Patent Publication Number: US-2020294652-A1

Title: Medication Enhancement Systems and Methods for Cognitive Benefit

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims priority to U.S. Provisional Patent Application No. 62/817,962, filed on Mar. 13, 2019, the entire disclosure of which is hereby expressly incorporated by reference. 
    
    
     GOVERNMENT RIGHTS 
     This invention was made with government support under Small Business Innovation Research Grant No. 1R43AG065035-01 awarded by the National Institutes of Health. The Government has certain rights in the invention. 
    
    
     BACKGROUND 
     Field of the Disclosure 
     The present disclosure relates to systems and methods for medication enhancement and cognitive benefit, and in particular, to systems and methods for providing computer generated cognitive therapy games and enhancements to cognitive medication. 
     Related Art 
     A 2013 report by the Alzheimer&#39;s Association showed that over 5 Million Americans suffer from dementia and its more severe variant called Alzheimer&#39;s disease (“AD”). According to the Alzheimer&#39;s Association, by 2019 the number of afflicted Americans had grown by about 40%, to 7.1 Million. AD is considered an irreversible neurodegenerative disorder. 
     Pharmacological approaches are frequently prescribed to treat AD, however, they are not always effective in treating cognitive impairments. Studies have shown that AD related cognitive impairments can affect decision making and problem solving (collectively called executive functions), memory, ability to focus, and quality of life. One study, which involved a review of 18 clinical studies on 802 patients, found that non-pharmacological approaches (physical exercise) to treating AD demonstrated benefits in the cognitive domains of memory, language, and attention in patients with AD. Studies have also found that physical activity interventions alone, or combined with other therapies, were effective in improving executive functions and self-reported concentration, while other studies have shown only a 0.4% success rate with pharmacological approaches, referred to herein generally as cognitive medication. 
     Web-based game treatment involving intellectual activities in the home is a newer form of non-pharmacological intervention which has been shown to delay the onset of dementia in elderly individuals. Integrative virtual rehabilitation is a rehabilitation method that uses virtual reality to simultaneously target the body, mind, and patient well-being. In some instances, integrative virtual rehabilitation can combine two non-pharmacological approaches that were found to benefit cognition for the elderly, e.g., physical activity and cognitive training. Furthermore, virtual rehabilitation game therapy has been found to be adaptable, highly motivating, and facilitate more intensive and integrative cognitive training than conventional approaches. 
     The BrightBrainer Rehabilitation System is a commercially available system and Class I medical device developed by Bright Cloud International Corp., which treats patients with deficits in attention, memory, executive functions, and other cognitive and neuromuscular conditions. It does so through custom therapeutic games that adapt to the patient&#39;s needs and ability on a day-to-day basis. Embodiments of the BrightBrainer Rehabilitation System are shown and described, for example, in U.S. Pat. No. 9,724,598, issued Aug. 8, 2017, entitled “Bimanual Integrative Remote Therapy System and Method” to Burdea, the entire disclosure of which is hereby incorporated by reference. Therapeutic games, such as those implemented by the BrightBrainer Rehabilitation System and described in U.S. Pat. No. 9,724,598, were shown to improve the focus and independence of severely impaired patients, e.g., patients with no working memory, no independence, flat emotional affect, within six (6) weeks (e.g., 18 sessions). U.S. Pat. No. 9,724,598 also discloses the use of certain food supplements for improved cognitive outcomes for patients playing cognitive bimanual games and the use of extra oxygen during therapeutic game play. 
     Studies have also found that such therapeutic games can improve executive function and reduce depression in impaired patients. Therapeutic games have also been found to benefit patients with cognitive impairments in eight (8) weeks (e.g., 16 sessions). Some benefits include improvement in language and reduction in mild cognitive impairments (“MCI”). For example, at least one patient, who initially presented with MCI, tested normal after eight (8) weeks of treatment using therapeutic games and maintained normal cognition after eight (8) weeks without therapeutic games. Additionally, in at least one instance an impaired male with Primary Progressive Aphasia started reading again and had improved behavior after BrightBrainer Rehabilitation System sessions. 
     Moreover, participants and therapists of a feasibility trial that targeted  21  individuals suffering with chronic post traumatic brain injury and/or stroke who underwent 18 BrightBrainer Rehabilitation System sessions have reported moderate to high levels of satisfaction with the system, and therapy was found to trend towards clinical effectiveness in Automated Neuropsychological Assessment Metrics. 
     Bright Cloud International Corp. also showed the feasibility of integrative VR-based rehabilitation for individuals chronic post-stroke living at home, e.g., through the use of a BrightBrainer Rehabilitation System.  FIG. 1A  is a diagram showing hardware components of the BrightBrainer Rehabilitation System, indicated at  10 . As shown, the system  10  includes a movable platform  11 , a medical grade computer  12 , an enclosure  13 , a large display  14 , a tracking means  15 , a multitude of game controllers  16 , held by the patient  17  and a power supply  18 . The BrightBrainer Rehabilitation System  10  also incorporates a Head Mounted Display (“HMD”)  19  placed in the enclosure  13  and wired to the computer  12 . 
     The system  10  can also include one or more game controllers  16 , such as the commercially available HTC VIVE controllers.  FIG. 1B  is a diagram showing a BrightBrainer Grasp therapeutic game controller  20 , which can also be used in connection with the system  10 . Therapeutic game controller  20  is described in detail in U.S. Patent Application Pub. No. 2017/0361217, published Dec. 21, 2017, entitled “Bimanual Integrative Virtual Rehabilitation System and Methods,” to Burdea et al., the entire disclosure of which is hereby expressly incorporated by reference. Therapeutic game controller  20  is also described in Burdea et al., “Novel Therapeutic Game Controller for Telerehabilitation of Spastic Hands: Two Case Studies,”  Proc.  13 th    Int. Conf. Virtual Rehabilitation , Tel Aviv Israel, July 2019, pp. 8, the entire disclosure of which is hereby expressly incorporated herein by reference. 
     Telerehabilitation intervention has been found to improve motor function, improve cognition, improve language, improve cognitive metrics, and decrease depression in patients suffering chronic impairments after stroke. 
     Computer games have also been used to diagnose dementia, as described in U.S. Patent Application Pub. No. 2016/0038075, published Feb. 11, 2016, entitled “Bimanual Computer Games System for Dementia Screening,” to Burdea et al., the entire disclosure of which is hereby expressly incorporated by reference. The use of computer games to diagnose dementia is also detailed in House et al., “A serious-gaming alternative to pen-and-paper cognitive scoring—a pilot study,” Int. Conference on Disability and Virtual Reality Technology, Sweden, 2014, the entire disclosure of which is hereby expressly incorporated herein by reference. The BrightScreener Rehabilitation System was tested as a screening system for individuals with dementia, including Alzheimer&#39;s disease. In this regard, a feasibility study was undertaken to determine if the BrightScreener Rehabilitation System was able to differentiate levels of cognitive impairment based on game performance alone, as well as to evaluate technology acceptance by a target population with dementia. It was found that BrightScreener Rehabilitation System implementing therapeutic games can be used as a digital technique to stratify levels of cognitive impairment. These results demonstrate that computerized systems using bimanual game interfaces are one alternative to conventional standardized scoring for Mild Cognitive Impairment and Dementia. 
     Web-based software applications like Elevate or Lumosity train cognition, but limit motor training to 2D uni-manual interactions. As such, they are unable to provide the needed physical exercise component shown to benefit early AD. Other integrative products such as Intendu or Jintronix utilize vision to track arm movements, but are unsuitable to track fingers. This limits the complexity of the training tasks. Furthermore, they rely on the Kinect system, a tracking device by Microsoft that is no longer made. Further still, none of these products incorporate a biosensor system to measure cognitive engagement, or use cognitive load and/or cognitive engagement as inputs in therapy shaping. None of these systems teach using, dosing, or monitoring cognitive medication use in conjunction with therapeutic games. 
     Additionally, combined (or integrative) remote rehabilitation systems are known in the art, such as the system described in U.S. Pat. No. 9,028,258, entitled “Combined Cognitive and Physical Therapy” to Burdea, the entire disclosure of which is hereby incorporated by reference. 
     Systems that use integrative virtual rehabilitation for individuals with dementia, Alzheimer&#39;s Disease, or other cognitive diseases, and are provided in the home for the benefit of patients and caregivers are needed. Additionally, systems and methods that leverage both cognitive training games and traditional medications for treating cognitive impairment, in order to combat Alzheimer&#39;s disease and other cognitive diseases are needed and have not yet been developed. 
     SUMMARY 
     In accordance with some aspects of the present disclosure, a system for measuring cognitive engagement using a combination of cognitive therapy game performance and physiological measurement data from a biosensor-integrated all-in-one head mounted display worn by a patient is provided. The biosensors can be cognitive engagement detection devices, such as, for example, skin temperature sensors, skin conductance measurement sensors, a blood oxygenation measurement system, an eye blinking detection system, an eye gaze detection system, and a head movement detection system. This data can be used by the system of the present disclosure to adapt one or more game parameters to the patient&#39;s momentary cognitive engagement response or degree of cognitive fatigue. For example, the type, intensity and challenge of the games can be modulated based on this information. The average difficulty of one or more games during a therapy session can also be monitored by the system of the present disclosure. As such, the system can adjust game session difficulty level based on a combination of the patient&#39;s performance and an index of cognitive load and cognitive engagement. 
     In some aspects, the system can determine a level of cognitive engagement of the patient based on the data generated by the cognitive engagement detection device, determine performance of the patient interacting with the therapeutic games based on information received from the game controllers, and determine cognitive improvement of the patient based on the cognitive engagement and the performance of the patient. 
     The system of the present disclosure can also be used over long durations of time in the home, as cognitive maintenance, which has been shown to reduce the incidence of dementia in aging populations, or reduce dementia severity after diagnosis. Thus, according to some aspects of the present disclosure, an in-home cognitive maintenance system is provided, which can be supplemented by other techniques used in brain wellness. For example, cognitive maintenance games generated by the system of the present disclosure can be used in isolation, or in combination with such techniques as outdoors physical exercising, reading books, learning a foreign language, socializing, yoga, or eating brain-stimulating foods. 
     According to some aspects of the present disclosure, the system can determine a galvanic response trend from a previous game played by a patient and an artificial intelligence (AI) algorithm can analyze the galvanic response trend to adjust one or more environmental game parameters of the next game. Thus, in a game-based rehabilitation session, when multiple games are played, the system can offer an optimized and winnable game setting for everyone, regardless of individual performance level. 
     According to some aspects of the present disclosure, the system can combine intense, remotely monitored cognitive training games and medication for cognitive diseases, to increase effectiveness of the cognitive medication. According to aspects of the present disclosure, the system can combine cognitive medication with therapeutic game scenes played by the patient to reduce rate of cognitive degradation and the cost of healthcare. According to aspects of the present disclosure, the type and dosage of the cognitive medication can be modified based on a cognitive state that is reported by a home-based system utilizing artificial intelligence software. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The foregoing features of the disclosure will be apparent from the following Detailed Description, taken in connection with the accompanying drawings, in which: 
         FIG. 1A  is a diagram showing hardware components of a prior art virtual reality cognitive game rehabilitation system; 
         FIG. 1B  is a diagram showing a game controller for a prior art cognitive game rehabilitation system; 
         FIG. 2  is a diagram illustrating hardware and software components of a cognitive game therapy system according to the present disclosure; 
         FIG. 3  is a diagram illustrating means for detecting cognitive engagement of the cognitive game therapy system of the present disclosure; 
         FIG. 4  is a front view of a head mounted display device according to the present disclosure; 
         FIG. 5  is a perspective view of the head mounted display device of  FIG. 4  according to the present disclosure; 
         FIG. 6  is a diagram illustrating hardware and software components of another cognitive engagement detection system according to the present disclosure; 
         FIG. 7A  is a diagram illustrating a game scene customization system according to the present disclosure; 
         FIG. 7B  is a diagram illustrating aspects of establishing a bio sensor baseline according to the present disclosure; 
         FIG. 7C  is a diagram illustrating a game scene selection system according to the present disclosure; 
         FIG. 8  is a graphical user interface generated by the system of the present disclosure, displaying a therapeutic game scene; 
         FIG. 9  is a graphical user interface generated by the system of the present disclosure, displaying another therapeutic game scene; 
         FIG. 10  is a diagram illustrating annual individual healthcare costs for patients with cognitive diseases; 
         FIG. 11  is a diagram illustrating exemplary treatment cost savings produced by the system of the present disclosure; 
         FIG. 12  is a diagram illustrating efficacy of the system of the present disclosure on the progression of Alzheimer&#39;s Disease; 
         FIG. 13  is a diagram illustrating a method for treating a cognitive disease according to the present disclosure; and 
         FIG. 14  is a diagram illustrating a method for treating a cognitive disease according to the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     The present disclosure relates to systems and methods of combining intense, remotely monitored cognitive training games and customary medication for cognitive diseases, such as early Alzheimer&#39;s disease (“AD”). The integration of computerized cognitive training games with the customary medication is done to increase the response and effectiveness of the cognitive medication. While the description below is directed towards one or more patients  17  (see  FIG. 2 ) with AD, some systems and methods of the present disclosure can be used by patients  17  with other medical conditions. For example, other patients that can benefit from such a combined therapy and therapeutic gaming in telerehabilitation include, but are not limited to, those who have survived a stroke, those who have sustained a Traumatic Brain Injury, or those who underwent chemotherapy and suffer from lasting cognitive impairments. Some, or all, of these patient groups can also take cognitive medications. 
       FIG. 2  is a diagram illustrating hardware and software components of a system  100  of the present disclosure for combined cognitive medication  144  and therapeutic games  145  training for patients  17 , patient  17  having cognitive impairments (such as Alzheimer&#39;s disease). A method of cognitive intervention is coupled with a measurement of associated cognitive engagement  210 . The system  100  and method can be used at home  102  by the patient  17 , or can be utilized in other settings, such as hospitals, assistive care facilities, or the like. Data  103  associated with the patient  17  can be stored on a remote database  105 . A remote clinician  106  can access the database  105  to determine the patient&#39;s  17  cognitive engagement  210 , cognitive fatigue  220 , cognitive improvement  222 , or a combination thereof. The remote database  105  can receive other the patient  17  data, and the remote clinician  106  can access such other data. The remote clinician  106  can access data from a plurality of patients  17 , and a plurality of clinicians  106  may access data from a plurality of patients  17 . 
     As shown in  FIG. 2 , the system  100  can include a biosensor module  110 , an all-in-one Head Mounted Display (HMD)  120 , game controllers  140 , and cognitive medication  144 . The cognitive medication  144  can be prescribed by remote clinician  106 , and taken by the patient  17  as customary treatment for cognitive diseases  223 . It is understood by those skilled in the art that the game controllers  140  can measure arm  150  movements during game play in response to cognitive training scenes  400 , which can be, for example, cognitive games or game scenes  400 . According to some aspects of the present disclosure, the game scenes  400  can be presented on the HMD  120  and replicated on a tablet  170 . Replicating the cognitive training scenes  400  on the tablet  170  allows a caregiver  18  of the patient  17  to monitor the patient&#39;s  17  actions. The tablet  170  can also transmit the cognitive training scenes  400  to the remote clinician  106 . Alternatively, or additionally, the HMD  120  can transmit the game scenes  400  to the remote clinician  106 . According to some aspects of the present disclosure, the patient  17  can take off the HMD  120  and play while looking at the cognitive training scenes  400  as they are displayed on the tablet  170 . The HMD  120  can also be linked to a television, computer monitor, or display via wired or wireless connection, such that the patient  17  can take off the HMD  120  and play while looking at the television, computer monitor, or display. 
     The all-in-one HMD  120  can be a commercially available HMD, for example, but not limited to, an all-in-one HMD sold under the brand name Oculus Quest. Computing hardware of the all-in-one HMD  120  can include a multi-core processor  130  having cores allocated to computing graphics cognitive training scenes  400 , tracking game controllers  140 , or the like. The all-in-one HMD  120  can be powered by a battery  181 , but the life of the battery  181  (e.g., runtime) can be a limiting factor for how long the patient  17  may be immersed in cognitive training scenes  400 . As such, the all-in-one HMD  120  can be plugged into, and rely on, a separate power supply  180 . 
     It is understood by those skilled in the art that two game controllers  140  can be held, one in each hand  160 , and the patient  17  can use the game controllers  140  to control avatars  2000  in the game cognitive training scenes  400 . It is further understood, that this is only one of a multitude of possible configurations, for example, a wireless or wired HMD  120  without its own computing hardware  130  can also be used by the patient  17 . In such a configuration, game cognitive training scenes  400  can be computed by a separate computer  190 . The separate computer  190  can be a Personal Computer, a tablet computer, a laptop, a game console, a smart phone, or other computation elements as those known in the art. 
     Where the system  100  utilizes a separate computer  190 , a cable can transmit game cognitive training scenes  400  to the HMD  120  for presentation to the patient  17 . It is understood by those skilled in the art that a cable can be eliminated via the use of wireless transmissions between the separate computer  190  and the HMD  120 . According to some aspects of the present disclosure, the separate computer  190  provides data to the HMD  120 , however game cognitive training scenes  400  are created within the HMD  120 . According to other aspects of the present disclosure, the separate computer  190  can utilize a large display  14 , such as illustrated in  FIG. 1A . 
     One component of the system  100  is a cognitive engagement detection device  200  for detecting cognitive engagement  210 , which can include one or more individual devices. Cognitive engagement  210  has been previously understood as investment of mental effort in order to complete an independent learning task online. However, cognitive engagement  210  is understood herein as mental effort of the patient  17  who is learning to interact with game cognitive training scenes  400  and succeeds in performing related gaming tasks  146 . The cognitive engagement detection device  200  for detecting cognitive engagement  210  may include one or a plurality of skin temperature sensors  230 , skin conductance measurement sensors  240 , blood oxygenation measurement system  250 , blinking detection system  260 , head movement detection system  270 , or a combination thereof (see  FIG. 3 ). 
       FIG. 3  is a diagram illustrating the cognitive engagement detection device  200  for detecting cognitive engagement  210  of the system  100  of the present disclosure. Artificial Intelligence software  135  can run on the all-in-one HMD  120  processor  130  or on the separate computer  190 . Artificial Intelligence software  135  can receive input from one or a plurality of the sensors and systems  230 ,  240 ,  250 ,  260  and  270 , and cam receive input from the game controllers  140 . The systems  230 ,  240 ,  250 ,  260 ,  270  and game controllers  140  can be in contact with, or actuated by, the patient  17 . The artificial intelligence software  135  can accordingly adjust game difficulty  401 , game duration  402 , game interaction modality  403 , game cognitive cues  404 , and available game selection  405 . In doing so, Artificial Intelligence software  135  can maximize cognitive engagement  210 , while monitoring cognitive fatigue  220 . 
     Head movement detection system  270  can include a tracking system of the HMD  120 . The cognitive engagement detection device  200  for measuring cognitive engagement  210  can include any of the sensors or system  230 ,  240 ,  250 ,  260 ,  270 , or a combination thereof. Additionally, the cognitive engagement detection device  200 , singularly or collectively, can provide feedback  280  to the HMD  120  processor  130 , or the separate computer  190 , on measure(s) obtained from the patient  17 . The HMD  120  processor  130  or separate computer  190  can then adjust the game cognitive training scenes  400  accordingly. 
       FIG. 4  is a front view of the HMD  120  of the system  100  according to the present disclosure. As shown, the HMD  120  can include straps  310  configured to keep the display  320 , located inside the HMD  120 , attached to the patient&#39;s  17  forehead  330 . A display  320  can present game scenes  400  to the patient  17 . It is further understood by those skilled in the art that the HMD  120  can include a head movement detection system  270  configured to determine the patient&#39;s  17  head movement and adjust game cognitive training scenes  400  accordingly. The head movement detection system  270  can include one or a plurality of cameras  271 . The cameras  271  can be infrared cameras and can also be used to measure movements of the game controllers  140  held by the patient  17 . 
       FIG. 5  is a perspective view of an HMD  120  of the system  100  according to the present disclosure. The cognitive engagement detection device  200  for measuring cognitive engagement can be incorporated into a compliant surface  233  of the HMD  120  that can be placed on, and around, the forehead area  330  of the patient  17 . The cognitive engagement detection device  200  for determining cognitive engagement  210  can be formed from a plurality of galvanic skin response sensors  231 , and the means  230  can be further formed from a plurality of temperature sensors  241 , such as those known in the art. As shown in  FIG. 5 , galvanic skin response sensors  231  and temperature sensors  241  can be placed side by side, and in an alternating fashion on the compliant area  322  of the HMD  120 . 
     The HMD  120  can be configured such that the patient&#39;s  17  forehead  330  contacts the galvanic skin response sensors  231  and temperature sensors  241  when the patient  17  wears the HMD  120 . In this case, such contact can be due to elasticity and shape of the HMD  120  and straps  310 , as well as placement of the galvanic skin response sensors  231  and temperature sensors  241  in the HMD  120  compliant area  322 . For example, the HMD  120  compliant area  322  can press the galvanic skin response sensors  231  and temperature sensors  241  against the forehead area  330 . Circuitry of the galvanic skin response sensors  231  and temperature sensors  241  can be in communication with (e.g., wired to) the controller module  245 , which can be located on an exterior surface of the HMD  120 . The controller module  245  can include a power means  246  to provide electricity needed by circuitry of the galvanic skin response sensors  231  and temperature sensors  241 . Additionally, the controller module  245  can include a processor  247  and a communication means  248 . Such communication means  248  can be used to send data from circuitry of cognitive engagement detection device  200  to the microprocessor  130 , so to affect one or more changes in game cognitive training scenes  400 . 
     The HMD  120  can also include an eye blinking detection system  260  and an eye gaze detection system  261 . The blinking detection system  260  can be in the form of specialized glasses  267 . The glasses  267  can also include the eye gaze detection system  261 . Both blink rate and eye gaze are known to correlate to cognitive state  264  of a patient  17 . The glasses  267  are not necessarily shaped similar to standard glasses (e.g., eyeglasses), and do not necessarily contain lenses, as exemplified by Pupil Lab&#39;s Core eye tracking headset. According to some aspects of the present disclosure, the eye blinking detection system  260  and eye gaze detection system  261  can be mounted directly within the HMD  120 , without the use of the specialized glasses  267 . 
       FIG. 6  shows a headband  266  and specialized glasses  267  of the system  100 , according to the present disclosure, positioned on the patient  17 . If the patient  17  does not wear the HMD  120 , as discussed in connection with  FIGS. 4 and 5 , the means  230 ,  240  can be provided on the headband  266 . As shown in  FIG. 6 , the headband  266  can be oriented such that the means  230 ,  240  are pressed against the forehead area  330  of the patient  17 . The headband  266  can also incorporate a controller module  345 . In the configuration of  FIG. 6 , the patient  17  can observe game cognitive training scenes  400  on the tablet  170  while wearing the specialized glasses  267 . As discussed herein, the glasses  267  can include a blinking detection system  260  and an eye gaze detection system  261 . For example, the glasses  267  can be those available commercially from Pupil Labs. The headband  266  can also include a wireless communication means  248  which transmits data from the means  230 ,  240 ,  260  to the tablet  170  to affect content of the game cognitive training scenes  400 . In the configuration of  FIG. 6 , the game scene  400  can always be viewed by the patient  17 . The head movement detection system  270  can also be incorporated in the headband  266  to determine when the patient  17  looks away from the game cognitive training scene  400 . According to some aspects of the present disclosure, the head movement detection system  270  can include a six (or more)-degree of freedom tracker  275 , inertia sensors  276 , ultrasonic sensors  277 , vision cameras  278 , magnetic trackers  279 , other technologies for tracking head movement known in the art, or a combination thereof. 
     Eye gaze  290  and spontaneous blink rates  291  are complementary measurements of cognitive engagement  210  of the patient  17 . According to some aspects of the present disclosure, one or more additional physiologic sensing elements can be included in the system  100  that will have complemental, but distinct measurement capabilities for the purposes described herein. As described herein, one or more custom therapeutic games  145  can be played with one, or both, arms  150  and one or both controllers  140 , so to also improve upper body motor function. 
       FIGS. 7A-C  illustrate systems and methods for measuring cognitive improvement and transmitting results to a remote database. Specifically,  FIG. 7A  is a diagram illustrating a customization system  1100  for a game-based therapy session  1000 , according to the present disclosure. As shown, a multitude of game scenes  400 , when played by the patient  17 , form a therapy session  1000 . A session customization system  1100  is provided that allows game difficulty  405  and game duration  450  of the game-based therapy session  1000  to be set. The session customization system  1100  can include an Artificial Intelligence software  135 , which sets the game scenes  400  based on a plurality of inputs  401 . The inputs  401  to the Artificial Intelligence software  135  can include, but are not limited to, patient  17  past performance  420  when playing game scenes  400 , cognitive medication  144  taken by the patient  17 , whether the patient  17  is on oxygen flow  430  (or not), availability  440  of game scenes  400  to be played by the patient  17 , duration  450  of game scenes  400 , difficulty  405  of game scenes  400 , interaction modality  460  used to play game scenes  400 , and cognitive engagement  210  of the patient  17  when playing game cognitive training scenes  400 . 
     Those skilled in the art will understand that sufficient brain oxygenation  431  is needed for proper cognitive functioning  432 . For example, U.S. Pat. No. 9,724,598, entitled “Bimanual Integrative Virtual Rehabilitation Systems and Methods” to Burdea, the entire disclosure of which is hereby incorporated by reference, teaches that extra oxygen meant to help neural activity by improving brain oxygenation is fed to a patient from an oxygen tank while the patient manipulates game avatars. 
     Biosensors baseline  410  can be used to interpret biosensor data  415  when deciding level of cognitive engagement  210 . Biosensor data  415  can be generated by the blinking detection system  260 , and the head movement  269  detection system  270 . Any number of skin temperature sensors  230 , skin conductance circuitry  240 , blood oxygenation sensor  250 , or combination thereof can also contribute to biosensor data  415 . Valid interpretation of biosensor data  415  can be based on the biosensor baseline  410  for each of above mentioned biosensors. For example, the blinking detection system  260  will provide a blinking rate  261 . 
       FIG. 7B  is a diagram illustrating aspects of establishing the biosensor baseline  410 , according to the present disclosure. As illustrated in  FIG. 7B , while establishing the biosensor baseline  410 , the blinking rate  261  of the patient  17  is measured before the start of the game therapy session  1000 . Methods of measuring blinking rate  261  are those discussed herein, such as using the glasses  267 , for example, Pupil Lab&#39;s Core headset, previously described. Special scenes (such as startling scenes  1110 , or relaxing scenes  1120 ) can be played to determine blink rate  261  of the patient  17 . Target objects  1130  in focusing scenes can be played to determine speed of eye gaze  290  adjustment to follow a moving object  1130  or lack thereof. Other methods can be used to measure the patient&#39;s  17  eye gaze  290  and blink rate  261 , before interacting with game scenes  400  during the session  1000 . 
     Similarly, head movement data  269  can be obtained during biosensor baseline  410 , to determine how much movement a head has from a neutral position  777 . For example, the patient  17  can be presented with an object of interest  778  to look at, which does not normally require head turning. If the patient  17  constantly moves their head  779  to look away from the object of interest  778 , it is indicative of lack of cognitive engagement  210 . Other methods can be used for determining biosensor baselines  410  and methods described herein are only examples of what is possible and what is needed by the Artificial Intelligence software  135  to determine changes from baseline  410  during the session  1000 . Following biosensors baseline  410 , the patient  17  using the system  100  (see  FIG. 2  above), can interact with one or a plurality of game scenes  400 , using one or both of the game controllers  140 . The game cognitive training scenes  400  can be integrative, such that the patient  17  will need to solve cognitively demanding problems  1033 , while repeatedly reaching out with one or both game controllers  140 . While doing so, patient&#39;s  17  hand  160  movements can be tracked, for example, wirelessly by all-in-one HMD  120 . 
     During each session  1000  Artificial Intelligence software  135  can track the patient  17  past performance  420  when interacting with any of a plurality of game scenes  400 . The patient  17  past performance  420  can be understood to mean past error rates, past game scores, past game difficulty level  405  and game duration  450 , and other such graphics scene  400 -derived variables. Past performance  420  when tracked over a sequence of sessions  1000  can allow Artificial Intelligence software  135  to determine if cognitive improvement  222  in the patient  17  has occurred. Cognitive improvement  222  is then transmitted to the remote database  105  of the system  100  and monitored by the remote clinician  106 . 
       FIG. 7C  is a diagram illustrating game scene selection and availability for a therapy session  1000 , according to the present disclosure. A plurality of different game cognitive training scenes  400  can be available at the beginning of each session  1000 . For example, a number of game cognitive training scenes  400  constituting game availability  440 , can be initially set by the remote clinician  106 , and communicated to the artificial intelligence software  135 . Game availability  440  can be initially be a subset of all available games. Subsequently, game availability  440  can be increased or decreased by the artificial intelligence software  135 . The artificial intelligence software  135 , according to some aspects of the present disclosure, can increase game availability  440  resulting in a larger number of different game cognitive training scenes  400  to motivate the patient  17 . Increased motivation leads to increased cognitive engagement  210 , and allows for longer durations of the session  1000 . Conversely, the artificial intelligence software  135  can reduce the duration of the session  1000  to minimize cognitive fatigue  220 . 
     Interaction modality  460  can relate to whether the patient  17  uses one or two game controllers  140  of system  100 . It is known to those skilled in the art that divided attention is problematic for the elderly. When the patient  17  interacts with game cognitive training scenes  400  using two game controllers  140 , divided attention occurs, possibly leading cognitive fatigue  220  to occur sooner. To minimize cognitive fatigue  220 , the artificial intelligence software  135  can switch the game cognitive training scene  400  to a variant played by the patient  17  with a single controller  140 . 
     The remote clinician  106  can introduce remote diagnostic sessions  1200  aiming to reassess level or cognitive impairment  1320  of the patient  17 . For example, the clinician  106  can prescribe such remote diagnostic sessions  1200  periodically. Such remote diagnostic sessions  1200  can utilize the system  100  in the patient&#39;s  17  home  102 . The diagnostic sessions  1200  can follow, for example, methods previously taught in U.S. Patent Application Pub. No. 2016/0038075, entitled “Bimanual Computer Games System for Dementia Screening,” to Burdea et al. 
     The artificial intelligence software  135  can maximize cognitive improvement  222  while minimizing cognitive fatigue  220 . Specifically, the artificial intelligence software  135  can detect cognitive fatigue  220  when the patient&#39;s  17  current performance  421  within the session  1000  diminishes over repeated interactions with the same game cognitive training scene  400 , despite the patient&#39;s  17  maintaining cognitive engagement  210 , and despite game difficulty  405  and game duration  450  being kept constant within the session  1000 . 
     Upon detecting cognitive fatigue  220 , the artificial intelligence software  135  can take remedial actions  1330 . Such remedial actions  1330  to address cognitive fatigue  220  of the patient  17  can include, but are not limited to, reducing game difficulty  405 , reducing game duration  450 , introducing a brief rest period in session  1000 , turning on oxygen flow  430 , or increasing oxygen flow  430  (if oxygen flow  430  had already been turned on). 
     According to some aspects of the present disclosure, the all-in-one HMD  120  can have less performance graphics hardware  1340  than dedicated graphics hardware  1350  usually found in commercially available PCs, laptops, game consoles or other computing devices. Graphics cognitive training scene  400  content complexity  1360  can be reduced to maintain a high graphics refresh rate  1370 . It is understood by those skilled in the art that graphics refresh rate  1370  can represent a number of images of a game scene  400  calculated by the graphics hardware  1340  every second. It is further understood that the system  100  can use graphics scenes  400  that have reduced content complexity  1380  to not overwhelm the patient  17 . Reduction of graphics scene  400  content complexity  1380 , regardless of game level of difficulty  405 , is another method to diminish incidence of cognitive fatigue  220 . 
       FIGS. 8 and 9  are graphical user interfaces generated by the system  100  of the present disclosure showing two therapeutic game scenes  400  with reduced content complexity  1380  used with the system  100 . For example,  FIG. 8  is a Numbers Avalanche game  2300 , which asks the patient  17  to dig though ice tiles  2310  to rescue people trapped in a cabin. Each of a plurality of ice tiles  2310  can have an associated number  2315  displayed on it. The patient&#39;s  17  pickaxe avatar  2340  can successfully break ice tiles  2310  with a correct answer  2350  to arithmetic or vocabulary problem  2360  displayed on the game scene  400 . As shown, the game scene  400  can ask the patient  17  to solve a subtraction equation  2360 , for example, “90−50=?” which has a correct answer  2350  of “40.” If the patient  17  breaks the correct answer tile  2350 , thus solving the subtraction equation  2360 , a hole  2370  appears in the ice wall  2380 . The game  2300  can be played with one game controller or two game controllers  140 . According to some aspects of the present disclosure, the two game controllers  140  control two pickaxe avatars  2340 . 
     In the game  2300  if the patient  17  incorrectly solves the problem  2360 , then ice tiles  2310  will not be broken and the hole  2370  will not appear in the ice wall  2380 . After several correctly answered questions  2360 , the ice wall  2380  can be cleared as the patient  17  breaks a multitude of ice tiles  2310 . Higher game difficulty levels  405  can make the patient  17  break through a multitude of ice walls  2380  in order to reach the cabin and rescue the people trapped inside. Still higher levels of difficulty  405  of game  2300  can require patient  17  to complete game scene  400  in a limited time, requiring increased use of both pickaxe avatars  2340 , thus increasing split attention training. 
       FIG. 9  is a Language Race game  3400  of the system  100 . The game  3400  can ask the patient  17  to steer a car avatar  3410  through a plurality of gates  3420  using the game controllers  140 . Each gate  3420  can display a word  3421  at its top. The patient  17  can be presented with a language problem  3460  on the game cognitive training scene  400 . For example, the patient  17  can be asked to select a synonym to the word “Mad,” from among three words  3421  displayed at the top of three adjacent respective gates  3420 . The patient  17  can be asked to steer the car avatar  3410  through the gate  3420  displaying the correct answer  3450  (e.g., the word “Angry”). In so doing, the patient  17  needs to successfully split attention between driving the car avatar  3410  and solving the language problem  3460  in a limited time  3500 . Due to the limited time  3500 , the game  3400  trains processing speed  3510  and focus  3520 . Higher game  3400  difficulty  405  can correspond to a faster car avatar  3410 , which requires faster reaction time. Additionally, the patient  17  can be presented with two, four, five or more gates  3420  from which to select the correct answer gate  3450  to problem  3460 . 
     A multitude of other game cognitive training scenes  400  are possible, and alternating different game scenes  400  is a method to maintain cognitive engagement  420 . To facilitate training at home  102 , a Session Scheduler can pre-load weekly games  2300 ,  3400  and similar sequences. According to some aspects of the present disclosure, the patient  17  can be allowed to select what game scene  400  to play next using one or a multitude of game controllers  140 . The system  100  of the present disclosure can include a Wi-Fi high-speed internet connection with a cloud server. A cloud server can store game performance and biosensor data. These data are accessible to the remote clinician  106 , or to the caregiver  18 . An automatic session report software can document cognitive areas trained, and other objective outcomes. 
     Moreover, as discussed below in connection with  FIGS. 10-14 , the system  100  of the present disclosure can be implemented with one or more cognitive medications, thereby improving the efficacy of both the medications and the system  100 . Currently, there is no treatment to cure Alzheimer&#39;s disease, but cognitive medications that slow the progression of this disease are available. However, currently available cognitive medications have efficacy on only about 25% of patients taking such cognitive medication alone. Furthermore, such slowing of cognitive decline only lasts about six (6) months from diagnosis, after which such cognitive medication  144  loses effect. 
     Additionally, combining the system  100  with cognitive medications can drastically reduce the financial impact of treatment on patients. For example,  FIG. 10  is a diagram illustrating the annual per-capita healthcare cost as a function of cognitive disease  223  severity. As illustrated in  FIG. 10 , there is a 200% cost differential between $30,000/year in healthcare costs for a patient  5000  who has mild cognitive impairment (“MCI”) and $60,000/year in healthcare costs for a patient  5001  who has stage III (advanced) Alzheimer&#39;s Disease. 
     It is well understood that the cognitive disease  223  will progress over time. Furthermore, current studies estimate that patients with Alzheimer&#39;s disease have a life expectancy of 7 to 10 years if diagnosed in their early 70s, but only 3 years if they are in their 90s when diagnosed. 
     Early detection of mild cognitive impairment for the patient  5000  can lead to slower cognitive decline, and less cognitive disease  223  severity later in life if a plurality of treatments are prescribed. Such plurality of treatments to slow cognitive decline can include one or more of cognitive medication  144 , socializing, yoga, cognitive boosting food supplements, and physical exercise. System  100 , when implemented with any of the plurality of treatments enumerated, further reduces the cognitive disease  223  severity over time. 
     Costs associated with treatment depend on the severity of the cognitive disease  223 . As such, implementing the systems and methods of the present disclosure in connection with one or more of the medications and treatments described herein produces significant costs savings when compared to the costs of treatment without system  100 . For example,  FIG. 11  is a diagram illustrating the treatment cost savings produced by the system  100  of the present disclosure. As shown, such healthcare costs savings increase with patient age and cognitive disease severity once system  100  is added to standard of care (e.g., at year one (1) on the diagram shown in FIG.  11 ). Such costs savings are represented by the area between the two cost progression curves (e.g., with system  100  and without system  100 ). Costs can be for representative of cognitive medication administered with interaction with game cognitive training scenes  400 , vs. cognitive medication alone. Additional savings stem from the fact that incidence of patients with Alzheimer&#39;s disease is growing. Further still, adding interaction with game scenes  400  of system  100  can lengthen the period of time over which cognitive medication  144  remains beneficial to the patient  17 . 
       FIG. 12  is a diagram illustrating the effect of the system  100  of the present disclosure on the progression of Alzheimer&#39;s disease from MCI to stage III (advanced stage). As shown, systems  100  utilizing cognitive medication  144  and therapeutic game scenes  400 , with added oxygen to insure sufficient brain oxygenation  431  results in less severity of the cognitive disease  223  over time, as compared to systems  100  which utilize cognitive medication  144  and therapeutic game scenes  400 , in the absence of sufficient brain oxygenation  431 . In both cases, there is a substantially smaller increase in the severity of cognitive disease  223  over time, compared to the increase in the severity of cognitive disease  223  when only cognitive medication  144  is taken. 
       FIG. 13  is a diagram illustrating a method  500  for treating a cognitive disease, according to some aspects of the present disclosure. More specifically,  FIG. 13  illustrates a method  500  for utilizing therapeutic game scenes  400  wherein a person  501  determines a dose of a cognitive medication  144  to be administered to the patient  17 . The person  501  may be a person assisting in the care of the patient  17  such as a clinician  106  or caregiver  18 , a researcher  510  studying cognitive medication  144 , or other person  520  involved in determining the dosage of a cognitive medication  144  for the patient  17 . The patient  17  receives a cognitive medication  144  as well as therapeutic game scenes  400  provided by the system  100 . The system  100  obtains game play data  502  from the patient&#39;s  17  interaction with game scenes  400 . The system  100  performs game data processing  503  and produces an output  504 . The output  504  contains information on the patient&#39;s  17  cognitive state  505 . The cognitive state  505  can include results of the system&#39;s  100  game data processing  503  including the patient&#39;s  17  cognitive aptitude, emotional disposition, impact of the cognitive medication  144  on the patient  17 , adverse side effects of the cognitive medication  144  on the patient  17 , and other data acquired by the system  100  during the patient&#39;s  17  interaction with the system  100  during gameplay. According to some aspects of the present disclosure, the output  504  can include data on the cognitive improvement  222  of the patient  17  utilizing the system  100 . 
     The output  504  can be received by a person  501 ,  510 ,  520 ,  18 . One or more of the persons  501   510 ,  520 ,  18  can utilizes the output  504  to modify the dosage of the cognitive medication  144 . Utilization of the output  504  allows for titration of the cognitive medication  144 , allowing for a reduction in dosages of the cognitive medication  144 , a reduction in side effects of the cognitive medication  144 , or an extension of the duration over which the cognitive medication  144  shows efficacy for the patient  17 . 
       FIG. 14  is a diagram illustrating a method  600  for treating a cognitive disease, according to some aspects of the present disclosure. Method  600  is similar to method  500 , discussed in connection with  FIG. 13 , except for the distinctions noted herein. More specifically,  FIG. 14  depicts method  600 , in which the person  501  of method  500  is replaced with a cognitive medication dosage determination system  601 . Cognitive medication dosage determination system  601  can receive the output  504  to determine a dosage of the cognitive medication  144 . The cognitive medication dosage determination system  601  can utilize machine learning, artificial intelligence software, or the like, together with patient information and output  504 , in determining the correct dosage of the cognitive medication  144  for the patient  17 . According to other aspects of the present disclosure, system  601  can automatically switch the type of cognitive medication  144  used to treat the patient  17 . 
     Exemplary cognitive medications can include, but are not limited to, donepezil (marketed under the brand name Aricept®), which is approved to treat all stages of Alzheimer&#39;s disease, and galantamine (marketed under the brand name Razadyne®), which is approved for mild-to-moderate stages of Alzheimer&#39;s Disease. For example, with regard to donepezil, an initial dose of 5 mg per day is recommended, which is thereafter increased to a maintenance dose. For mild to moderate Alzheimer&#39;s disease, a maintenance dose of 10 mg per day of donepezil is recommended, while for cases of moderate to severe Alzheimer&#39;s disease, the maintenance dose is increased to 23 mg per day after the patient has been on a dose of 10 mg per day for at least three (3) months. With regard to galantamine, the recommended initial dose is 8 mg per day, which is increased to a maintenance dose that is between 16 and 24 mg orally once a day based on clinical benefit and tolerability. However, when combined with the cognitive training systems and methods described herein, the dosages of these cognitive medications can be reduced. For example, a patient prescribed 23 mg per day of donepezil can have their dosage reduced to 10 mg per day when administered in connection with the cognitive training systems of the present disclosure. Similarly, a patient prescribed 24 mg a day of galantamine (e.g., or another dosage on the upper end of the recommended range) can have their dosage reduced to 16 mg per day (e.g., or another dosage on the lower end of the recommended range) when administered in connection with the cognitive training systems of the present disclosure. Further still, the systems and methods described herein (e.g., in connection with  FIGS. 13 and 14 ) can recommend that a patient switch from donepezil to galantamine, or vice versa, if the system determines that the other cognitive medication is more beneficial (e.g., increased efficacy, lower side effects, etc.) for the patient. 
     Having thus described the systems and methods in detail, it is to be understood that the foregoing description is not intended to limit the spirit or scope thereof. It will be understood that the embodiments of the present disclosure described herein are merely exemplary and that a person skilled in the art may make any variations and modification without departing from the spirit and scope of the disclosure. All such variations and modifications, including those discussed above, are intended to be included within the scope of the disclosure.