiation.

[0064] In other examples, the lighting device may be electric room lighting, a self- luminous tablet, a light box, electrically powered ambient lighting devices, a linear source (e.g., LED strip) or other lighting devices known in the art. In an example, the light box may be a diffused light box such as a ganzfeld sphere. In some examples, the light treatment may be going outside for a duration at a given clock time depending on the patient’s desired circadian phase.

[0065] In some aspects, the necessary CS for the light treatment may be converted into photopic illuminance of “white” light delivered to the eyes of the patient with electric room lighting between about 0 lux to 1000 lux. In an aspect, the light treatment may Page 16 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center be a white light having an amount of about 0 lux to about 100 lux, about 100 lux to about 200 lux, about 200 lux to about 300 lux, about 300 lux to about 400 lux, about 400 lux to about 500 lux, about 500 lux to about 600 lux, about 600 lux to about 700 lux, about 700 lux to about 800 lux, about 800 lux to about 900 lux, or about 900 lux to about 1,000 lux all correlating to different CS values and therefore different effects on the patient’s circadian phase. In some examples, the light treatment may be administered via a white light source with correlated color temperatures (CCTs) ranging from about 2200 K to about 7500 K, where each value in the range provides a different effect on the patient’s circadian phase.

[0066] In an aspect, the light treatment may comprise pure blue light from a blue LED having a particular wavelength (e.g., peak emission of 470 nm), full-width-half- maximum bandwidth (e.g., FWHM of 20 nm), and irradiance (e.g., 0.5 W / m2). In other examples, other light treatments may be given in terms of CS and thereby CLA. In an example, the light treatment may be a polychromatic white light and / or narrowband light. A narrow-band light source may have a peak wavelength between 380 nm and 730 nm, corresponding to different CS values and therefore having differing effects on the patient’s circadian phase.

[0067] In an aspect, the duration of the light may be about 1 minute to about 30 minutes, about 30 minutes to about 1 hour, about 1 hour to about 1.5 hours, about 1.5 hours to about 2 hours, about 2 hours to about 2.5 hours, about 2.5 hours to about 3 hours, about 3 hours to about 3.5 hours, about 3.5 hours to about 4 hours, about 4 hours to about 4.5 hours, about 4.5 hours to about 5 hours, about 5 hours to about 5.5 hours, about 5.5 hours to about 6 hours, or more. The duration of the light treatment, in combination with the amount, as measured by CS, have differing effects on the adjustment of the patient’s circadian rhythm. For example, a higher CS for a short duration may have a similar effect to a lower CS for a longer duration. The model can predict change in circadian phase for each administered CS at each duration, thereby providing a variety of CS values and durations to adjust a patient’s circadian phase.

[0068] The clock time of the light treatment may be any time from 12:00 am to 11:59 pm (e.g., the morning, the afternoon, the evening, the night, or combinations thereof). The clock time may be important for the light treatment. For example, if a patient wants to advance their circadian phase, the patient may be exposed to a higher CS light or a CS light for a longer duration earlier in the day. Similarly, the model may provide Page 17 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center another option where an even higher CS light is necessary to advance the patient’s circadian phase at a later clock time.

[0069] The amount of light and the duration of light may be related. For example, a light treatment having 700 lux for 30 minutes may be roughly equivalent to a light treatment having 350 lux for 1 hour and walking outside will correspond to an even shorter duration than 30 minutes.

[0070] In an aspect, the light treatment may include limiting the patient’s exposure to circadian effective light. This may be accomplished by providing the patient with glasses that block circadian effective light such as narrowband blue light. In some examples, the gasses may be orange glasses. The blocking or limiting of a patient’s exposure to circadian light may be referred to as treating the patient to circadian dark. In some examples, limiting or protecting exposure to circadian effective light may occur in the evening or night. In another example, wearing an eye mask while sleeping may further promote adjustment to the patient’s desired circadian phase.

[0071] In some examples, the light treatment may be administered with the same parameters every day. In other examples, equivalent light treatments (e.g., one light treatment with a certain amount, duration, and clock time may be equivalent to a different amount, duration, and time) may be administered on different days due to a patient’s schedule or preference.

[0072] It will be appreciated that the pacemaker model may determine the effect of any type of light or dark exposure in terms of CS for a specific duration and clock time. The above examples for light and dark sources, durations, and clock times are examples only. The pacemaker model provides accurate predictions of light and dark exposure effects on the circadian phase of the patient and therefore is operable to determine numerous different combinations of light sources, durations, and clock times to adjust the patient’s circadian phase to the desired circadian phase. In this manner, the pacemaker model is operable to provide the patient with a plurality of light treatment options.

[0073] In some aspects, the method 1100 may further include monitoring the patient’s light / dark exposures throughout the day using the at least one photosensor. The photosensor may be in communication with a computing device. The computing device may be in communication with a lighting device or other wearable device. In some aspects, the computing device may be in communication with a display. The Page 18 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center display may provide haptic feedback to the user related to the light treatment. For example, the display may provide feedback that the light from the lighting device or outdoor lighting is an insufficient amount of light. The display may also provide guidance on the light treatment. For example, the display may indicate that it is the correct clock time to begin the light treatment. The display may indicate that it is time for circadian dark exposure (e.g., no light provided). The display may indicate the duration of the light treatment and may provide a timer to indicate when the light treatment is completed. In some examples, the display may be a mobile device. In a further example, an audible alert may be given to a patient related to duration, amount, and clock time of the light treatment. In some examples, the audible alert may be produced by a mobile device.

[0074] In an aspect, the computing device may be in communication with a lighting device. The computing device may control the amount, duration, and clock time of light to provide a light treatment. For example, in some instances, the computing device may be able to adjust ambient light to provide the light treatment. At certain clock times, the ambient light may be adjusted by the computing device to provide the light treatment to change the patient’s circadian phase. In another example, the computing device may be operable to turn the lighting device on and provide CS light at a desired clock time for a desired duration, thereby fully automating the light treatment.

[0075] In another aspect, the lighting device, the display, and the computing device may all be one component, such that the device is operable to determine the light treatment parameters, provide the light treatment, and provide feedback related to the light treatment.

[0076] In an aspect, the method 1100 may further include determining a patient’s circadian phase (e.g., new circadian phase) at least one day after the light treatment has started. In this manner, the patient’s progress towards their desired circadian phase may be determined. The light treatments may then be adjusted to enhance progress or maintain the current circadian phase of the patient. The method 1100 may be conducted on patients of any age. In an example, the age of the patient may be about 1 year old to about 95 years old.

[0077] In some aspects, determining the patient’s circadian phase may also optionally include monitoring a plurality of light exposures of the patient during at least one monitoring period of 24 hours. In some examples, more than one monitoring Page 19 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center period may be used. Monitoring the plurality of light exposures may be conducted using at least one calibrated photosensor. In an example, the photosensor may be a calibrated photometric device. In one example, the photosensor may be a Daysimeter. The Daysimeter may contain a red-green-blue (RGB) solid-state photosensor package with an infrared (IR) filter. The RGB reading may allow a computing system to compute a variety of spectrally weighted irradiance values such as photopic illuminance (lux), CLA, and CS. The Daysimeter may also contain a three-axis, solid-state accelerometer package to measure a behavior response (R) influenced by the circadian system, called Activity Index (AI), simultaneous with the light stimulus (S). Sampling rates of the light exposures may occur every second or less. Storage rates may be between every 30 seconds to every 180 seconds. At the end of the storage rate, the light exposure measurements may be sent to the computing system, such that the light exposure measurements are stored and / or analyzed by the computing system. In some examples, the light exposures may be measured as irradiance at a cornea of the patient weighted by circadian effective light (CLA). In other examples, the light exposures may be measured using any metric traceable to circadian effective light. The photosensor may be located on the patient’s body. In one example, the photosensor may be located on a wrist, torso, chest, or head of a patient.

[0078] In some aspects, monitoring the patient’s light exposure throughout a day may improve the efficacy of the light treatment. For example, by monitoring the patient’s light exposures, more effective CS light treatments may be determined. For example, if a patient is working outdoors for an entire morning, a higher CS for a light treatment may not be necessary around noon. Whereas if the patient is inside for the entire morning, a higher CS around noon may help adjust the patient’s circadian phase to the desired circadian phase. The information gathered from the patient’s light exposures may improve the treatment by more accurately determining the circadian phase and predicting necessary light exposures for circadian phase adjustment.

[0079] In another aspect, the light treatment may be configured to re-align the circadian phase of the patient to improve population specific health outcomes. For example, the light treatment may improve inflammation, neutropenic fever, and symptom burden of a multiple myeloma patient. In another example, the light treatment may improve sleep and mood of patients with Alzheimer’s disease. In another example, the light treatment may improve the sleep schedule for any human. In an Page 20 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center example, the light treatment may be used to change the circadian phase of a patient who has been traveling between time zones.

[0080] In other examples, the light treatment may be configured to help submariners adjust their circadian phase to a desired schedule depending on the demands of their job. Office workers may adjust their circadian phase by, for example, going on a walk every day at noon or being exposed to other circadian effective light for longer durations, such as a lighting device in their office. Similarly, school students may adjust their circadian phase by going on walk outdoors around noon or being exposed to other circadian effective light earlier in the day and then limiting light exposures later in the day. Furthermore, the method provided herein may be operable to predictably shorten the re-entrainment period for a regularly commuting daytime worker following daylight savings transition by providing a light treatment to adjust the worker’s circadian phase.

[0081] FIG. 12 is a diagram illustrating an example of a system for implementing certain aspects of the present technology. In particular, FIG.12 illustrates an example of computing system 1200, which can be for example any computing device making up an internal computing system, a remote computing system, a camera, or any component thereof in which the components of the system are in communication with each other using connection 1205. Connection 1205 can be a physical connection using a bus, or a direct connection into processor 1210, such as in a chipset architecture. Connection 1205 can also be a virtual connection, networked connection, or logical connection.

[0082] In some aspects, computing system 1200 is a distributed system in which the functions described in this disclosure can be distributed within a datacenter, multiple data centers, a peer network, etc. In some aspects, one or more of the described system components represents many such components each performing some or all of the function for which the component is described. In some aspects, the components can be physical or virtual devices.

[0083] Example computing system 1200 includes at least one processing unit (CPU or processor) 1210 and connection 1205 that couples various system components including system memory 1215, such as ROM 1220 and RAM 1225 to processor 2310. Computing system 1200 can include a cache 1212 of high-speed memory connected directly with, in close proximity to, or integrated as part of processor 1210. Page 21 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center

[0084] Processor 1210 can include any general purpose processor and a hardware service or software service, such as services 1232, 1234, and 1236 stored in storage device 1230, configured to control processor 1210 as well as a special-purpose processor where software instructions are incorporated into the actual processor design. Processor 1210 may essentially be a completely self-contained computing system, containing multiple cores or processors, a bus, memory controller, cache, etc. A multi-core processor may be symmetric or asymmetric.

[0085] To enable user interaction, computing system 1200 includes an input device 1245, which can represent any number of input mechanisms, such as a microphone for speech, a touch-sensitive screen for gesture or graphical input, keyboard, mouse, motion input, speech, etc. Computing system 1200 can also include output device 1235, which can be one or more of a number of output mechanisms. In some instances, multimodal systems can enable a user to provide multiple types of input / output to communicate with computing system 1200. Computing system 1200 can include communications interface 1240, which can generally govern and manage the user input and system output. The communication interface may perform or facilitate receipt and / or transmission wired or wireless communications using wired and / or wireless transceivers, including those making use of an audio jack / plug, a microphone jack / plug, a universal serial bus (USB) port / plug, an Apple® Lightning® port / plug, an Ethernet port / plug, a fiber optic port / plug, a proprietary wired port / plug, a Bluetooth® wireless signal transfer, a BLE wireless signal transfer, an IBEACON® wireless signal transfer, an RFID wireless signal transfer, near-field communications (NFC) wireless signal transfer, dedicated short range communication (DSRC) wireless signal transfer, 802.11 WiFi wireless signal transfer, WLAN signal transfer, Visible Light Communication (VLC), Worldwide Interoperability for Microwave Access (WiMAX), IR communication wireless signal transfer, Public Switched Telephone Network (PSTN) signal transfer, Integrated Services Digital Network (ISDN) signal transfer, 3G / 4G / 5G / LTE cellular data network wireless signal transfer, ad-hoc network signal transfer, radio wave signal transfer, microwave signal transfer, infrared signal transfer, visible light signal transfer, ultraviolet light signal transfer, wireless signal transfer along the electromagnetic spectrum, or some combination thereof. The communications interface 1240 may also include one or more Global Navigation Satellite System (GNSS) receivers or transceivers that are used to determine a location of the Page 22 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center computing system 1200 based on receipt of one or more signals from one or more satellites associated with one or more GNSS systems. GNSS systems include, but are not limited to, the US-based GPS, the Russia-based Global Navigation Satellite System (GLONASS), the China-based BeiDou Navigation Satellite System (BDS), and the Europe-based Galileo GNSS. There is no restriction on operating on any particular hardware arrangement, and therefore the basic features here may easily be substituted for improved hardware or firmware arrangements as they are developed.

[0086] Storage device 1230 can be a non-volatile and / or non-transitory and / or computer-readable memory device and can be a hard disk or other types of computer readable media which can store data that are accessible by a computer, such as magnetic cassettes, flash memory cards, solid state memory devices, digital versatile disks, cartridges, a floppy disk, a flexible disk, a hard disk, magnetic tape, a magnetic strip / stripe, any other magnetic storage medium, flash memory, memristor memory, any other solid-state memory, a compact disc read only memory (CD-ROM) optical disc, a rewritable compact disc (CD) optical disc, digital video disk (DVD) optical disc, a blu-ray disc (BDD) optical disc, a holographic optical disk, another optical medium, a secure digital (SD) card, a micro secure digital (microSD) card, a Memory Stick® card, a smartcard chip, a EMV chip, a subscriber identity module (SIM) card, a mini / micro / nano / pico SIM card, another integrated circuit (IC) chip / card, RAM, static RAM (SRAM), dynamic RAM (DRAM), ROM, programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash EPROM (FLASHEPROM), cache memory (L1 / L2 / L3 / L4 / L5 / L#), resistive random-access memory (RRAM / ReRAM), phase change memory (PCM), spin transfer torque RAM (STT-RAM), another memory chip or cartridge, and / or a combination thereof.

[0087] The storage device 1230 can include software services, servers, services, etc., that when the code that defines such software is executed by the processor 1210, it causes the system to perform a function. In some aspects, a hardware service that performs a particular function can include the software component stored in a computer-readable medium in connection with the necessary hardware components, such as processor 1210, connection 1205, output device 1235, etc., to carry out the function. The term “computer-readable medium” includes, but is not limited to, portable or non-portable storage devices, optical storage devices, and various other mediums Page 23 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center capable of storing, containing, or carrying instruction(s) and / or data. A computer- readable medium may include a non-transitory medium in which data can be stored and that does not include carrier waves and / or transitory electronic signals propagating wirelessly or over wired connections. Examples of a non-transitory medium may include, but are not limited to, a magnetic disk or tape, optical storage media such as CD or DVD, flash memory, memory or memory devices. A computer- readable medium may have stored thereon code and / or machine-executable instructions that may represent a procedure, a function, a subprogram, a program, a routine, a subroutine, a module, a software package, a class, or any combination of instructions, data structures, or program statements. A code segment may be coupled to another code segment or a hardware circuit by passing and / or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, etc. may be passed, forwarded, or transmitted via any suitable means including memory sharing, message passing, token passing, network transmission, or the like.

[0088] In some cases, the computing device or apparatus may include various components, such as one or more input devices, one or more output devices, one or more processors, one or more microprocessors, one or more microcomputers, one or more cameras, one or more sensors, and / or other component(s) that are configured to carry out the steps of processes described herein. In some examples, the computing device may include a display, one or more network interfaces configured to communicate and / or receive the data, any combination thereof, and / or other component(s). The one or more network interfaces can be configured to communicate and / or receive wired and / or wireless data, including data according to the 3G, 4G, 5G, and / or other cellular standard, data according to the Wi-Fi (802.11x) standards, data according to the BluetoothTMstandard, data according to the IP standard, and / or other types of data.

[0089] The components of the computing device can be implemented in circuitry. For example, the components can include and / or can be implemented using electronic circuits or other electronic hardware, which can include one or more programmable electronic circuits (e.g., microprocessors, GPUs, DSPs, CPUs, and / or other suitable electronic circuits), and / or can include and / or be implemented using computer Page 24 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center software, firmware, or any combination thereof, to perform the various operations described herein.

[0090] In some aspects the computer-readable storage devices, mediums, and memories can include a cable or wireless signal containing a bit stream and the like. However, when mentioned, non-transitory computer-readable storage media expressly exclude media such as energy, carrier signals, electromagnetic waves, and signals per se. Examples

[0091] A major goal of any model is to predict data that are not part of the model development. However, the accuracy of model predictions is not isolated to the master clock (O) alone. Since all the pacemaker models in the literature have used photopic illuminance as the photic stimulus (S), there is likely some inherent error in the prediction accuracy. Similarly, there are several phase markers to characterize the response (R) of the master clock. Some are more fraught with sources of error (e.g., minimum core body temperature (CBTmin)) than others (DLMO), but no single, downstream outcome measure is without uncertainty. Therefore, to compare model predictions, it is necessary to rely on accuracy metrics that reflect not just the error associated with the model (O), but with the stimulus (S) and the response (R) as well.

[0092] A variety of metrics can be used to assess the accuracy of S-O-R model predictions, but two of particular importance, and utilized here, when possible, are (1) mean absolute error (MAE), which characterizes the variance in the actual values with respect to the modeled values and (2) the amount of data within an accuracy criterion. Regarding the latter metric, an accuracy criterion of 1 h was chosen, reflecting the current state of model development; no model to date has been able to predict all data within an accuracy criterion of 30 min, and all models have shown to predict all data within an accuracy criterion of 3 h.

[0093] The data sets listed in Table 1 have some advantages for evaluating pacemaker (O) model predictions of circadian phase change (R) due to light stimulation (S). First, and foremost, a useful pacemaker model should be able to predict data that were not used in model development. All four studies introduced here measured phase changes resulting from photic stimulation and have not been used in any pacemaker model development. Second, there are four independent data sets, not just one. So, pacemaker model predictions can be independently tested and compared, thus avoiding the possibility of “getting lucky” in predicting just one data set. Third, all four data sets were obtained under Page 25 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center field conditions, not under controlled experiments. As such, these data should be inherently more variable than laboratory data because light exposures, as well as other potential influences on circadian phase, were not controlled. If pacemaker models can predict phase changes for ambulatory data, they should also be able to predict phase changes in controlled laboratory experiments. Therefore, these four data sets represent a “worst-case” test of pacemaker models. Fourth, the proper specification of S and R is critical in testing pacemaker models. Without confidence in S and R, model prediction will be compromised. These four data sets are unique in this regard because the personal light sensors have been calibrated in terms of CLA, not photopic illuminance, and because assessments of the phase maker, DLMO, were obtained by a known, carefully supervised bioassay laboratory.

[0094] All four ambulatory experiments utilized calibrated personal light sensors – Daysimeters, to quantify S and well-controlled bioassay assessments of light-induced DLMO changes to quantify R. There are different versions of the light sensor (Daysimeter). The Daysimeters used in the experiments have been used to study circadian phase disruption in several sample populations: (1) nurses, (2) school children, (3) school teachers, (4) young adults, and (5) older adults. Broadly, a Daysimeter contains a red- green-blue (RGB), solid-state photosensor package, with an infrared (IR) filter. The R, G, and B reading from a calibrated light source enable software to compute a variety of spectrally weighted irradiance values such as photopic illuminance (lux), CLA and CS. These sensors also contain a three-axis, solid-state accelerometer package to measure a behavioral response (R) influenced by the circadian system, called Activity Index (AI), simultaneous with the light stimulus (S). Sampling rates were once every second, while storage rates (average values) varied between once every 30 seconds to once every 180 seconds (depending upon the study). The lab maintains a calibration file for each of the units developed. Importantly, not all photosensors used in other experiments are known to have been calibrated, and those that have been calibrated do not necessarily provide circadian-relevant values of light, like CLA or CS. Again, this failure to calibrate light sensors for the purposes of assessing pacemaker models will reduce accuracy of estimates.

[0095] In terms of R, Δ DLMO is a considered to be the best measure of circadian phase change. A trained nurse collected and stored all samples for biomarker Page 26 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center assessments. Table 1 summarizes the four data sets used in assessments of model prediction accuracy.

[0096] Two points should be noted regarding the light measurements in these four studies. First, the Daysimeter devices used to record circadian light exposures (CLA / CS) across the four datasets from Table 1 were calibrated based upon the original Rea et al. model of human circadian phototransduction, and not based upon the most recent revision to the model characterizing circadian light exposure in units of CLA / CS. Second, for the Appleman et al. (2013) dataset, only circadian light exposures (CLA) were recorded, and hence, any prediction accuracies using photopic light exposures as light stimuli could not be reported. Data Set Sample Protocol Characteristics / Position of Light Sensor Appleman et al., 2013 N = 21 adults DLMO assessed on the last night of the 5-day Age = 22.5 + / - 3.9 years baseline period and on 11 females the last night of the intervention week. For the Device: Daysimeter-D intervention, subjects Position of Daysimeter: were either assigned to Wrist an advance group receiving 2 h of LED blue light (λ max ≈ 476 nm) exposure in the morning and 3 h of orange-filtered light (λ < 525 nm = 0) in the evening, or a delay group receiving the blue light for 3 h in the evening and 2 h of orange-filtered light in the morning. Subjects were required to Page 27 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center follow a 90-min advanced sleep schedule while wearing a calibrated wrist-worn Daysimeter. Sharkey et al., 2011 N = 25 adults with Examined the effects of deprived sleep an advanced sleep / wake schedule and morning Age = 21.8 + / - 3.0 years blue light on circadian 13 females phase in adults with late sleep schedules and Device: Daysimeter-S subclinical features of Position of Daysimeter: delayed sleep phase headset (at eye level) syndrome (DSPD). Subjects were required to follow a fixed, individualized, advanced (1–2.5 h) sleep / wake schedule that included 7.5 h of time in bed per night. DLMO assessed on the last night of the baseline week and on the last night of the intervention week. Following baseline, subjects were assigned to either receive LED blue light (2max ≈ 470, ∼225 lux, n = 12) or “dim” (<1 lux, n = 13) light for 1 h after waking each day. Light exposures were Page 28 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center tracked from wake to sleep using head-worn Daysimeters. Rea et al., 2016 N = 11 adults DLMO was assessed on the last night of the 2- Age = 25.4 + / - 6.9 years week baseline collection Device: Daysimeter-S period and again on the last night of the 2-week Position of Daysimeter: intervention collection attached to collar period. Active light intervention comprised of LED blue light goggles (CS = 0.5) worn every morning for a minimum of 2 h or a maximum of 4 h depending upon previous light exposure. Orange- filtered glasses (2 < 525 nm = 0) were worn during the evening hours from 5:00 pm to bedtime. Daysimeters as well as wrist-worn actigraphs were continuously worn all 4 weeks. Figueiro et al., 2014 N = 23 regular adults All the subjects experienced an advance Age = 31.1 + / - 11.1 years protocol (receiving 2 h of 17 females blue light exposure in the morning and 3 h of Device: Daysimeter-D orange-filtered light in the evening), as well as a Page 29 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center Position of Daysimeter: delay protocol (blue light Wrist for 3 h in the evening and 2 h of orange-filtered light in the morning), in a counter-balanced order. Subjects were required to follow a 90-min advanced sleep schedule (except for the baseline period) while wearing a calibrated wrist-worn Daysimeter. For both sessions, DLMO assessed on the last night of the 5-day baseline period and on the last night of the intervention week. Table 1: An overview of the studies that provided data sets for modeling

[0097] A six step, serial approach, was used to evaluate model prediction accuracy. Step 1 was to determine whether predictions are better with or without Process L for the original limit-cycle oscillator model. Step 2 was to determine whether CLA was better than photopic illuminance for prediction accuracy. Step 3 was to determine whether CS as photic input obviates Process L. Step 4 was to determine whether considering only the morning light exposure period can improve prediction accuracy. Step 5 was to determine the importance of the sensitivity modulator and the initial estimate of clock time for the CBTmin. Step 6 was to determine if the Kronauer99 model parameters still hold given the change in characterization of the light stimulus input. FIG.10 is a graphical illustration of the Kronauer99 framework.

[0098] The Kronauer99 model was numerically solved and propagated in time using the parameter values as displayed in Table 2. Since the outcome measure for the Kronauer99 model consists of CBTmin and not DLMO, prior biomarker data, as illustrated in FIG.1, were used to establish the relationship between CBTmin and DLMO (DLMO = CBTmin – 7 h). Constant routine (CR) estimates of initial circadian phase were Page 30 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center not available for any of the four field studies. Even though the model at baseline was initialized assuming a CBTmin of 0400 (4:00 AM) across the groups, a systematic analysis was later performed by varying and optimizing the initial CBTmin at baseline from 0300 (3:00 AM) to 0900 (9 AM) in increments of 1 h. Predicted CBTmin at the end of the baseline period was used as the initial CBTmin for analyzing phase changes following the intervention period for each participant. For the analyses reported below, calibrated and personalized light-exposure data recorded for each individual participant across four field studies, Table 1, were used as the photic input to predict changes in circadian phase and validated against the proxy for Δ CBTmin (Δ DLMO). Error in prediction accuracy, calculated at an individual level, was subsequently averaged across individuals within the group and these values are reported in Tables 3-7, for each of the four datasets. Parameters Values Range 0.05 0.01-0.19 αo (Process L) 0.0075 0.0025-0.0200 β (Process L) G (Process L) 33.75 NA p (Process L) 0.6 0.1-1.0 I0 (Process L) 9500 NA µ (Process L) 0.13 0.01-0.30 q (Process L) 0.33 0.15-1.00 k (Process L) 0.55 0.15-0.95 Table 2: Published parameter values for Kronauer99 model and the range of parameter values over which predication accuracy of the modified model with CLA and CS as inputs was re-evaluated

[0099] All analysis was undertaken using MATLAB software, wherein the MATLAB numerical solver, ode45, was primarily used to solve the mathematical differential equations.

[0100] Step 1: Determine whether predications are better with or without Process L for the original limit-cycle oscillator model. The impact of prior light exposures was investigated by including and excluding Process L in the working model framework for each of the data sets. For this analysis, Process L was simply bypassed, inputting the Page 31 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center light data into Process P directly. The light data from the Daysimeter has a relatively high temporal bandwidth being sampled at 3-min intervals or less. The importance of the high frequency content for accurate predictions helped us determine the importance of the temporal dynamics of Process L and values of the involved time constants in a subsequent analysis. For example, Process L does not treat each light stimulus to the pacemaker independently. Rather, the magnitude of the effect from a given light stimulus, depends upon the magnitude of the effect caused by previous light stimuli.

[0101] As is evident from Table 3, the exclusion of Process L from the original Kronauer99 model substantially increases the MAE from 1.07 to 1.41 h and the percentage of subjects with error < 1 h drops from 53 to 46%. Thus, Process L improves the circadian phase prediction accuracy. This means, in effect, that light exposures are not independent when driving the SCN and sampling intervals should be short (<180 s). Rather, one must know with relatively high precision the previous light exposure before the impact of the next light exposure can be predicted. Model Data Set R2Mean absolute Subjects with error (MAE) in error < 1.0 hours hours (%) Kronauer99 Rea et al., 0.07 1.48 45 without 2016 Process L Figueiro et al., 0.11 1.16 60 2014 Sharkey et al., 0.11 1.58 32 2011 Average 0.10 1.41 46 Kronauer99 Rea et al., 0.11 0.91 55 with Process 2016 L Figueiro et al., 0.42 0.86 67 2014 Page 32 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center Sharkey et al., 0.21 1.43 36 2011 Average 0.25 1.07 53 Table 3: Summary of model predictions with and without Process L for the Kronauer99 model Model Data Set R2Mean absolute Subjects with error (MAE) in error < 1.0 hours hours (%) CLA without Rea et al., 0.04 1.15 55 Process L 2016 I0 = 9500 Figueiro et al., 0.31 1.04 62 2014 Sharkey et al., 0.00 1.57 27 2011 Appleman et 0.35 1.2 48 al., 2013 Average 0.18 1.24 48 CLA with Rea et al., 0.18 0.57 91 Process L 2016 I0 = 9500 Figueiro et al., 0.69 0.76 71 2014 Sharkey et al., 0.01 1.54 27 2011 Appleman et 0.77 0.82 67 al., 2013 Average 0.41 0.92 64 Table 4: Summary of model predictions with and without Process L for the Kronauer99 model using CLA as the photic stimulus Page 33 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center Model Data Set R2Mean absolute Subjects with error (MAE) in error < 1.0 hours hours (%) CS without Rea et al., 0.34 0.92 64 Process L 2016 I0= 0.7 Figueiro et al., 0.73 1.20 49 2014 Sharkey et al., 0.16 0.94 59 2011 Appleman et 0.77 1.22 38 al., 2013 Average 0.50 1.07 52 CS with Rea et al., 0.49 0.66 91 Process L 2016 I0 = 0.7 Figueiro et al., 0.72 0.66 80 2014 Sharkey et al., 0.17 1.21 41 2011 Appleman et 0.80 0.63 86 al., 2013 Average 0.55 0.79 75 Table 5: Summary of model predictions for the Kronauer99 model using CS as photic input (CS-oscillator model) Model Data Set R2Mean absolute Subjects with error (MAE) in error < 1.0 hours hours (%) Morning CS Rea et al., 0.29 1.76 27 (0600-1000) 2016 Figueiro et al., 0.31 1.31 42 2014 Page 34 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center Sharkey et al., 0.01 1.93 18 2011 Appleman et 0.06 1.56 48 al., 2013 Average 0.17 1.64 34 All CS (24 Rea et al., 0.49 0.66 91 hours) 2016 Figueiro et al., 0.72 0.66 80 2014 Sharkey et al., 0.17 1.21 41 2011 Appleman et 0.80 0.63 86 al., 2013 Average 0.55 0.79 75 Table 6: Summary of model predictions for the CS-oscillator with light exposures from only 0600 to 1000 considered Data Set CBTmin (time) R2Mean absolute Subjects with error (MAE) in error < 1.0 hours hours (%) Rea et al., 0400 0.49 0.66 91 2016 Figueiro et al., 0400 0.72 0.66 80 2014 Sharkey et al., 0400 0.17 1.21 41 2011 Appleman et 0400 0.80 0.63 86 al., 2013 Average ------ 0.55 0.79 75 Rea et al., 0300 0.52 0.60 91 2016 Figueiro et al., 0500 0.73 0.60 82 2014 Page 35 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center Sharkey et al., 0900 0.27 0.59 91 2011 Appleman et 0400 0.80 0.63 86 al., 2013 Average -------- 0.58 0.61 88 Table 7: Summarizing the effect of changing CBTmin on prediction accuracy for the CS-oscillator model across the four data sets

[0102] Step 2: Determine whether CLA is better than photopic illuminance for prediction accuracy. For this step, CLA replaced photopic illuminance as the input light parameter “l’ as specified in the Kronauer99 framework in equation A2.6.

[0103] The rest ofthe results from Tables 3-4 using CLA as input to Process L improves the MAE from 1.07 h (original Kronauer99 model) to 0.92 h and the percentage of subjects with error < 1 h increases from 53 to 64%. Thus, prediction accuracy improves by adjusting the spectral sensitivity of the retinal mechanisms providing input to the Kronauer99 model (i.e., substituting CLA for photopic illuminance).

[0104] Step 3: Determine whether circadian stimulus as photic input obviates Process L. For this step, CS replaced photopic illuminance as the input light parameter “I” as specified in the Kronauer99 framework (Eq. A2.6). The value of I0 (Eq. A2.6) was set to 0.7, which is the mathematical asymptote for CS. CS is a sigmoid function, inherently rendering every weak light stimulus equal (below threshold) and every strong light stimulus equal (above saturation). If, for example, the light stimuli were always either above saturation or below threshold, characterizing light exposures in units of CS would reduce the significance of Process L for model predictions. Indeed, there is no difference between the original Kronauer99 model with photopic illuminance as the photic input to Process L (Table 3, MAE = 1.07 and a 1h accuracy criterion = 53%) and using CS without Process L (Table 5 MAE = 1.07 and a 1-h accuracy criterion = 52%).

[0105] However, there is significant improvement when CS is used as photic input to Process L (Table 5), MAE = 0.79 and a 1-h accuracy criterion = 75%). Thus, correctly characterizing the photic input, in terms of both spectral (CLA) and absolute (CS) Page 36 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center sensitivity over the full operating range of the retinal phototransduction mechanisms, to Process L improves model prediction accuracy.

[0106] Step 4: Determine whether considering only the morning light exposure period can improve prediction accuracy. Diurnal species, including humans, typically exhibit intrinsic periods slightly longer than 24 h. To entrain to local time, morning light exposure is particularly important because it will advance the clock phase and the majority of humans free run with a period slightly longer than 24 h. Whether measuring morning light exposure alone would accurately predict phase changes was examined. Several permutations of using only the selective portions of the daily light-dark patterns to the predictive models were performed. As compared to continuous measurements of light exposure throughout the wake period as the predictive input, selective light pulse input models fared poorly. MAE and percent subjects with error < 1 h values for one such scenario wherein only the light-dark patterns from 0600 (6:00 AM) to 1000 (10:00 AM) were considered as the predictive inputs, are shown in Table 6. Adjusting the start (0600 (6:00 AM)) and end times (1000 (10:00 AM)), or splitting the exposure window (for e.g., 0600 (6:00 AM) – 0800 (8:00 AM) and 1800 (6:00 PM) – 2000 (8:00 PM)), did not improve the prediction accuracy.

[0107] Step 5: Determine the importance of the sensitivity modulator and the initial estimate of the CBTmin. The Kronauer99 model included a sensitivity modulator between Process L and Process P which controls the relative effectiveness of photic exposures depending upon the circadian phase of the pacemaker at the time of exposure. For example, a light exposure in the early morning should be more effective for inducing a phase change than that very same light exposure mid-day. Values generated by the sensitivity modulator depend upon the value of the circadian phase marker, CBTmin. The circadian phase marker was initially estimated to occur at 0400 (4:00 AM) to depict a “typical” CBTmin for people entrained to the solar day; that is, 4 h after midnight. Importantly, this assumed value of 0400 (4:00 AM) also sets the values for the light drive terms, x and xc, quite apart from the sensitivity modulator, as illustrated in FIG.10, where x is a variable proportional to endogenous core body temperature and xcis a complementary variable.

[0108] The systematic review of Kronauer99 model components also included an examination of the role of the initial estimate of the CBTmin in prediction accuracy. Theoretically, a large enough baseline data, consisting of light exposure history and biomarker assessment, should obviate the initial CBTmin estimate, as subsequent Page 37 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center predictions of post-intervention phase will utilize the CBTmin at the end of the baseline period as the initial phase. FIG. 3A-B shows the results of including or excluding the sensitivity modulator with CBTmin = 0400 (4:00 AM) when using CS as the photic input (S) to Process L for the four data sets (see Table 5). Of note, it will be recalled that the four data sets employed DLMO as the phase marker, but the analysis is based upon light- induced changes in DLMO (i.e., Δ DLMO). Thus, the absolute values of DLMO are unimportant, and all phase changes are evaluated relative to the phase determined at the end of the baseline period. On average, MAE across the four data sets dropped from 0.79 to 0.75 h with exclusion of the sensitivity modulator. However, the percentage of subjects with error < 1 h decreased from 75 to 71%. A closer look at these two metrics for the individual data sets shows that including the sensitivity modulator improved both MAE and the percentage of subjects with error < 1 h for three of the four data sets. Indeed, the Sharkey data were significantly worse when the sensitivity modulator was included. These results suggested that the sensitivity modulator could not be examined alone, but rather that there was an interaction between the assumed CBTmin value and the sensitivity modulator in determining predictive accuracy of the model.

[0109] The Sharkey data set involved young adult subjects with delayed sleep. This would suggest a priori that the CBTmin would be much later than the 0400 (4:00 AM) value estimated originally by Kronauer99. Whereas no other set of subjects would have been as phase delayed, it was deemed necessary to determine how the assumed value of CBTmin affected prediction accuracy. Given the absence of CR protocol estimated initial circadian phase, FIG. 4 shows the prediction accuracy values where CBTmin was systematically varied between 0300 (3:00 AM) and 0900 (9:00 AM) for the four data sets. The checkered bars in FIG.4 depict the assumptions in the original Kronauer99 model with the sensitivity modulator and an initial CBTmin = 0400.

[0110] The prediction accuracy values in the upper half of Table 7 are the same as those in the lower half of Table 6 where the CBTmin = 0400 (4:00 AM) and the sensitivity modulator is included in the model. The lower half of Table 7 summarizes the findings from interaction plots in FIG.4. Specifically, inclusion of the sensitivity modulator with the optimum time of the initial circadian phase marker (i.e., the value of CBTmin) always led to the greatest prediction accuracy. For each of the four data sets, the prediction accuracy values, MAE and percent subjects with error < 1 h, are shown with the optimum CBTmin with the sensitivity modulator. Assuming baseline CBTmin = 0400 (4:00 AM) was only accurate for Page 38 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center one of the four data sets (Appleman et al., 2013) and as expected, the discrepancy between optimum CBTmin value and CBTmin = 0400 (4:00 AM) was greatest for the Sharkey data. Table 7 shows the importance of setting an optimum value for CBTmin; MAE decreased from 0.79 to 0.61 and the percent of subjects with error < 1 h increased from 75 to 88%.

[0111] These results demonstrate that chronotype is important for accurately predicting light-induced phase changes, particularly for more extreme chronotypes like those in the Sharkey study. It will be recalled that Figueiro et al. (2014) employed both phase-advanced and phase-delayed chronotypes in their study. As might be expected, the optimum CBTmin for the delayed group (owls) was later than that for the advanced group (larks). Consistent with an initial estimate, CBTmin = 0400 (4:00 AM) was optimum for the larks, with a MAE of 0.72 h and 83% subjects with error < 1 h. The optimum CBTmin for the owls was 0500 (5:00 AM), with a MAE of 0.75 h and 86% subjects with error < 1 h. Despite their designated chronotype, the difference in CBTmin for the two groups was quite small, likely because all the people in this study worked during the day.

[0112] Broadly speaking, this serial analysis demonstrates that prediction accuracy can vary quite considerably depending upon the explicit or implicit assumptions about the light stimulus (S) and the study cohort (O). Therefore, the CS-oscillator model developed here and derived from the original framework of the Kronauer99 model is an improvement in prediction accuracy.

[0113] Step 6: Validate the original Kronauer model parameters given the change in characterization of the light stimulus input. Since the light stimulus (S) to the model developed here is different than that used by Kronauer99, it was necessary to examine how well the original model parameters affected prediction accuracy. The published values of the model parameters are shown in Table 2.

[0114] All model parameter values were systematically varied over a range as shown in Table 2 to determine how they might affect prediction accuracy from the model developed here for the four data sets. G is inherently derived from α0 and β, and hence was excluded from the parameter-validation analysis. The originally published I0 value of 9500 was preserved when the light stimulus was changed from photopic illuminance to CLA. However, when the light stimulus input was changed from CLAto CS, the default value of I0had to be changed to 0.7, which is the mathematical asymptote for CS. Being an asymptote, I0 optimization was also excluded from the parameter-validation analysis. Page 39 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center

[0115] Following Kronauer99, the association between the light exposures recorded and the modeled time constants – α0 and, from Process L, is governed by the parameter “p,” or the light exponent. Contour plots, as illustrated in FIGS.5-6, demonstrate how the changes in values of α0 and affect the MAE and percent subjects with error < 1 h, respectively. The targets in the second column and the filled circles in the third column of FIGS.5-6 depict the prediction accuracy for Kronauer99 values. A change in prediction accuracy as a function of changing p, the light exponent, is also reported. This analysis revealed that, with a few exceptions in the Sharkey et al. (2011) data set, the prediction accuracy for base case scenario (α0 = 0.05; = 0.0075; p = 0.06) was always within ± 10% of the best achievable accuracy over the entire range of the parameters deployed across the data sets. In other words, there was no evidence that prediction accuracy could be substantially improved by changing the parameter values published in Kronauer99 and used in analyses. Therefore, the model developed here retained those originally published for Process L.

[0116] Similarly, FIGS. 7-8 examined the prediction accuracy for changes to the published Process P parameter values (µ = 0.13; k = 0.55; q = 0.33). Again, with a few exceptions in the Sharkey et al. (2011) data set, the original values were always within ± 10% of the best achievable accuracy over the entire range of the parameter values evaluated across the data sets. Since there was no evidence to support changing the original Process P parameter values, they were retained in the present model.

[0117] Earlier versions of the limit-cycle oscillator models also reported the human PRC characteristics and how well the respective models predicted PRC data. This analysis of the shift in the melatonin midpoint revealed a characteristic type 1 PRC with a significant peak-to-trough amplitude of 5.02 h.

[0118] In trying to achieve the highest accuracy for predicting phase change for the four data sets, there was no inadvertent compromise to the accuracy of predicting the PRC. Analysis revealed that a re-characterization of the light stimulus input from lux to CLA (and then CS), without changing other parameters of the Kronauer99 framework, had no bearing on the PRC characteristics (see identical plots in FIGS.9A-B). This was expected, as the PRC predictions use a constant spectrum, intensity, and duration pulse of light for which only the time-of-day of exposure changes.

[0119] A model for predicting light-induced circadian phase changes can aid in the adjustment of circadian phase to support re-entrainment for shift work, military operations, Page 40 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center and air travel. In this regard, a breakthrough was the van der Pol oscillator model. No other model has made substantive improvements to its prediction accuracy. The present systematic examination of the Kronauer99 model showed that it remains as good as any in terms of prediction uncertainty, which is limited to about 1 h.

[0120] The analysis of the Kronauer99 model was approached using a well-established framework from experimental psychology whereby the stimulus (S) acts on the organism (O) to produce a response (R). Within that framework, using four independent data sets, a serial analysis of the factors in the Kronauer99 model that could affect prediction accuracy was conducted. This analysis led to several conclusions.

[0121] It has already been established that light processed by the retina is the most important phase-shifting stimulus (S) to the master clock in the SCN. However, the definition of light for stimulating the master clock in the Kronauer99 model relies upon photopic illuminance where the spectral weighting function is the photopic luminous efficiency function [V(λ)]. From a wealth of research conducted over the last 20 years, V(λ) is incorrect for characterizing the spectral sensitivity of the circadian system. Recent modeling efforts of circadian phototransduction have quantified the non-linear spectral sensitivity of circadian-effective light (CLA). Replacing photopic illuminance with irradiance at the cornea weighted by CLA improved prediction accuracy.

[0122] Kronauer99 introduced a compressive function of the raw photopic illuminance via Process L. This function has no link to retinal neurophysiology but was simply a convenient and necessary transformation needed to increase prediction accuracy. In addition to defining the spectral sensitivity, the functional relationship between optical irradiance incident on the cornea and the response of these retinal mechanisms has been quantified in terms of circadian stimulus (CS) from threshold to saturation. CS represents an inherently compressive function of circadian-effective light based upon the neurophysiology of the retina. Therefore, the neural signal reaching the SCN defined in terms of CS is quantified in terms of both its spectral sensitivity and its operating characteristic. The CS transformation obviated arbitrary compression of the light input via I0 and improved the prediction accuracy. Derived from the Kronauer99 framework with revised characterization of the input photic stimulus in units of CS, the revised pacemaker model has been referred to as the CS-oscillator model.

[0123] Kronauer99 introduced Process L to account for hysteresis by the circadian- phototransduction mechanisms. In effect, this means that the effectiveness of a given Page 41 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center light pulse is not independent of the effectiveness of the previous light pulse. All neural systems, including those in the retina, adapt to repeated stimulation. Although the tie to retinal neurophysiology is weaker than that for spectral and absolute sensitivity to light (above), this non-linear response of the retina to light was shown to be critical for prediction accuracy.

[0124] Diurnal humans, on average, have an intrinsic period of slightly longer than 24 h. Thus, morning light will, in principle, advance the clock to keep entrainment. For the CS- oscillator model, whether measuring morning light exposure alone would accurately predict phase changes was examined. It was quite clear that it was necessary to collect all light data throughout the day to accurately predict phase changes.

[0125] The time of light exposure is important. Even though a typical CBTmin value of 0400 (4:00 AM) appears to be a good estimate of the circadian phase marker for most people, individual differences are important. Most notably, the cohort from Sharkey et al. (2011) was a group of phase-delayed adolescents and young adults and a sensitivity modulator term of 0800 (8:00 AM) for CBTmin produced the most accurate predictions for that cohort.

[0126] After integrating these five conclusions into the CS-oscillator model, the utility of the free-parameter coefficients in the original Kronauer99 formulation was examined. No compelling reason to adjust the original coefficients was found.

[0127] Table 8 shows how accurate the original Kronauer99 model was in predicting the four independent data sets used in the present analysis along with the improvements introduced here. In sum, the CS-oscillator model developed here provides improved prediction accuracy. Model Data Set R2Mean Subjects with Absolute Error error < 1.0 (MAE) in hours (%) hours Original Average (3 0.25 1.07 53 Kronauer99 studies) CS-Oscillator Average (4 0.58 0.61 88 studies) Table 8: Overall Improvement in the prediction accuracy

[0128] Specific details are provided in the description above to provide a thorough understanding of the aspects and examples provided herein. However, it will be understood by one of ordinary skill in the art that the aspects may be practiced without Page 42 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center these specific details. For clarity of explanation, in some instances the present technology may be presented as including individual functional blocks including functional blocks comprising devices, device components, steps or routines in a method embodied in software, or combinations of hardware and software. Additional components may be used other than those shown in the figures and / or described herein. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the aspects in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the aspects.

[0129] Individual aspects may be described above as a process or method which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but may have additional steps not included in a figure. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.

[0130] Processes and methods according to the above-described examples can be implemented using computer-executable instructions that are stored or otherwise available from computer-readable media. Such instructions can include, for example, instructions and data which cause or otherwise configure a general purpose computer, special purpose computer, or a processing device to perform a certain function or group of functions. Portions of computer resources used can be accessible over a network. The computer executable instructions may be, for example, binaries, intermediate format instructions such as assembly language, firmware, source code, etc. Examples of computer-readable media that may be used to store instructions, information used, and / or information created during methods according to described examples include magnetic or optical disks, flash memory, USB devices provided with non-volatile memory, networked storage devices, and so on.

[0131] Devices implementing processes and methods according to these disclosures can include hardware, software, firmware, middleware, microcode, hardware Page 43 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center description languages, or any combination thereof, and can take any of a variety of form factors. When implemented in software, firmware, middleware, or microcode, the program code or code segments to perform the necessary tasks (e.g., a computer- program product) may be stored in a computer-readable or machine-readable medium. A processor(s) may perform the necessary tasks. Typical examples of form factors include laptops, smart phones, mobile phones, tablet devices, or other small form factor personal computers, personal digital assistants, rackmount devices, standalone devices, and so on. The functionality described herein also can be embodied in peripherals or add-in cards. Such functionality can also be implemented on a circuit board among different chips or different processes executing in a single device, by way of further example.

[0132] The instructions, media for conveying such instructions, computing resources for executing them, and other structures for supporting such computing resources are example means for providing the functions described in the disclosure.

[0133] In the foregoing description, aspects of the application are described with reference to specific aspects thereof, but those skilled in the art will recognize that the application is not limited thereto. Thus, while illustrative aspects of the application have been described in detail herein, it is to be understood that the inventive concepts may be otherwise variously embodied and employed, and that the appended claims are intended to be construed to include such variations, except as limited by the prior art. Various features and aspects of the above-described application may be used individually or jointly. Further, aspects can be utilized in any number of environments and applications beyond those described herein without departing from the broader spirit and scope of the specification. The specification and drawings are, accordingly, to be regarded as illustrative rather than restrictive. For the purposes of illustration, methods were described in a particular order. It should be appreciated that in alternate aspects, the methods may be performed in a different order than that described.

[0134] One of ordinary skill will appreciate that the less than (“<”) and greater than (“>”) symbols or terminology used herein can be replaced with less than or equal to (“≤”) and greater than or equal to (“≥”) symbols, respectively, without departing from the scope of this description.

[0135] Where components are described as being “configured to” perform certain operations, such configuration can be accomplished, for example, by designing Page 44 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center electronic circuits or other hardware to perform the operation, by programming programmable electronic circuits (e.g., microprocessors, or other suitable electronic circuits) to perform the operation, or any combination thereof.

[0136] The phrase “coupled to” refers to any component that is physically connected to another component either directly or indirectly, and / or any component that is in communication with another component (e.g., connected to the other component over a wired or wireless connection, and / or other suitable communication interface) either directly or indirectly.

[0137] Claim language or other language reciting “at least one of” a set and / or “one or more” of a set indicates that one member of the set or multiple members of the set (in any combination) satisfy the claim. For example, claim language reciting “at least one of A and B” or “at least one of A or B” means A, B, or A and B. In another example, claim language reciting “at least one of A, B, and C” or “at least one of A, B, or C” means A, B, C, or A and B, or A and C, or B and C, or A and B and C. The language “at least one of” a set and / or “one or more” of a set does not limit the set to the items listed in the set. For example, claim language reciting “at least one of A and B” or “at least one of A or B” can mean A, B, or A and B, and can additionally include items not listed in the set of A and B.

[0138]

[0001] The various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the aspects disclosed herein may be implemented as electronic hardware, computer software, firmware, or combinations thereof. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

[0139] The techniques described herein may also be implemented in electronic hardware, computer software, firmware, or any combination thereof. Such techniques may be implemented in any of a variety of devices such as general purposes computers, wireless communication device handsets, or integrated circuit devices Page 45 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center having multiple uses including application in wireless communication device handsets and other devices. Any features described as modules or components may be implemented together in an integrated logic device or separately as discrete but interoperable logic devices. If implemented in software, the techniques may be realized at least in part by a computer-readable data storage medium comprising program code including instructions that, when executed, performs one or more of the methods described above. The computer-readable data storage medium may form part of a computer program product, which may include packaging materials. The computer-readable medium may comprise memory or data storage media, such as RAM such as synchronous dynamic random access memory (SDRAM), ROM, non- volatile random access memory (NVRAM), EEPROM, flash memory, magnetic or optical data storage media, and the like. The techniques additionally, or alternatively, may be realized at least in part by a computer-readable communication medium that carries or communicates program code in the form of instructions or data structures and that can be accessed, read, and / or executed by a computer, such as propagated signals or waves.

[0140] The program code may be executed by a processor, which may include one or more processors, such as one or more DSPs, general purpose microprocessors, an application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Such a processor may be configured to perform any of the techniques described in this disclosure. A general purpose processor may be a microprocessor; but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Accordingly, the term “processor,” as used herein may refer to any of the foregoing structure, any combination of the foregoing structure, or any other structure or apparatus suitable for implementation of the techniques described herein.

[0141] The disclosures shown and described above are only examples. Even though numerous characteristics and advantages of the present technology have been set forth in the foregoing description, together with details of the structure and function of Page 46 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center the present disclosure, the disclosure is illustrative only, and changes may be made in the detail, especially in matters of shape, size and arrangement of the parts within the principles of the present disclosure to the full extent indicated by the broad general meaning of the terms used in the attached claims. It will therefore be appreciated that the examples described above may be modified within the scope of the appended claims. Page 47 of 58 98666117.2

Claims

PATENT Atty Docket: 093698-822897 Via Patent Center CLAIMS What is claimed is:

1. A method of determining a light treatment for a patient in need thereof, the method comprising: determining a circadian phase of the patient; and determining the light treatment to adjust the determined circadian phase, wherein the light treatment comprises an amount, a duration, and a clock time relative to the determined circadian phase of light for the light treatment.

2. The method of claim 1, the method further comprising administering the light treatment.

3. The method of claim 1, wherein determining the circadian phase of the patient comprises: monitoring, using at least one calibrated photometric device, a plurality of light exposures of the patient during at least one monitoring period of 24 hours; and / or determining a biomarker relative to clock time of the patient; wherein the light exposures are measured as irradiance at a cornea of the patient using any metric traceable to circadian effective light based on CLA.

4. The method of claim 3, wherein the biomarker determines DLMO and / or CBTmin.

5. The method of claim 3, wherein the at least one calibrated photometric device is a Daysimeter.

6. The method of claim 5, wherein at least one photosensor is located on a wrist, a torso, a chest, or a head of the patient.

7. The method of claim 1, wherein the light treatment is exposure to or protection from circadian effective light. Page 48 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center 8. The method of claim 1, wherein the light treatment predictably changes the determined circadian phase of the patient to a desired circadian phase.

9. The method of claim 1, wherein the light treatment is outdoor light exposures.

10. The method of claim 1, wherein the light treatment comprises limiting exposure to light.

11. The method of claim 1, wherein a photopic illuminance traceable to CLA of “white” light delivered at eye level for the light treatment with electric room lighting is between 0 lux and 1,000 lux.

12. The method of claim 1, wherein the duration of the light delivered for the light treatment is about 1 hour, about 2 hours, about 3 hours, about 4 hours, about 5 hours, or about 6 hours.

13. The method of claim 1, wherein the amount of light determines the duration and clock time of the light for the light treatment, or the duration and clock time of the light determines the amount of light for the light treatment.

14. The method of claim 1, wherein the amount of light is 700 lux and the duration is 30 minutes.

15. The method of claim 1, wherein the amount of light is 350 lux and the duration is 1 hour.

16. The method of claim 1, wherein the light treatment is any light or dark exposure having a CS between 0.01 and 0.

7.

17. The method of claim 1, wherein the light treatment is pure blue light provided by a pure blue LED having a wavelength of peak emission of about 470 nm, a full- width-half-maximum bandwidth of 20 nm and an irradiance of 0.5 W / m2, or wherein the light treatment has a CLA of 0 to 1000. Page 49 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center 18. The method of claim 1, wherein the amount of the light is 0 to about 1000 as specified in terms of CLA.

19. The method of claim 1, the method further comprising determining an effect of an amount, duration, and clock time of a light or dark exposure on the patient’s determined circadian phase.

20. The method of claim 1, wherein the clock time, the duration, and the amount of the light delivered for the light treatment is based on the determined circadian phase of the patient and a desired circadian phase.

21. The method of claim 1, wherein the light treatment re-aligns circadian phase as per patient’s preset goal to potentially improve population specific health outcomes including inflammation, neutropenic fever, and symptom burden of a multiple myeloma patient.

22. The method of claim 1, wherein the light treatment comprises a 24 hour light / dark exposure plan.

23. The method of claim 22, wherein the 24 hour light / dark exposure plan comprises a plurality of circadian effective lighting exposures and a plurality of circadian dark exposures.

24. The method of claim 1, wherein the light treatment comprises light from naturally available daylight or an electrically powered ambient lighting device, as per patient’s preference.

25. The method of claim 1, wherein the light treatment is provided by a white light having a correlated color temperature of about 2200 K to about 7500 K. Page 50 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center 26. The method of claim 1, wherein the light treatment is provided by a narrowband light source having a peak wavelength of about 380 nm to about 730 nm.

27. The method of claim 1, wherein the light treatment is tailored and administered at a time of day preferred by the patient from 12 AM to 11:59 PM.

28. The method of claim 1, wherein the light treatment is administered to the patient at eye level.

29. The method of claim 1, wherein the light treatment comprises a circadian effective light period for 0 hours to 24 hours.

30. The method of claim 1, wherein the light treatment comprises a circadian dark period for 0 hours to 24 hours.

31. The method of claim 1, wherein the light treatment improves sleep and mood of patients with Alzheimer’s disease.

32. The method of claim 1, wherein the light treatment comprises polychromatic white light and / or narrowband light capable of stimulating a circadian system.

33. The method of claim 1, wherein the clock time is in the morning, the afternoon, the evening, the night, or a combination thereof.

34. The method of claim 1, the method further comprising determining a new circadian phase of the patient at least one day after the light treatment has been administered.

35. The method of claim 1, wherein the light treatment is administered every day beginning at the clock time. Page 51 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center 36. The method of claim 1, wherein the patient has an age of about 1 years old to about 95 years old.

37. The method of claim 1, wherein the light treatment is provided by a lighting device.

38. The method of claim 37, wherein the lighting device is a light box, a light mask, wearable light goggles, and LED strip, or a self-luminous tablet.

39. A non-transitory computer readable medium storing instructions thereon that when executed by at least one processor cause the at least one processor to perform operations to determine a light treatment for a patient in need thereof, the operations comprising: determining a circadian phase of the patient; and determining the light treatment to adjust the determined circadian phase, wherein the light treatment comprises an amount, duration, and clock time relative to the determined circadian phase of light for the light treatment.

40. The non-transitory computer readable medium of claim 39, the operations further comprising administering the light treatment.

41. The non-transitory computer readable medium of claim 39, wherein determining the circadian phase of the patient comprises: receiving, using at least one calibrated photometric device, a plurality of light exposures of the patient during at least one monitoring period of 24 hours; and / or receiving a biomarker relative to clock time of the patient; wherein the light exposures are measured as irradiance at a cornea of the patient using any metric traceable to circadian effective light based on CLA.

42. The non-transitory computer readable medium of claim 41, wherein the biomarker relative to the clock time determines DLMO and / or CBTmin. Page 52 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center 43. The non-transitory computer readable medium of claim 41, wherein the at least one calibrated photometric device is a Daysimeter.

44. The non-transitory computer readable medium of claim 41, wherein the at least one calibrated photometric device is located on a wrist, a torso, a chest, or a head of the patient.

45. The non-transitory computer readable medium of claim 39, wherein the light treatment is exposure to or protection from circadian effective light.

46. The non-transitory computer readable medium of claim 39, wherein the light treatment predictably changes the determined circadian phase of the patient to a desired circadian phase.

47. The non-transitory computer readable medium of claim 39, wherein the light treatment is outdoor light exposures.

48. The non-transitory computer readable medium of claim 39, wherein the light treatment comprises limiting exposure to light.

49. The non-transitory computer readable medium of claim 39, wherein a photopic illuminance traceable to CLA of “white” light delivered at eye level for the light treatment with electric room lighting is between 0 lux and 1,000 lux.

50. The non-transitory computer readable medium of claim 39, wherein the duration of the light delivered for the light treatment is about 1 hour, about 2 hours, about 3 hours, about 4 hours, about 5 hours, or about 6 hours.

51. The non-transitory computer readable medium of claim 39, wherein the amount of light determines the duration and clock time of the light for the light treatment, or the duration and clock time of the light determines the amount of light for the light treatment. Page 53 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center 52. The non-transitory computer readable medium of claim 39, wherein the amount of light is 700 lux and the duration is 30 minutes.

53. The non-transitory computer readable medium of claim 39, wherein the amount of light is 350 lux and the duration is 1 hour.

54. The non-transitory computer readable medium of claim 39, wherein the light treatment is any light or dark exposure having a CS between 0.01 and 0.

7.

55. The non-transitory computer readable medium of claim 39, wherein the light treatment is pure blue light provided by a pure blue LED having a wavelength of peak emission of about 470 nm, a full-width-half-maximum bandwidth of 20 nm and an irradiance of 0.5 W / m2.

56. The non-transitory computer readable medium of claim 39, wherein the amount of the light is 0 to about 1000 as specified in terms of CLA.

57. The non-transitory computer readable medium of claim 39, the operations further comprising determining an effect of an amount, duration, and clock time of a light or dark exposure on the patient’s determined circadian phase.

58. The non-transitory computer readable medium of claim 39, wherein the clock time, the duration, and the amount of the light delivered for the light treatment is based on the determined circadian phase of the patient and a desired circadian phase.

59. The non-transitory computer readable medium of claim 39, wherein the light treatment re-aligns circadian phase as per patient’s preset goal to potentially improve population specific health outcomes including inflammation, neutropenic fever, and symptom burden of a multiple myeloma patient.

60. The non-transitory computer readable medium of claim 39, wherein the light treatment comprises a 24 hour light / dark exposure plan. Page 54 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center 61. The non-transitory computer readable medium of claim 60, wherein the 24 hour light / dark exposure plan comprises a plurality of circadian effective lighting exposures and a plurality of circadian dark exposures.

62. The non-transitory computer readable medium of claim 39, wherein the light treatment comprises light from naturally available daylight or an electrically powered ambient lighting device, as per patient’s preference.

63. The non-transitory computer readable medium of claim 39, wherein the light treatment is provided by a white light having a correlated color temperature of about 2200 K to about 7500 K.

64. The non-transitory computer readable medium of claim 39, wherein the light treatment is provided by a narrowband light source having a peak wavelength of about 380 nm to about 730 nm.

65. The non-transitory computer readable medium of claim 39, wherein the light treatment is tailored and administered at a time of day preferred by the patient from 12 AM to 11:59 PM.

66. The non-transitory computer readable medium of claim 39, wherein the light treatment is administered to the patient at eye level.

67. The non-transitory computer readable medium of claim 39, wherein the light treatment comprises a circadian effective light period for 0 hours to 24 hours.

68. The non-transitory computer readable medium of claim 39, wherein the light treatment comprises a circadian dark period for 0 hours to 24 hours.

69. The non-transitory computer readable medium of claim 39, wherein the light treatment improves sleep and mood of patients with Alzheimer’s disease. Page 55 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center 70. The non-transitory computer readable medium of claim 39, wherein the light treatment comprises polychromatic white light and / or narrowband light capable of stimulating a circadian system.

71. The non-transitory computer readable medium of claim 39, wherein the clock time is in the morning, the afternoon, the evening, the night, or a combination thereof.

72. The non-transitory computer readable medium of claim 39, the operations further comprising determining a new circadian phase of the patient at least one day after the light treatment has been administered.

73. The non-transitory computer readable medium of claim 39, wherein the light treatment is administered every day beginning at the clock time.

74. The non-transitory computer readable medium of claim 39, wherein the patient has an age of about 1 years old to about 95 years old.

75. The non-transitory computer readable medium of claim 39, wherein the light treatment is provided by a lighting device.

76. The non-transitory computer readable medium of claim 75, wherein the lighting device is a light box, a light mask, wearable light goggles, and LED strip, or a self-luminous tablet.

77. The non-transitory computer readable medium of claim 39, the operations further comprising turning on a lighting device to administer the light treatment.

78. The non-transitory computer readable medium of claim 77, the operations further comprising turning the lighting device off when the duration of the light treatment is completed. Page 56 of 58 98666117.2PATENT Atty Docket: 093698-822897 Via Patent Center 79. The non-transitory computer readable medium of claim 39, the operations further comprising providing an alert to the patient indicating it is time for the light treatment.

80. The non-transitory computer readable medium of claim 39, the operations further comprising providing an audible alert to the patient that it is time for the light treatment.

81. The non-transitory computer readable medium of claim 39, the operations further comprising providing feedback to the patient of the amount of light, duration of light, and clock time of light via a display. Page 57 of 58 98666117.2

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