US20100076334A1 - Alzheimer's cognitive enabler - Google Patents

Alzheimer's cognitive enabler Download PDF

Info

Publication number
US20100076334A1
US20100076334A1 US12/233,817 US23381708A US2010076334A1 US 20100076334 A1 US20100076334 A1 US 20100076334A1 US 23381708 A US23381708 A US 23381708A US 2010076334 A1 US2010076334 A1 US 2010076334A1
Authority
US
United States
Prior art keywords
eeg waveform
eeg
data
patient
stored
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US12/233,817
Other languages
English (en)
Inventor
Martine Rothblatt
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
UTASIA Inc
Original Assignee
Unither Neurosciences Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Unither Neurosciences Inc filed Critical Unither Neurosciences Inc
Priority to US12/233,817 priority Critical patent/US20100076334A1/en
Assigned to Unither Neurosciences, Inc. reassignment Unither Neurosciences, Inc. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: ROTHBLATT, MARTINE
Priority to JP2011527893A priority patent/JP5643207B2/ja
Priority to ES09815029.5T priority patent/ES2528029T3/es
Priority to CA2737183A priority patent/CA2737183C/en
Priority to CN2009801357066A priority patent/CN102149319B/zh
Priority to KR1020117008452A priority patent/KR101520524B1/ko
Priority to EP09815029.5A priority patent/EP2344031B1/en
Priority to PCT/US2009/056837 priority patent/WO2010033461A2/en
Priority to TW098131679A priority patent/TWI520714B/zh
Publication of US20100076334A1 publication Critical patent/US20100076334A1/en
Priority to US13/966,686 priority patent/US20140180159A1/en
Priority to US14/724,982 priority patent/US10521666B2/en
Priority to US16/720,951 priority patent/US11301680B2/en
Priority to US17/692,515 priority patent/US20220198798A1/en
Assigned to UTASIA INC. reassignment UTASIA INC. CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: Unither Neurosciences, Inc.
Abandoned legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/70—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A61B5/377—Electroencephalography [EEG] using evoked responses
    • A61B5/378—Visual stimuli
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/369—Electroencephalography [EEG]
    • A61B5/377—Electroencephalography [EEG] using evoked responses
    • A61B5/38—Acoustic or auditory stimuli
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4076—Diagnosing or monitoring particular conditions of the nervous system
    • A61B5/4088—Diagnosing of monitoring cognitive diseases, e.g. Alzheimer, prion diseases or dementia
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F1/00—Details not covered by groups G06F3/00 - G06F13/00 and G06F21/00
    • G06F1/16—Constructional details or arrangements
    • G06F1/1613—Constructional details or arrangements for portable computers
    • G06F1/163—Wearable computers, e.g. on a belt

Definitions

  • Embodiments of the present invention relate to apparatus, systems and methods for improving the quality of life of an individual suffering from a debilitating disease as well as members of interest affected by the sufferer's diminished capacity.
  • Debilitating diseases which affect a person's mental capacity are especially difficult to endure, both for the individual suffering from the disease as well as family members, friends and caregivers who must care for the individual.
  • dementia One form of a mentally debilitating disease is dementia.
  • Dementia is a brain disorder that seriously affects a person's ability to carry out daily activities.
  • the most common form of dementia among older people is Alzheimer's disease, which initially involves the parts of the brain that control thought, memory, and language.
  • memory loss shown as a difficulty to remember recently learned facts, is the most common symptom, although it is often initially misdiagnosed as age-related memory-loss or stress. Later symptoms include confusion, anger, mood swings, language breakdown, long-term memory loss, and the general withdrawal of the sufferer as his or her senses decline.
  • Alzheimer's disease there is no cure for Alzheimer's disease. Also, there are no effective ways for an Alzheimer's disease sufferer to effectively interact with family and friends at the various stages of the disease.
  • an Alzheimer's cognitive enabler is disclosed that allows an Alzheimer's disease suffer to effectively interact with family, friends, caregivers, etc. at the various stages of the disease.
  • a computing device that enables user interaction when the user is in a mentally debilitating state includes a memory configured to store electroencephalogram (EEG) waveform signals.
  • the EEG waveform signals are generated by associated recognition data.
  • Response data is generated based on the associated recognition data and stored in memory.
  • An input component is configured to receive an EEG waveform signal from a user.
  • a processor is configured to compare the received EEG waveform signal with the stored EEG waveform signals to determine if the received EEG waveform signal matches a stored EEG waveform signal.
  • An output component is configured to automatically output the response data generated by the associated recognition data based on the determination from the processor.
  • the computing device includes a memory, an input component, a processor and an output component.
  • the memory is configured to store EEG waveform signals.
  • the EEG waveform signals are generated by associated recognition data. Response data is generated based on the associated recognition data and stored in memory.
  • the input component is configured to receive an EEG waveform signal from a user.
  • the processor is configured to compare the received EEG waveform signal with the stored EEG waveform signals to determine if the received EEG waveform signal matches a stored EEG waveform signal and the output component is configured to automatically output the response data generated by the associated recognition data based on the determination from the processor.
  • the server computer is configured to update EEG waveform signals, associated recognition data and response data stored in the memory of the computing device.
  • a method for enabling user interaction when the user is in a mentally debilitating state includes storing electroencephalogram (EEG) waveform signals, whereby the EEG waveform signals are generated by associated recognition data.
  • the method also includes the steps of storing response data generated based on the associated recognition data and receiving an EEG waveform signal from a user.
  • the method further includes the steps of comparing the received EEG waveform signal with the stored EEG waveform signals and determining that the received EEG waveform signal matches a stored EEG waveform signal.
  • the method also includes the step of automatically outputting the response data generated by the associated recognition data based on the determining step.
  • FIG. 1 illustrates a user with an embodiment of the Alzheimer's Cognitive Enabler (ACE) device of the present invention
  • FIG. 2 illustrates an operating environment in which the ACE device, system and method of the present invention may operate
  • FIG. 3 is a flowchart depicting steps performed within the ACE device in accordance with one embodiment of the present invention.
  • an Alzheimer's cognitive enabler allows the Alzheimer's disease patient to draw upon his or her less-affected cognitive waveforms to trigger recognition and conversation functions that are blocked by beta amyloid plaque in the brain, but can be made available on the ACE.
  • the ACE may be equated to or conceptualized as a “cognitive wheelchair” providing mental assistance as compared to physical assistance provided by a conventional wheelchair.
  • ACE device 100 being carried by user 110 (i.e., an Alzheimer's patient) in FIG. 1 .
  • the ACE device 100 has access to input devices such as an EEG device 150 , video camera 121 , microphone 124 , and input device 122 (e.g., a keyboard, a hand-writing recognition device, etc.).
  • the ACE device 100 also has access to a visual display device 132 and a speaker output device 134 .
  • the input and output devices may be integrated together with the ACE device 100 into a single device, while in alternative embodiments the ACE device 100 may be a separate device that has the ability to accept input from and provide output to (e.g., via physical or wireless connections) any of a variety of devices which may be accessible (e.g., carried by the user or located nearby in the environment).
  • the ACE device 100 further includes a processor 160 for processing information stored in its memory 165 as discussed in greater detail below.
  • the invention is further illustrated by, though in no way limited to, the following particular embodiments and examples.
  • a variety of situations are illustrated for which user 110 may wish to store information that can be later used to assist the user 110 to interact with persons 170 .
  • the ACE device 100 is prescribed for user 110 at the user's first sign of cognitive decline.
  • the Alzheimer's patient, family member(s) and/or caregivers would load the ACE device 100 with the patient's salient images, voices data, memories, etc. and associated EEG waveforms.
  • Via artificial intelligence technology it is not critical that every bit of data has an associated EEG waveform.
  • the artificial intelligence program running the ACE device 100 uses relational database technology to bring together related images after an index image is EEG triggered. More generally, the ACE device 100 is configured to conduct a normal conversation with a person based on stored data and advanced artificial intelligence-based chatbot software upon an EEG waveform associated with just recognition of the person. In general, any EEG waveform will trigger some conversational capability out of the ACE device 100 , with such conversational capability being as close to the motivations that gave rise to the EEG waveform as the stored associations permit.
  • the Alzheimer's patient While wearing EEG device 150 , the Alzheimer's patient is able to train the ACE device 100 to react as he or she would in given situations when interacting with others. Thereafter, once the disease has progressed, the ACE device 100 can be used to interact with others on behalf of the Alzheimer's patient using images and sound recognition routines, conversational software and patient-specific settings previously stored and continuously updated as discussed in greater detail below.
  • the user 110 may wish to store a variety of information about the person for later recollection.
  • the user 110 can use the video camera 121 and microphone 124 to capture video and audio recordings of the encounter.
  • the user 110 can also use the video camera 121 to capture other current information about the environment which may assist in later recollection about the encounter, such as a video image of the location in which the encounter occurred.
  • the user 110 can use the microphone 124 to record dictated information about the person 170 , such as the person's name, address, e-mail address, phone number, etc.
  • the ACE device 100 can then store this dictated information as an audio recording, or can instead perform voice recognition on the dictation in order to produce a textual version of the information.
  • the user 110 can provide some, or all of the information about the person to the ACE device 100 directly as text via text input device 121 .
  • the user 110 can provide information to the ACE device 100 via any other available input means, such as transmitted information from a portable device (not shown) that the person might be carrying (e.g., another ACE device).
  • the ACE device 100 associates the various information with the received EEG waveform signal from the EEG device 150 .
  • the ACE device 100 is configured such that an Alzheimer's patient who sees person 170 again, but fails to recognize him, could automatically trigger an appropriate greeting for person 170 based on the EEG waveform generated when the Alzheimer's patient's see that person again but is unable to recognize him.
  • the ACE device 100 may be in the form of a general-purpose body-mounted wearable computer worn by user 110 .
  • Many wearable computers travel with the user, such as being strapped or attached to a user's body or clothing or being mounted in a holster.
  • the wearable computer has a variety of user-worn user input devices including the microphone 124 , a hand-held flat panel display with character recognition capabilities, and various other user input devices 222 .
  • the computer has a variety of user-worn output devices that include the hand-held flat panel display, an earpiece speaker, an eyeglass-mounted display, etc.
  • the computer can also receive information from various user sensor input devices and from environment sensor input devices, including the video camera 121 .
  • the ACE device 100 can receive and process the various input information and can present information to the user 110 on the various output devices.
  • the ACE device 100 receives various input information from the input devices that can be stored.
  • the general-purpose body-mounted wearable computer may include a touch screen feature (which may approximate the size of a human head, but could be any size, for example) that enables the ACE device 100 to respond to tactile as well as audio and video inputs. For example, if the Alzheimer's patient was in a late stage of the disease, the patient's omnipresent, naturally moving image on the touch screen could be kissed, and the programming features of the ACE device 100 would recognize that input and respond in the Alzheimer patient's voice, with a reply such as “THANK YOU FOR THE KISS GRANDSON.”
  • an ACE system and method of the present invention operates primarily in a computer network environment.
  • the ACE system 20 includes a program system administration site 10 which includes server computer 12 and a system database 14 and a number of workstations 18 that communicate with the server computer 12 .
  • the workstations 18 may be used by patients/caregivers 18 a, family members 18 b or friends 18 c or any other system participant 18 d.
  • the workstation 18 may be a stand alone personal computer (PC) based system with wireless internet connectivity, and Smart Phones with Wi-Fi connectivity to an off-site server, the same as the ACE device 100 .
  • PC personal computer
  • the off-site server may provide software upgrades, act as a repository for certain database functions and provide diagnostic functions.
  • the wireless-linked feature of the ACE device 100 and the ACE system 20 helps to ensure that no data is lost in the event of a failure, theft, breakage or loss of the ACE device 100 .
  • All data from the ACE device 100 is automatically uploaded to server computer 12 and then to system database 14 for safe storage. This stored data can be readily downloaded into a replacement ACE device.
  • the personal computer typically will require a video monitor, sound and video cards.
  • the workstation 18 may be any device capable of interacting with a computer network, including such devices as personal digital assistance (PDA) and cellular phones.
  • PDA personal digital assistance
  • Additional system requirements include a PC compatible video camera, PC compatible directional microphone, speakers, and a Blue Tooth commercial EEG headset.
  • a tablet PC, and voice activated microphones may be required in addition to the above.
  • Embodiments of the present invention also may require onsite training and a patient support facility 24 in some cases or the patient may require assistance in utilizing the invention, in both instances the ACE system 20 is amenable to additional users assisting the patient in providing the input or in training the patient in utilizing the supplemental system input devices.
  • Resident on the sever computer 12 of the ACE system 20 is an Alzheimer's disease recognition program 16 .
  • server 12 has installed therein, newer versions of conversational software that are more sophisticated in replicating normal conversational patterns.
  • Such software is configured to review saved conversations between the patient and family to identify errors and adjust conversational parameters. This is analogous to how “auto-tune” software works with digital music, in that a person's voice can be analyzed for being off-tune and corrected.
  • the ACE device 100 and ACE system 20 are trained via patient interaction in each of the following instances: recording the patient's voice, obtaining varying minutes of digital video of the patient's facial expressions (speaking, laughing, and joy, sadness) to obtain a viseme database.
  • a viseme is defined as a unit of speech in the visual domain; how ones face forms words and expressions.
  • the ACE device 100 and ACE system 20 build a lexicon of patient's visemes from video taping the patient. In the case where the patient cannot participate, the lexicon is built synthetically. In the synthetic process, the patient's face is photographed in high definition, for example, and donor visemes are digitally overlaid onto the photographed face of the patient and the result is akin to live animation.
  • videotaping can be performed by trained staff, a caregiver, etc.
  • the patient may also construct, or be assisted in constructing a database of family members and friends (Family/Friends) with whom the patient would wish to interact.
  • the database may also include the contact information for caregivers and health care providers.
  • voice samples of these individuals may be collected from Wi-Fi capable cell phone interactions, as well as prearranged voice recording conducted by training staff.
  • the patient may construct or be aided in constructing, or have constructed by the training staff, a database of responses for their phone (cellular and landline) and PC systems, as well as establishing the pre-sets for when the system responds for them.
  • baseline voice samples of the patient may be used for Alzheimer analysis.
  • the patient may be instructed by a staff member in the training and use of the EEG device 150 .
  • the EEG device 150 serves as an auxiliary data input tool and data collection device for the ACE device 100 and ACE system 20 with the EEG signals serving in place of the PC's mouse, acting as a drawing and pointing/selection agent on the screen, and one capable of dragging and dropping screen based objects.
  • the software is configured to default to running as if the appropriate EEG signal was triggered.
  • “daughter” has a specific EEG, signal but it is not recognized, it will be possible for “daughter” to specify that it is the daughter visiting the patient, and then the ACE device 100 will converse as if the EEG signal for “daughter” had been triggered. Familiarity with the EEG device 150 will also assist the patient in accessing the device and system as the patient's health declines.
  • Baseline EEG samples obtained from patient use may be uploaded to the server 12 and the data may be then analyzed.
  • the patient may be trained to use the voice recognition software as an auxiliary data entry tool. This will allow the patient to more readily enter his or her autobiographical memories, and to use the PC more fully in conjunction with the EEG device 150 . Voice samples from the usage may be utilized for voice synthesis as well as diagnostic analysis.
  • the data collected through phone conversations and interviews with the patient and the patient's Family/Friends may be utilized to assist in constructing affirmative conversations for the ACE device 100 and ACE system 20 to deploy.
  • staff psychologists may conduct interviews with Family/Friends, review personal material and construct a patient autobiographical inventory that will serve as the basis for constructing a conversational database and the autobiographical database stored either in the ACE device 100 or stored remotely on the ACE system 20 .
  • the EEG waveform signal generated from the EEC device 150 is used to retrieve the correct responses.
  • voice and face recognition software is used to identify the initiator of a conversation and then the ACE device 100 and ACE system 20 supplies a correct response set based on the recognition of the initiator of the conversation.
  • the response is profiled based upon the historical psychodynamics between that individual and the patient.
  • the ACE device 100 and ACE system include a profiling methodology which is a psychological framework employed to maximize the therapeutic investment of energy into the suspense of disbelief experienced by the patient's Friend/Family in interacting with a patient avatar.
  • a patient avatar is defined as an audio construct of the patient, one that will have the patient's face, facial expression and voice.
  • the patient avatar will appear on the monitor speaking in the patient's own voice, and to a very large degree, with the patients' own facial expressions. If the patient was unable to participate, the voice will be gender appropriate and pitch and tone balanced.
  • the facial expression may be human and warm and the face will be that of the patient.
  • the ACE device 100 and ACE system 20 may include an emotion software engine that is based upon actual digitally sampled emotions from an Alzheimer's patient.
  • the ACE device 100 and ACE system 20 are configured to portray realistic emotions of the Alzheimer's patient, triggered by EEG waveform signals and/or program-analyzed semantic cues in an conversational software engine.
  • the conversational database generates an appropriate conversational segment in response to a unique speaker from the information stored in the system database 14 or in the memory of the ACE device 100 and then further processed.
  • An example conversation is provided below:
  • Sarah the grand-daughter, is recognized by the ACE device 100 or the ACE system 20 , either by the associated EEG waveform, voice recognition software or face recognition software, the conversation generation then looks up Sarah, recognize her grandmother's pet name for her and that she has a pet named Jo-jo.
  • inputs including videotaping of a patient in scripted conversation conducted by training staff.
  • this may be held over multiple sessions of 15 minute duration totaling 60 minutes in aggregate, for example.
  • the sessions are designed to capture the patient in a variety of emotional responses and facial patterns.
  • the trainer/technician performing the video taping in addition to following the script may be trained in how to provoke the various emotive responses desired in order to capture a variety of facial expression of the patient.
  • the resulting video is then processed into the viseme database for the patient avatar as discussed above.
  • high quality head shots of the patient's designated Family/Friends may be taken by the training staff and input into the ACE device 100 and ACE system 20 for the facial recognition component.
  • the training staff may also sample Family/Friend vocal recordings for input into the voice recognition component.
  • the trainer may take high definition images of the patient's face. Visemes may then be constructed synthetically from the images. The process is one of overlaying the patients face over a “digital donor”, one carries out the process of mapping say, trainer Mary's visemes, removing Mary's characteristic facial features leaving behind a dynamic template, and then mapping the patient's facial features onto the template. This may be a one time process, completed on site by the training staff.
  • ACE device 100 and ACE system 20 outputs according to an embodiment of the present invention
  • text, audio-visual, or audio responses through the patient's phone system (land as well as cellular) and PC/PDA/Smartphone either at the patient's request or at a predetermined setting in response to the diagnostic data gathered from the patient may be output.
  • Video may be processed and synchronized with the patient's visemes to produce a patient avatar. According to one preferred implementation of the present invention, the processing may be conducted by training staff onsite.
  • the ACE device 100 and ACE system 20 when prompted by the initiator, may then cue the conversational database load either in the system database 14 or locally in memory of the ACE device 100 for the initiator and prepare to integrate the speech synthesis engine with the patient avatar in response to the initiators spoken word.
  • voice data obtained from voice control of the PC and from cellular conversations may be analyzed for early onset of the Alzheimer's using currently established diagnostic benchmarks developed for voice recognition technology and the indicia of Alzheimer's disease.
  • This data set may be compared against baseline voice data collected at the patient's initial use of the system.
  • EEG waveform data collected from the patient may be analyzed using currently established protocols for the prediction of or indicia of Alzheimer's disease.
  • ACE system 20 is a system platform that is designed to assist a patient diagnosed in the pre-onset stages of Alzheimer's disease through the later stages of the disease.
  • the preferred model envisions a patient's interacting directly with the ACE device 100 and ACE system 20 , providing inputs both for system training, patient diagnosis and patient memory storage. As the patient becomes infirmed, or feels unable to complete or attend to specific communication based tasks, the device and system provide responses for the patient.
  • the ACE device 100 and ACE system 20 are configured to recognize a vocal prompt and or the face of a member from the Family/Friend indexed in the database 14 or local memory, which will initialize the device and system and will commence conversation with the indexed individual.
  • the patient interacts with the device and system through a number of dimensions.
  • Phone conversations provide profile data for the Family/Friend database-namely, the individuals within the database, voice samples, frequency and duration of interaction; cellular phone data is transmitted via Wi-Fi to the server 12 for storage and analysis.
  • PC based activities may be gradually controlled by supplemental devices, viz., the patient's oral commands (voice recognition) and through EEG waveform based commands.
  • Data collected from the device and system may be transmitted to the server 12 for diagnostic analysis and for use in the patient avatar.
  • the device and system may be engaged by default or by the patient's choice to intervene on any or all communication channels available to the patient. If the perceived deficit reaches a predetermined threshold, the device and system is configured to alert caregivers, healthcare providers, and family members and friends as desired.
  • the patient has some capacity for conversation, or may easily feel fatigue.
  • the patient may wear and may interact with the ACE device and ACE system through the EEG device 150 and may guide the conversation with Family/Friends, selecting conversational elements from the conversational database or elements from his or her autobiographical database via a tablet PC.
  • the patient may also turn the patient avatar on or off. The pre-sets established will determine whether the patient is in a state to make the determination.
  • the ACE device and system When a patient is in a state of decline such that self sustaining conversation is either a burden to the patient or a mental impracticality, the ACE device and system is configured to intervene between the patient and family member, or the patient and the patient's friend.
  • the patient is present, juxtaposed with a video monitor of either the ACE device or ACE system.
  • one speaker at a time engages the patient, with each speaker wearing a voice activated microphone.
  • the device and system Upon speaking to the patient, the device and system is activated via voice and facial recognition using the software provided therein; the patient avatar displays recognition, and enters into a conversation with the initiator.
  • the patient avatar is configured to converse approximately as one would expect an elderly family member: short answers, of durations 20 seconds or less, and for a total conversation length of no more than five minutes per family participant, for example.
  • the conversations with the same party normally will not repeat the same content during the next conservation if (i) the original database is sufficiently robust and (ii) the conversation doesn't duplicate the content, for example. Even in the second instance, for example, there is no assurance that the content of the patient avatar's content would be the same.
  • the content of the conversation may be uploaded to a server, such as server 12 for diagnostic analysis. Specific events referenced by the patient avatar may be accessed by the Family/Friend by accessing the autobiographical database events referenced for that day.
  • the ACE device and system are also configured to monitor patient pain and mood levels via EEG waveform signals output as well as a standard set of outputs (e.g., heartbeat, pulse rate, blood pressure, etc.). All data collected is available to the patient's health care providers and approved subscribers historically and in real-time via Wi-Fi (PC/Smartphone/PDA) or a remote server.
  • Wi-Fi PC/Smartphone/PDA
  • FIG. 3 is a flowchart depicting steps performed within the ACE device in accordance with one embodiment of the present invention.
  • the process begins from a start state S 400 and proceeds to process step S 401 , wherein EEG waveform signals are stored in memory.
  • the EEG waveform signals are generated by associated recognition data.
  • response data generated based on the associated recognition data is also stored in memory.
  • an EEG waveform signal from a user is received.
  • the process step S 404 the received EEG waveform signal is compared with the stored EEG waveform signals.
  • the process proceeds to decision step S 405 where it is determined whether or not the received EEG waveform signal matches a stored EEG waveform signal. If the received EEG waveform signal matches one of the stored EEG waveform signals, the process proceeds to process step S 406 where the response data generated by the associated recognition data is automatically outputted, otherwise, the process returns to process step S 403 .
  • Alzheimer's disease is characterized by a slow, gradual decline in cognition which cause great grief and diminished quality of life to the Alzheimer's disease sufferer as well as his or her family.
  • the ACE device, system and method can significantly ameliorate the diminished quality of life.
US12/233,817 2008-09-19 2008-09-19 Alzheimer's cognitive enabler Abandoned US20100076334A1 (en)

Priority Applications (13)

Application Number Priority Date Filing Date Title
US12/233,817 US20100076334A1 (en) 2008-09-19 2008-09-19 Alzheimer's cognitive enabler
PCT/US2009/056837 WO2010033461A2 (en) 2008-09-19 2009-09-14 Alzheimer's cognitive enabler
KR1020117008452A KR101520524B1 (ko) 2008-09-19 2009-09-14 알츠하이머 인지 인에이블러
EP09815029.5A EP2344031B1 (en) 2008-09-19 2009-09-14 Alzheimer's cognitive enabler
ES09815029.5T ES2528029T3 (es) 2008-09-19 2009-09-14 Habilitador cognitivo para la enfermedad de Alzheimer
CA2737183A CA2737183C (en) 2008-09-19 2009-09-14 Alzheimer's cognitive enabler
CN2009801357066A CN102149319B (zh) 2008-09-19 2009-09-14 阿尔茨海默氏症认知使能器
JP2011527893A JP5643207B2 (ja) 2008-09-19 2009-09-14 ユーザが精神的に衰弱した状態にあるときにユーザの対話を可能にするコンピューティングデバイス、コンピューティングシステム及び方法
TW098131679A TWI520714B (zh) 2008-09-19 2009-09-18 阿茲海默症之認知致能器
US13/966,686 US20140180159A1 (en) 2008-09-19 2013-08-14 Alzheimer's cognitive enabler
US14/724,982 US10521666B2 (en) 2008-09-19 2015-05-29 Computing device for enhancing communications
US16/720,951 US11301680B2 (en) 2008-09-19 2019-12-19 Computing device for enhancing communications
US17/692,515 US20220198798A1 (en) 2008-09-19 2022-03-11 Computing device for enhancing communications

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
US12/233,817 US20100076334A1 (en) 2008-09-19 2008-09-19 Alzheimer's cognitive enabler

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US13/966,686 Continuation US20140180159A1 (en) 2008-09-19 2013-08-14 Alzheimer's cognitive enabler

Publications (1)

Publication Number Publication Date
US20100076334A1 true US20100076334A1 (en) 2010-03-25

Family

ID=42038374

Family Applications (5)

Application Number Title Priority Date Filing Date
US12/233,817 Abandoned US20100076334A1 (en) 2008-09-19 2008-09-19 Alzheimer's cognitive enabler
US13/966,686 Abandoned US20140180159A1 (en) 2008-09-19 2013-08-14 Alzheimer's cognitive enabler
US14/724,982 Active 2029-12-06 US10521666B2 (en) 2008-09-19 2015-05-29 Computing device for enhancing communications
US16/720,951 Active 2028-10-31 US11301680B2 (en) 2008-09-19 2019-12-19 Computing device for enhancing communications
US17/692,515 Pending US20220198798A1 (en) 2008-09-19 2022-03-11 Computing device for enhancing communications

Family Applications After (4)

Application Number Title Priority Date Filing Date
US13/966,686 Abandoned US20140180159A1 (en) 2008-09-19 2013-08-14 Alzheimer's cognitive enabler
US14/724,982 Active 2029-12-06 US10521666B2 (en) 2008-09-19 2015-05-29 Computing device for enhancing communications
US16/720,951 Active 2028-10-31 US11301680B2 (en) 2008-09-19 2019-12-19 Computing device for enhancing communications
US17/692,515 Pending US20220198798A1 (en) 2008-09-19 2022-03-11 Computing device for enhancing communications

Country Status (9)

Country Link
US (5) US20100076334A1 (es)
EP (1) EP2344031B1 (es)
JP (1) JP5643207B2 (es)
KR (1) KR101520524B1 (es)
CN (1) CN102149319B (es)
CA (1) CA2737183C (es)
ES (1) ES2528029T3 (es)
TW (1) TWI520714B (es)
WO (1) WO2010033461A2 (es)

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110157221A1 (en) * 2009-12-29 2011-06-30 Ptucha Raymond W Camera and display system interactivity
US20190216383A1 (en) * 2016-06-29 2019-07-18 Robert Polkowski Cognitive support system for a sufferer of cognitive dysfunction and method for operating the same
TWI684160B (zh) * 2017-07-31 2020-02-01 陳兆煒 分析提示系統及方法
EP2713881B1 (en) * 2011-06-01 2020-10-07 Koninklijke Philips N.V. Method and system for assisting patients
US11273283B2 (en) 2017-12-31 2022-03-15 Neuroenhancement Lab, LLC Method and apparatus for neuroenhancement to enhance emotional response
US11341583B2 (en) * 2015-10-02 2022-05-24 Not So Forgetful, LLC Apparatus and system for providing reminders and recommendations, storing personal information, memory assistance and facilitating related purchases through an interconnected social network
US11341962B2 (en) 2010-05-13 2022-05-24 Poltorak Technologies Llc Electronic personal interactive device
US11364361B2 (en) 2018-04-20 2022-06-21 Neuroenhancement Lab, LLC System and method for inducing sleep by transplanting mental states
US11452839B2 (en) 2018-09-14 2022-09-27 Neuroenhancement Lab, LLC System and method of improving sleep
US11717686B2 (en) 2017-12-04 2023-08-08 Neuroenhancement Lab, LLC Method and apparatus for neuroenhancement to facilitate learning and performance
US11723579B2 (en) 2017-09-19 2023-08-15 Neuroenhancement Lab, LLC Method and apparatus for neuroenhancement
US11786694B2 (en) 2019-05-24 2023-10-17 NeuroLight, Inc. Device, method, and app for facilitating sleep

Families Citing this family (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWI559904B (en) * 2014-05-22 2016-12-01 Nat Univ Chin Yi Technology Brainwave control integrated system for wheelchair and message sending
EP3192058A4 (en) * 2014-09-08 2018-05-02 Simx LLC Augmented reality simulator for professional and educational training
US9864431B2 (en) 2016-05-11 2018-01-09 Microsoft Technology Licensing, Llc Changing an application state using neurological data
US10203751B2 (en) 2016-05-11 2019-02-12 Microsoft Technology Licensing, Llc Continuous motion controls operable using neurological data
CN107137079B (zh) * 2017-06-28 2020-12-08 京东方科技集团股份有限公司 基于脑信号控制设备的方法、其控制设备及人机交互系统
JP7135886B2 (ja) * 2019-01-24 2022-09-13 トヨタ自動車株式会社 促し発話装置、促し発話方法及びプログラム
CN111358428A (zh) * 2020-01-20 2020-07-03 书丸子(北京)科技有限公司 一种观察能力测试评定方法和装置
CN111467641B (zh) * 2020-05-27 2022-02-22 浙江莱恩海思医疗科技有限公司 一种声光复合疗法实施装置
CN111569270B (zh) * 2020-05-27 2022-03-15 浙江莱恩海思医疗科技有限公司 一种复合光照疗法实施装置
US11567574B2 (en) 2020-09-22 2023-01-31 Optum Technology, Inc. Guided interaction with a query assistant software using brainwave data
US11955028B1 (en) 2022-02-28 2024-04-09 United Services Automobile Association (Usaa) Presenting transformed environmental information

Citations (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6011991A (en) * 1998-12-07 2000-01-04 Technology Patents, Llc Communication system and method including brain wave analysis and/or use of brain activity
US6309361B1 (en) * 1998-05-04 2001-10-30 Kirtley E. Thornton Method for improving memory by identifying and using QEEG parameters correlated to specific cognitive functioning
US6434419B1 (en) * 2000-06-26 2002-08-13 Sam Technology, Inc. Neurocognitive ability EEG measurement method and system
US6463321B2 (en) * 1999-08-10 2002-10-08 Thuris Corporation Method and computer program product for assessing neurological conditions and treatments using evoked response potentials
US6466232B1 (en) * 1998-12-18 2002-10-15 Tangis Corporation Method and system for controlling presentation of information to a user based on the user's condition
US20020188217A1 (en) * 2001-06-07 2002-12-12 Lawrence Farwell Method and apparatus for brain fingerprinting, measurement, assessment and analysis of brain function
US6513046B1 (en) * 1999-12-15 2003-01-28 Tangis Corporation Storing and recalling information to augment human memories
US6527715B2 (en) * 1998-10-30 2003-03-04 The United States Of America As Represented By The Secretary Of The Army System and method for predicting human cognitive performance using data from an actigraph
US6553252B2 (en) * 1998-10-30 2003-04-22 The United States Of America As Represented By The Secretary Of The Army Method and system for predicting human cognitive performance
US6622036B1 (en) * 2000-02-09 2003-09-16 Cns Response Method for classifying and treating physiologic brain imbalances using quantitative EEG
US6842877B2 (en) * 1998-12-18 2005-01-11 Tangis Corporation Contextual responses based on automated learning techniques
US20050228785A1 (en) * 2004-04-02 2005-10-13 Eastman Kodak Company Method of diagnosing and managing memory impairment using images
US20060008785A1 (en) * 2004-07-09 2006-01-12 William Clark Method of and system for interacting with cognitively impaired individuals
US20060009978A1 (en) * 2004-07-02 2006-01-12 The Regents Of The University Of Colorado Methods and systems for synthesis of accurate visible speech via transformation of motion capture data
US6996261B2 (en) * 2001-01-30 2006-02-07 Decharms R Christopher Methods for physiological monitoring, training, exercise and regulation
US7080322B2 (en) * 1998-12-18 2006-07-18 Tangis Corporation Thematic response to a computer user's context, such as by a wearable personal computer
US20070299360A1 (en) * 2006-06-21 2007-12-27 Lexicor Medical Technology, Llc Systems and Methods for Analyzing and Assessing Dementia and Dementia-Type Disorders
US20080138783A1 (en) * 2006-12-06 2008-06-12 Microsoft Corporation Memory training via visual journal

Family Cites Families (29)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5377258A (en) * 1993-08-30 1994-12-27 National Medical Research Council Method and apparatus for an automated and interactive behavioral guidance system
JP2593625B2 (ja) 1994-01-12 1997-03-26 株式会社脳機能研究所 生体情報自動識別装置
US6542081B2 (en) * 1996-08-19 2003-04-01 William C. Torch System and method for monitoring eye movement
US6494719B1 (en) * 1999-10-20 2002-12-17 Brent E. Logan Method and system for reproducing a progressive or regressive pattern of sonic variations
US7136695B2 (en) 2001-10-12 2006-11-14 Pless Benjamin D Patient-specific template development for neurological event detection
US6878111B2 (en) * 2002-07-09 2005-04-12 Cardiac Pacemakers, Inc. System for measuring subjective well being
JP4285012B2 (ja) * 2003-01-31 2009-06-24 株式会社日立製作所 学習状況判断プログラム及びユーザ状況判断システム
US20040210159A1 (en) * 2003-04-15 2004-10-21 Osman Kibar Determining a psychological state of a subject
JP4269827B2 (ja) 2003-07-02 2009-05-27 財団法人くまもとテクノ産業財団 画像刺激−脳波意思伝達方法
DE112004002948T5 (de) * 2003-08-21 2007-08-02 SSPT Pty Ltd., Blackburn Eignungstest
US8190248B2 (en) 2003-10-16 2012-05-29 Louisiana Tech University Foundation, Inc. Medical devices for the detection, prevention and/or treatment of neurological disorders, and methods related thereto
US20050163302A1 (en) * 2004-01-22 2005-07-28 Mock Von A. Customer service system and method using physiological data
US20060093997A1 (en) * 2004-06-12 2006-05-04 Neurotone, Inc. Aural rehabilitation system and a method of using the same
EP2260760B1 (en) * 2004-06-18 2014-08-27 Neuronetrix Solutions, LLC Evoked response testing method for neurological disorders
US20070106127A1 (en) * 2005-10-11 2007-05-10 Alman Brian M Automated patient monitoring and counseling system
JP2008059385A (ja) 2006-08-31 2008-03-13 Toshiba Corp 情報処理装置、情報処理方法、プログラム、及び情報処理装置の制御方法
US8564544B2 (en) * 2006-09-06 2013-10-22 Apple Inc. Touch screen device, method, and graphical user interface for customizing display of content category icons
WO2008059878A1 (fr) 2006-11-15 2008-05-22 Panasonic Corporation Dispositif d'ajustement pour un procédé d'identification d'ondes cérébrales, procédé d'ajustement et programme informatique
CA2673644C (en) * 2006-12-27 2016-02-09 Case Western Reserve University Situated simulation for training, education, and therapy
US7761414B2 (en) * 2007-01-07 2010-07-20 Apple Inc. Asynchronous data synchronization amongst devices
US20080208015A1 (en) * 2007-02-09 2008-08-28 Morris Margaret E System, apparatus and method for real-time health feedback on a mobile device based on physiological, contextual and self-monitored indicators of mental and physical health states
US20090119154A1 (en) * 2007-11-07 2009-05-07 Searete Llc, A Limited Liability Corporation Of The State Of Delaware Determining a demographic characteristic based on computational user-health testing of a user interaction with advertiser-specified content
WO2009090671A2 (en) * 2007-12-27 2009-07-23 Setu Parikh System and method to stimulate human genius
US9149599B2 (en) * 2008-04-09 2015-10-06 Lotus Magnus, Llc Brain stimulation systems and methods
US8666501B2 (en) * 2008-07-02 2014-03-04 Microtransponder, Inc. Methods, systems, and devices for treating tinnitus with VNS pairing
US20100009324A1 (en) * 2008-07-14 2010-01-14 E. Keith Owens Method and device for post clinical treatment of dependency relapses
MY168264A (en) * 2008-07-15 2018-10-16 Dtt holdings pty ltd Method for preparing a patent for a medical treatment
US8441356B1 (en) * 2009-02-16 2013-05-14 Handhold Adaptive, LLC Methods for remote assistance of disabled persons
US9943698B2 (en) * 2014-04-22 2018-04-17 Lockheed Martin Corporation Cognitive enhancement using feedback

Patent Citations (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6309361B1 (en) * 1998-05-04 2001-10-30 Kirtley E. Thornton Method for improving memory by identifying and using QEEG parameters correlated to specific cognitive functioning
US6743167B2 (en) * 1998-10-30 2004-06-01 The United States Of America As Represented By The Secretary Of The Army Method and system for predicting human cognitive performance using data from an actigraph
US6553252B2 (en) * 1998-10-30 2003-04-22 The United States Of America As Represented By The Secretary Of The Army Method and system for predicting human cognitive performance
US6527715B2 (en) * 1998-10-30 2003-03-04 The United States Of America As Represented By The Secretary Of The Army System and method for predicting human cognitive performance using data from an actigraph
US6011991A (en) * 1998-12-07 2000-01-04 Technology Patents, Llc Communication system and method including brain wave analysis and/or use of brain activity
US6842877B2 (en) * 1998-12-18 2005-01-11 Tangis Corporation Contextual responses based on automated learning techniques
US6466232B1 (en) * 1998-12-18 2002-10-15 Tangis Corporation Method and system for controlling presentation of information to a user based on the user's condition
US7137069B2 (en) * 1998-12-18 2006-11-14 Tangis Corporation Thematic response to a computer user's context, such as by a wearable personal computer
US7080322B2 (en) * 1998-12-18 2006-07-18 Tangis Corporation Thematic response to a computer user's context, such as by a wearable personal computer
US6463321B2 (en) * 1999-08-10 2002-10-08 Thuris Corporation Method and computer program product for assessing neurological conditions and treatments using evoked response potentials
US6513046B1 (en) * 1999-12-15 2003-01-28 Tangis Corporation Storing and recalling information to augment human memories
US6549915B2 (en) * 1999-12-15 2003-04-15 Tangis Corporation Storing and recalling information to augment human memories
US7155456B2 (en) * 1999-12-15 2006-12-26 Tangis Corporation Storing and recalling information to augment human memories
US6622036B1 (en) * 2000-02-09 2003-09-16 Cns Response Method for classifying and treating physiologic brain imbalances using quantitative EEG
US6434419B1 (en) * 2000-06-26 2002-08-13 Sam Technology, Inc. Neurocognitive ability EEG measurement method and system
US6996261B2 (en) * 2001-01-30 2006-02-07 Decharms R Christopher Methods for physiological monitoring, training, exercise and regulation
US20020188217A1 (en) * 2001-06-07 2002-12-12 Lawrence Farwell Method and apparatus for brain fingerprinting, measurement, assessment and analysis of brain function
US20050228785A1 (en) * 2004-04-02 2005-10-13 Eastman Kodak Company Method of diagnosing and managing memory impairment using images
US20060009978A1 (en) * 2004-07-02 2006-01-12 The Regents Of The University Of Colorado Methods and systems for synthesis of accurate visible speech via transformation of motion capture data
US20060008785A1 (en) * 2004-07-09 2006-01-12 William Clark Method of and system for interacting with cognitively impaired individuals
US20070299360A1 (en) * 2006-06-21 2007-12-27 Lexicor Medical Technology, Llc Systems and Methods for Analyzing and Assessing Dementia and Dementia-Type Disorders
US20080138783A1 (en) * 2006-12-06 2008-06-12 Microsoft Corporation Memory training via visual journal

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110157221A1 (en) * 2009-12-29 2011-06-30 Ptucha Raymond W Camera and display system interactivity
US9319640B2 (en) * 2009-12-29 2016-04-19 Kodak Alaris Inc. Camera and display system interactivity
US11367435B2 (en) 2010-05-13 2022-06-21 Poltorak Technologies Llc Electronic personal interactive device
US11341962B2 (en) 2010-05-13 2022-05-24 Poltorak Technologies Llc Electronic personal interactive device
EP2713881B1 (en) * 2011-06-01 2020-10-07 Koninklijke Philips N.V. Method and system for assisting patients
US11341583B2 (en) * 2015-10-02 2022-05-24 Not So Forgetful, LLC Apparatus and system for providing reminders and recommendations, storing personal information, memory assistance and facilitating related purchases through an interconnected social network
US20190216383A1 (en) * 2016-06-29 2019-07-18 Robert Polkowski Cognitive support system for a sufferer of cognitive dysfunction and method for operating the same
TWI684160B (zh) * 2017-07-31 2020-02-01 陳兆煒 分析提示系統及方法
US11723579B2 (en) 2017-09-19 2023-08-15 Neuroenhancement Lab, LLC Method and apparatus for neuroenhancement
US11717686B2 (en) 2017-12-04 2023-08-08 Neuroenhancement Lab, LLC Method and apparatus for neuroenhancement to facilitate learning and performance
US11273283B2 (en) 2017-12-31 2022-03-15 Neuroenhancement Lab, LLC Method and apparatus for neuroenhancement to enhance emotional response
US11318277B2 (en) 2017-12-31 2022-05-03 Neuroenhancement Lab, LLC Method and apparatus for neuroenhancement to enhance emotional response
US11478603B2 (en) 2017-12-31 2022-10-25 Neuroenhancement Lab, LLC Method and apparatus for neuroenhancement to enhance emotional response
US11364361B2 (en) 2018-04-20 2022-06-21 Neuroenhancement Lab, LLC System and method for inducing sleep by transplanting mental states
US11452839B2 (en) 2018-09-14 2022-09-27 Neuroenhancement Lab, LLC System and method of improving sleep
US11786694B2 (en) 2019-05-24 2023-10-17 NeuroLight, Inc. Device, method, and app for facilitating sleep

Also Published As

Publication number Publication date
CN102149319B (zh) 2013-07-17
US20200364458A1 (en) 2020-11-19
US20140180159A1 (en) 2014-06-26
CA2737183C (en) 2022-05-17
TWI520714B (zh) 2016-02-11
JP5643207B2 (ja) 2014-12-17
WO2010033461A3 (en) 2010-06-10
EP2344031A2 (en) 2011-07-20
US10521666B2 (en) 2019-12-31
KR101520524B1 (ko) 2015-05-14
CN102149319A (zh) 2011-08-10
US11301680B2 (en) 2022-04-12
JP2012502741A (ja) 2012-02-02
ES2528029T3 (es) 2015-02-03
CA2737183A1 (en) 2010-03-25
WO2010033461A2 (en) 2010-03-25
EP2344031A4 (en) 2012-11-21
US20220198798A1 (en) 2022-06-23
EP2344031B1 (en) 2014-10-22
TW201016191A (en) 2010-05-01
US20150262016A1 (en) 2015-09-17
KR20110070981A (ko) 2011-06-27

Similar Documents

Publication Publication Date Title
US11301680B2 (en) Computing device for enhancing communications
US11696714B2 (en) System and method for brain modelling
US20220110563A1 (en) Dynamic interaction system and method
US10874340B2 (en) Real time biometric recording, information analytics and monitoring systems for behavioral health management
US11037545B2 (en) Interactive personal assistive devices and systems with artificial intelligence, and related methods
US9747902B2 (en) Method and system for assisting patients
JP2019084249A (ja) 認知症診断装置、認知症診断方法、及び認知症診断プログラム
US10504379B2 (en) System and method for generating an adaptive embodied conversational agent configured to provide interactive virtual coaching to a subject
US20160117940A1 (en) Method, system, and apparatus for treating a communication disorder
US11751813B2 (en) System, method and computer program product for detecting a mobile phone user's risky medical condition
JP6851871B2 (ja) 意思創発装置、意思創発方法および意思創発プログラム
WO2011116340A2 (en) Context-management framework for telemedicine
JP7390268B2 (ja) 認知機能予測装置、認知機能予測方法、プログラム及びシステム
WO2020097412A1 (en) Speech analysis devices and methods for identifying migraine attacks
US20240008766A1 (en) System, method and computer program product for processing a mobile phone user's condition
US20230012989A1 (en) Systems and methods for rapid neurological assessment of clinical trial patients
WO2024038439A1 (en) System and method for evaluating a cognitive and physiological status of a subject
JP2024003313A (ja) 情報処理装置、情報処理方法及びプログラム
WO2023184039A1 (en) Method, system, and medium for measuring, calibrating and training psychological absorption
CN117615699A (zh) 用于监测改变意识的治疗物质的疗程的系统和方法
CN112489797A (zh) 一种陪护方法、装置及终端设备

Legal Events

Date Code Title Description
AS Assignment

Owner name: UNITHER NEUROSCIENCES, INC.,MARYLAND

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:ROTHBLATT, MARTINE;REEL/FRAME:021806/0832

Effective date: 20080919

STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION

AS Assignment

Owner name: UTASIA INC., MARYLAND

Free format text: CHANGE OF NAME;ASSIGNOR:UNITHER NEUROSCIENCES, INC.;REEL/FRAME:063399/0557

Effective date: 20121203