DE202019103671U1 - Portable brain function monitor - Google Patents

Abstract

Portable and portable brain function monitoring device having a headband and a muscle loop in which a plurality of graphene and / or photonic sensors are embedded in fabric or stainless steel for detecting at least changes in the amplitude and frequency of brain waves (electroencephalogram ( EEG)) and circulation before seizures, the device being set up to warn of impending seizures.

Description

This is a low cost, environmentally friendly and non-invasive medical invention designed to detect and monitor brain function and cerebral blood flow. It is both portable and portable.

In this embodiment of the invention, photonic sensors and graphene sensors placed on the scalp allow the detection and description of brain currents and blood flow associated with ailments.

In addition, this invention is supported by the detection of muscle contractions, blood oxygen levels, cardiac and respiratory rates using graphene sensors.

Photonic and graphene sensors in a ring worn by an individual measure muscle movements, blood oxygen levels, cardiac and respiratory rates. Such a device detects the effect of abnormal brain activity, such as seizures or stroke.

Such an embodiment allows multimedia recording of the impact of abnormal brain activity on the wearer, thereby providing visual evidence of an event, such as a stroke or seizure. Graphene sensors, when placed on either side of the forehead, detect changes in the brainwaves associated with drowsiness and trigger an audible vibrating alarm and a visual record.

Medical background:

There are about one hundred billion neurons. They communicate with each other by generating electricity on the order of microvolts. The electroencephalogram (EEG) is a record of it in a curve, but first they need to be amplified. The resulting record has a particular diagnostic pattern. An EEG is used as an aid to a good history in the diagnosis and follow-up of people with epilepsy. It has other uses, such as monitoring brain tumors or strokes, suffering from a brain tumor, and diagnosing brain dead.

In the conventional method for recording in EEG departments, usually about twenty or more electrodes are adhered to the patient's scalp. They are arranged in an internationally applied pattern from the forehead to the back of the head. Such a recording is corrupted by wave patterns caused by noise and body movement. The resulting record is evaluated by an experienced neurophysiologist trained in the EEG technique.

Dr. Carton, a British physician in Liverpool, discovered in 1875 using an animal galvanometer that the brain produces electrical signals.

In 1929, Dr. Hans Berger, a German physician, a record of human brain waves, the electroencephalogram (EEG), referring to Caton's research. Adrian and Mathews from Cambridge in the United Kingdom (UK) have confirmed Berger's work.

Among the neurological diseases affecting the brain, epilepsy is the most common. Seizures are the result of epilepsy, affecting 600,000 people in the UK, 5 million in Europe, 2.6 million in the US and 50 million worldwide. A seizure causes a sudden burst of electrical activity, which can lead to disturbances of consciousness, in some to muscle contractions, what is described as tonic-clonic movements, or grand-times-severe epileptic seizures. In the UK alone, approximately 600 people die from epilepsy. In a form of epilepsy called Absence Epilepsy or Petit Mal, disturbances of consciousness occur that last only a few seconds and are therefore often not recognized. It occurs more often in children. Changes in blood flow, to the extent that brain cells are depleted of oxygen, are triggered by a variety of ailments. In severe conditions, such as status epilepticus, persistent seizures may cause brain damage due to reduced blood flow causing brain damage.

Cerebrovascular diseases, such as stroke, are the leading cause of death worldwide after coronary heart disease. WHO estimates that there are over 5 million deaths from cerebrovascular accidents, such as stroke, which is defined as a local or generalized disorder of brain function over 24 hours or more, with no apparent cause other than cerebral vascular origin causing death ,

Hemorrhage in the brain can cause damage to the affected areas, and such bleeding, when spread, destroys the structure and function of adjacent areas of the brain. Subarachnoid hemorrhage is a hemorrhage in the meninges. Intraventricular hemorrhage, which occurs in the cavity between the two halves of the brain, is particularly common Preterm infants. Transient ischemic attacks (TIA) are a milder form and may precede a stroke. Recognition is important because it provides the opportunity to prevent a stroke.

Graphene sensors and photonic sensors are the two types of sensors used in this invention. While graphene sensors are good for detecting functions, photonic sensors are better for detecting blood circulation.

Concerning photonics (Phos Greek for light), the French physicist Becquerel becomes the first photovoltaic cell 1839 attributed. Maxwell from Scotland describes light as an electromagnetic field in "A Dynamic Theory of the Electromagnetic Field". In the energy spectrum, photons are in the middle, with radio waves and microwaves at the bottom and X-rays and gamma rays at the top of the radiation. Photon has found wide application in medicine, such as in lasers.

Graphene is a carbon material that is thin, strong and a very good conductor of electricity. It was discovered at the University of Manchester by Professor Andre Geim and Professor Kostaya Novoselov. They were awarded the 2004 Nobel Prize for their invention. It was chosen for its resistance and conductivity for use in this embodiment. Stroke and epilepsy are two common conditions that affect the brain. Circulatory changes in the brain are difficult to diagnose in the early stages of a disease. Severe epilepsy can damage blood vessels and damage brain areas.

State of the art

Viglione et al. In 1975 described a seizure warning system using a pattern recognition technique based on fast Fourier transform (FFT). Cohen et al describe spectral analysis and the construction of four baseband and detection techniques during surgical procedures. Terry Thomas Jones describes detection methods using existing handheld software from Texas Instruments and Toshiba. Chenna Kesavalu Rajagopal, the author of this invention, has described a wearable but attached brain alert device. The Dracup et al invention, a prediction and detection system, includes a motion detector and accelerometer. The method described by Litt and colleagues regarding signals obtained from an implanted system uses a predetermined process of identifying a vector to predict and detect seizures. Leyde et al describe an implanted device in their patent. Frei and Osario adapt a closed loop feedback control device to detect disturbances in the monitoring of neurological signals. It is a device for eliminating poor quality signals.

The Kramer et al invention analyzes the use of motion sensor systems, generic motion models, and accelerometers. The Echauz et al prediction and detection system is based on an implant. Warwick and colleagues describe a simplified EEG system that has a headgear to monitor and report that an epileptiform activity threshold has been reached without a readable display. Eschauz et al describe a closed-loop reaction system that involves a complete or partial system. The Kramer et al invention is an epilepsy warning system with a detection and analysis system and a motion detector. The Warwick and Team invention integrates a base unit with a simplified EEG system with electrodes in its onset alarm system.

The dry-sensor EEG / EMG (electromyography) and motion detection system invented by Luo and Team detects seizures using GPS, motion detection using accelerometer technology. Glasses are used to attach the seizure detection unit in addition to the electrode placement. Use in a form of epilepsy called photosensitive epilepsy, in which seizures are caused by bright light, is described. The EMG is used to measure electrical currents generated during muscle contraction. The present invention described herein does not use motion detection or electromyography, but amplitude based detection of whole muscle contraction using photonics or graphene sensors. The seizure monitoring system of Kidmose et al is designed for seizures resulting from hypoglycemia and uses an implanted device and a low blood glucose warning system called hypoglycemia.

The Picard et al washable portable biosensor is based on integrated photoplethysmography and detection of skin conductance and motion detection technology. The use of photonics or graphene sensors to detect blood flow, muscle contractions in larger or smaller hand muscles to detect tonic-clonic seizures is not found in the prior art.

Description of the technology of the invention:

The present invention relates to a device, in particular a portable and portable device comprising a headband and a muscle loop having a plurality of graphene and photonic sensors embedded in fabric or stainless steel. Such sensors could also be embedded in a pillow to allow monitoring in a person's sleeping position.

The choice of sensors, graphs, photonics, number and placement of such sensors may vary according to the patient and the clinical conditions.

As an example, two graphene sensors can be placed around the head of patients with epilepsy; Two graphene sensors on the forehead can be used to monitor wakefulness.

In one embodiment, one or two photonic sensors may be used to monitor solely the blood flow to the brain.

In a preferred embodiment, a graphene and a photonic sensor are placed in contact with muscles in the upper and lower arms, including wrists and fingers, thighs, leg or ankle, to monitor muscle contractions, heart rate, respiratory rate and blood oxygen content. This allows monitoring of a form of epilepsy known as grand mal seizures and a form of stroke in which muscle weakness (transient ischemic attack TIA) or paralysis may precede the stroke. A slow heart rate and respiratory arrest (apnea) can lead to death. In one embodiment, the cushion is lined with sensors. Such graphene and photonic sensors around the head, pillow, and other body regions are connected to hardware via Bluetooth or other wireless means, with Artificial Intelligence (AI) software, hereafter referred to as KI, capable of controlling the brainwaves (EEG) and blood flow to the brain. It is programmed to recognize patterns associated with suffering. The resulting measure will be determined by the nature of the condition identified by the AI.

Graphene and photonic sensors are more efficient in making contact with the skin and are more comfortable for patients. They can be embedded in textile or stainless steel mesh headbands. Such materials are inexpensive and can be recycled. Smallest voltages of an electric current transmitted to the sensors are amplified, noise and other disturbances are filtered. This invention has a logic module included in the hardware that is positioned on the headband, the pillow, and other body portions, such as the limbs.

1. a) Detektieren eines Vor-Anfall-Musters; die KI in dem System in dem Logikmodul erkennt intuitiv das Wellenmuster, das Anfällen vorherging, und sammelte diese in einer Wissensbasis. Es ist eine solche eingebaute Wissensbasis der Erkennung eines EEG-Musters eines Patienten, die das hörbare, vibrierende und visuelle Aufzeichnen in Erwartung von Anfällen auslöst;
2. b) Detektieren von Anfällen, wenn voreingestellte Parameter von Amplitude und Frequenz länger als fünf Sekunden gegenwärtig sind;
3. c) Zusammenfügen von Informationen von den photonischen- und Graphen-Sensoren, die auf dem Kopf, an Muskeln um die Arme, das Handgelenk, die Finger, die Beine und die Fußgelenke platziert sind.

The amplified signals that are transmitted undergo further amplification through a series of preamplifiers, amplifiers and filtering using double bandstop filters to remove artifacts. Artifacts are signals that are different from the signals that are caused by brain activity, such as movement, ambient noise, or when an electrode has been removed. The signals are then processed in hardware, with the AI reading the brain waves (EEG) and blood flow to the brain to detect the following:

1. a) detecting a pre-seizure pattern; the AI in the system in the logic module intuitively recognizes the wave pattern that preceded seizures and collected them in a knowledge base. It is such a built-in knowledge base of recognizing a patient's EEG pattern that triggers audible, vibratory and visual recording in anticipation of seizures;
2. b) detecting seizures when preset parameters of amplitude and frequency are present for more than five seconds;
3. c) Merging information from the photonic and graphene sensors placed on the head, muscles around the arms, wrist, fingers, legs and ankles.

It allows timely prediction and detection of seizures, vascular disabilities, such as obstruction caused by thrombosis, brain hemorrhage, brain hemorrhage, ventricular bleeding, subarachnoid space, or narrowing of blood vessels, causing transient ischemia. All of these changes in blood flow together or individually can result in death if left untreated.

Seizures may be treated or prevented by standard emergency procedures, such as drops of medicine that can be placed in the patient's mouth.

The power supply for the hardware in the headband, the pillow and the loop around the muscles on the limbs is provided by means of rechargeable batteries. It may be connected to a telephone, a handheld device such as a smartphone, a caregiver who can perform treatment, or a computer using radio frequencies or Bluetooth with the information stored for subsequent analysis. Recorded data, multimedia data such as audiovisual data may be transmitted by wireless transmission to a medical facility or a medical emergency response service.

This alert allows for treatment as agreed between the patient and the doctor to stop seizures. It allows the person to go to a safe place and / or perform self-medication as agreed with the doctor.

This embodiment is capable of triggering a multimedia device in the handset or a computer. The EEG recordings and visual appearance during seizures are recorded in a handheld device, such as a smartphone. Such a combination of visual appearance and EEG record provides clear evidence of seizures. An individual's multimedia video recording during seizures and simultaneous EEG recording at this time is considered "the benchmark" (gold standard) in the diagnosis of epilepsy in addition to classifying the nature of epilepsy.

Such a multi-media record of a stroke or similar condition, or TIA, with concomitant changes in blood flow allows the AI to accurately describe such events to aid the physician.

A significant extension of this embodiment described above is configured to operate alone or with the scalp electrodes comprising photonic sensors in a system attached to the musculature. Such sensors may be embedded in textile or stainless steel frames. Such a photonic sensor measures the amplitude of abnormal muscle contractions followed by relaxation during tonic-clonic seizures or grand mal seizures. Another sensor measures heart rate and respiratory rate. It can be attached to the upper arm, forearm, upper leg of an adult, or the thigh of an infant or young child and communicates with the AI in the logic module connected to this embodiment of the device ( 4 and 5 ). In one embodiment, a ring equipped with photonic sensors and carried by the individual measures oxygen content, heart rate, and respiratory rate. It detects muscle weakness in transient ischemia (TIA) or contractions in tonic-clonic seizures, providing independent confirmation of the signals detected by the sensors placed on muscle. The AI is able to validate such information during the merge. Such a logic module is equipped with a rechargeable battery and capable of detecting muscle contractions causing a sudden collective increase in amplitude, and communicating with the logic module on the head or directly with another device via radio frequency, Bluetooth or wireless. Such another device may be a telephone, computer, handset with a multimedia device, such as a video or audio alarm unit, or the logic module communicating with a caregiver, medical facility, or emergency service. Such communication can be via Bluetooth or wireless.

The device detects the peak and wave pattern of three cycles per second present in absentee seizures, also called petit mal epilepsy. Such early detection would allow clinicians to treat promptly, thereby preventing loss of education and self-esteem. Children are most affected by this type of epilepsy. The device serves as a diagnostic tool when the diagnosis of epilepsy is ambiguous and longer observation is needed to confirm or reject the diagnosis of epilepsy.

In a rare but distressing condition called West Syndrome (infantile spasms), EEG and video would be crucial in early diagnosis and treatment.

Although it is an adjunct to scalp sensors, it can be useful as a separate unit when diagnosed using scalp electrodes and video recording.

Pre-amplification of signals to reduce noise levels:

A strategic arrangement of preamplifiers, amplifiers, comparator module, double band-stop filter and flip-flop provides detection of changes in amplitude, frequency and clinical functions, such as heart rate, respiration and muscle contractions, during seizure activity and produces an audible or visual alarm. Such an arrangement provides a graphics interface for storage in Android or smartphones, cloud arrangements or forwarding to a caregiver and / or medical services.

The DC / DC converter completely isolates the patient from the mains, even when the individual is connected to the mains during monitoring for seizures. The hardware is equipped with a rechargeable battery.

ANGLE AND HITCH ALLOWANCES:

The artificial intelligence AI in the logic module is able to warn against the onset and onset of a seizure or onset of a stroke, triggering an audible, vibrating and / or visual alarm and multimedia video recording.

1. a. wenn die tonisch-klonische Muskelaktivität detektiert wird;
2. b. wenn die Herzfrequenz weniger als 60 Schläge pro Minute ist;
3. c. wenn die Atemfrequenz weniger als 20 pro Minute ist;
4. d. Wenn eine Reduktion der Blutoxygenierung vorliegt, die von den photonischen Sensoren, die in dem Ring platziert sind, gemessen wird. Die KI in dem Modul ist dazu eingerichtet, altersbedingte Sauerstoffgehalte zu detektieren.
5. e. Sie ist dazu ausgelegt, Vorrang vor anderen Parametern, wie zum Beispiel Amplitude und Frequenz oder Durchblutung, von den Kopfhautsensoren und Muskelsensoren zu haben, wenn die vitalen Funktionen, wie niedrige Herzfrequenz (Bradykardie) und/oder gesenkte Atemfrequenz wie bei Apnoe und niedriger Blutsauerstoffgehalt (Hypoxämie), von den Sensoren in den Fingern detektiert werden.

The effects of abnormal brain activity or blood flow in the muscle and vital functions such as breathing, heart rate and tissue oxygenation are analyzed by the AI in the logic modules in addition to changes in amplitude, frequency of brain waves, blood flow in the cerebral vessels. The AI in the logic module is programmed to trigger on the following states:

1. a. when the tonic-clonic muscle activity is detected;
2. b. when the heart rate is less than 60 beats per minute;
3. c. if the respiratory rate is less than 20 per minute;
4. d. When there is a reduction in blood oxygenation measured by the photonic sensors placed in the ring. The AI in the module is designed to detect age-related oxygen levels.
5. e. It is designed to take precedence over other parameters, such as amplitude and frequency or perfusion, from the scalp sensors and muscle sensors when the vital functions, such as low heart rate (bradycardia) and / or decreased respiratory rate, as in apnea and low blood oxygen content ( Hypoxemia), are detected by the sensors in the fingers.

Two dry electrodes placed on either side of the forehead detect the onset of sleep or drowsiness ( 1 ). When predetermined parameters are reached, an audible and visual alarm is triggered by the AI to alert the driver, pilot, operator or other persons carrying this device ( 2 ). By warning the driver, pilot or operator of the onset of drowsiness, this embodiment prevents accidents and loss of life, the driver and others. It also records such events for proof of the event.

SHORT VERSION

The present invention describes the detection of changes in the brain currents before and during seizures. During seizures, there is a sudden increase in amplitude and frequency. The addition of a mechanism to detect the effect of such an increase in brain activity on the muscle, heart rate and respiratory rate provides a monitoring mechanism for epilepsy.

Epilepsy is a common disease characterized by changes in state of consciousness and brainwaves. It is not a single suffering. In a form known as Petit Mal, there is a brief loss of consciousness that is barely perceptible. Another type of epilepsy, tonic-clonic or grand-mal seizures, results in increased tonicity or contracture and muscle relaxation.

Using dry electrodes placed in different places on a person, this device receives information about wave patterns that characterize various forms of epilepsy, such as tonic-clonic and petit mal, before and during seizures.

In addition, placement of electrodes on the forehead detects the slowing of brain waves during drowsiness or early sleep.

The technology of the embodiment consists of dry sensors contained in inexpensive materials to detect brain waves, muscle contractions, cardiac and respiratory rates. Such enhanced brain waves are further enhanced, filtered and characterized by artifacts. These signals are transmitted via Bluetooth, WiFi or radio frequency to be analyzed in the connected hardware, and the resulting information is transmitted to a caregiver, a medical service and an emergency service for further action. Audible and visual alarm systems are added to the warning system of the invention. In addition, video recording provides further evidence of seizures.

list of figures

• 1 and 2 show a front view and a side view of a portable device according to the invention, which is arranged on the head of a person;
• 3 shows a flowchart of a functional layout of the portable device;
• 4 shows a schematic view from behind a calf of a person who wears a muscle loop;
• 5 illustrates a child wearing a device according to the invention on the thigh area.

Detailed description of the invention:

1 and 2 show a front view and a side view of a portable and portable device 1 according to the invention, on one head 2 a person is arranged. The device 1 has a headband 3 in which a plurality of graphene sensors and / or photonic sensors 4 embedded in fabric or stainless steel, for detecting changes in the amplitude and frequency of brain waves (electroencephalogram (EEG)) and blood flow from seizures, the device being adapted to warn of impending seizures. A sensor 4 in the headband 3 is embedded, is temporally arranged, the other sensor 4 is arranged parietal. Such graphene sensors and / or photonic sensors 4 around the head 2 , on a cushion and / or other body regions are connected by Bluetooth or wireless means to an external computing device having at least a processor, a controller and a communication device. An appropriate hardware module 5 can be part of the device 1 his. The computing device processes an AI (artificial intelligence) software that is capable of detecting the brain waves (EEG) and blood flow of the brain coming from the device 1 by means of the sensors 4 be recorded and transmitted, analyzed.

3 shows a flowchart of a functional layout, such as the portable and portable device 1 and the Kl (artificial intelligence) software information provided by sensors 4 and / or sensors 8th be collected, processed. The flowchart shows on the left side the detection function of at least one sensor 8th to muscle weakness, paralysis and / or muscle contraction through the muscle module MM to detect. Corresponding data provided by the sensors 8th are detected by a muscle logic module MLM processed. When predetermined parameters are reached, an audible and / or visual alarm is issued by the muscle logic module MLM triggered. In the center, the flow chart shows electrical signals representing cerebral blood flow from the graphene sensors and / or photonic sensors 4 . 8th be detected by a brain module BM are processed.

The flow chart shows graphene sensors and photonic sensors 4 . 8th Showing the function and blood flow in the brain through the brain module BM Detect and transfer such data with those of muscles through the muscle module MM be obtained, connect. The artificial intelligence (AI) in the control logic of both the muscle logic module MLM as well as a brain logic module BLM allows several actions, for example to generate an audible and / or visual alarm. The brain and muscle modules BM . MM are set up to work together or independently. The alarm function of the logic modules MLM and BLM also allows informing institutions and / or triggering multimedia recording as shown on the right side of the flowchart.

Regarding 4 is a schematic view of a calf 10 a person from behind who has a muscle loop 6 wears, shown. The muscle loop 6 has a band 9 in which a variety of graphene and / or photonic sensors 4 . 8th embedded in fabric or stainless steel. In addition, there is a hardware module 7 that has the muscle logic module, part of the muscle loop 6 , The muscle loop 6 is between the gastrocnemius muscle 11 and the Achilles tendon 12 the calf 10 arranged. By means of photonic sensors 8th Muscle contractions, heart rate, respiratory rate, and blood oxygen levels can be monitored.

5 Illustrates a kid holding a device 1 according to the invention in the thigh area 13 wearing.

List prior art:

1. 1. Epileptic Seizure Warning System: Viglione, Sam S. et al: US 3,863,625 ,
2. 2. Real Time EEG Spectral Analyzer: Cohen, Daniel E. et al: EP 85300427.3 ,
3. 3. Portable Epileptic Attack Warning and Recording Device: Terry Thomas Jones: GB 2335046.
4. 4. Brain Monitor: Chenna Kesavalu Rajagopal: GB 2336211.
5. 5. Method for Prediction, Detection, Monitoring, Analysis and Alerting of Seizures: Dracup, Jeffrey Albert: US 200130060167.
6. 6. Method and Apparatus for Predicting the Onset of Seizures Based on Signals from Indicative Activity: Litt, Brian et al: US 6658287 ,
7. 7. Methods and Systems for Measuring a Subject's Susceptibility to a Seizure: Leyde, Kent W et al: US 2008/0183097 ,
8. 8. Signal Quality Monitoring and Control for a Medical Device System: Free Mark G. et al: US 7146211 ,
9. 9. Device and Method for Detecting Epileptic Event: Kramer, Uri et al .: US8109891.
10. 10. Dry Sensor EEG / EMG and Seismic Detection and Monitoring: Luo et al: US 2012/0197092.
11. 11. Unified Probabilistic Framework for Predicting and Detecting Seizure Onsets in the Brain and Multitherapeutic Devices: Echauz, Javier Ramon et al: US 2008/0021342.
12. 12. Abnormal Motion Detector and Monitor: Nathan et al: US 2015/0190085.

LIST OF REFERENCE NUMBERS

1

device

2

head

3

headband

4

sensor

5

hardware module

6

muscle loop

7

hardware module

8th

sensor

9

tape

10

calf

11

Gastrocnemius muscle

12

Achilles tendon

13

leg

BM

brain module

MM

muscle module

BLM

Brain logic module

MLM

Muscle logic module

QUOTES INCLUDE IN THE DESCRIPTION

This list of the documents listed by the applicant has been generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Cited patent literature

• US 3863625 [0051]
• US 6658287 [0051]
• US 2008/0183097 [0051]
• US 7146211 [0051]

Cited non-patent literature

• Cohen, Daniel E. et al: EP 85300427.3 [0051]

Claims (26)

A portable and portable brain function monitoring device having a headband and a muscle loop in which a plurality of graphene and / or photonic sensors are embedded in fabric or stainless steel for detecting at least changes in the amplitude and frequency of brain waves (electroencephalogram ( EEG)) and circulation before seizures, the device being set up to warn of impending seizures. Device after Claim 1 , characterized in that the device comprises a memory unit for recording the previous amplitude and frequency pattern. Device after Claim 1 or 2 , characterized in that the device is adapted to learn such information by means of artificial intelligence stored in a hardware module of the device. Device after Claim 2 , characterized in that the device is adapted to create individualized warnings by means of artificial intelligence. Device according to one of Claims 1 to 4 , characterized in that the device comprises means for alerting the person, the caregiver or the responsible adult and affiliated organizations or emergency services at the onset of seizures. Device according to one of Claims 1 to 5 , characterized in that the apparatus is adapted to detect peak and wave patterns of three cycles per second occurring in absentee seizures, also called petit mal epilepsy. Device according to one of Claims 1 to 6 characterized in that the device comprises a video recording device, wherein the video recording of the event provides visual evidence to the person, the caregiver or the responsible adult and affiliated organizations or emergency services and / or clinicians. Device according to one of Claims 1 to 7 , characterized in that the device is arranged to serve as a diagnostic tool when the diagnosis of epilepsy is ambiguous and a longer observation is needed to confirm or discard the diagnosis of epilepsy. Device after Claim 7 or 8th , characterized in that the combination of EEG and video recording supports the history for those undergoing treatment. Device according to one of Claims 1 to 9 , characterized in that the device is adapted to detect the onset of seizures and changes in heart rate, respiration and muscle activity and blood oxygen content by means of at least one graphene and photonic sensor. Device after one Claim 1 to 10 , characterized in that the device is adapted to detect the occurrence of rhythmic muscle contractions followed by relaxation in addition to respiratory and heart rate. Device after Claim 1 to 11 , characterized in that the device is adapted to allow on the basis of circulatory changes that are detectable by means of the device, the diagnosis of a stroke. Device according to one of Claims 1 to 12 Characterized in that the device is adapted to perform the monitoring of neonates with risk for intraventricular hemorrhage by the detection of changes in the amount of blood flow rate and the oxygen content in the brain, which would allow a pediatrician applying preventive measures. Device according to one of Claims 1 to 13 , characterized in that the device is adapted to detect the brief loss of perfusion and, together with muscle monitoring, to permit the prediction and early detection of mild stroke and transient ischemic attack (TIA). Device after Claim 14 , characterized in that the muscle monitoring together with the electroencephalogram (EEG) and the means for detecting circulatory changes provide valuable information about the extent and severity of a stroke. Device according to one of Claims 1 to 15 , characterized in that the portable device is adapted to allow the monitoring of blood flow and brain function in patients undergoing brain and vital surgery. Device according to one of Claims 1 to 16 characterized in that, due to the mobile nature of such device and the display of vital signals, such as cerebral blood flow, function and oxygen content, useful for monitoring intensive care patients on standard wards, in clinics and outpatient clinics. Device according to one of Claims 1 to 17 characterized in that the portable device is adapted to be used for monitoring those affected by a mild stroke at home or early discharge from those with epilepsy, stroke or other cerebral events. Device after Claim 1 to eighteen characterized in that the device is set up by detecting the EEG pattern obtained from the electrodes placed on the forehead at the onset of drowsiness, alerting drivers, operators and pilots at the onset of sleep. Device after Claim 19 characterized in that the apparatus is arranged to receive further supporting information by a camera that is placeable in front of the individual to detect rapid eye movement associated with drowsiness. Device according to one of Claims 1 to 20 , characterized in that the device with scalp electrodes and / or muscle components alone is useful in the follow-up of those with seizures and stroke. Device according to one of Claims 1 to 21 , characterized in that the device comprises a cardiac and respiratory monitor, wherein cardiac and respiratory rate monitoring is indispensable for prompt intervention in the form of medical treatment of stroke and prevention of further damage to the brain and death from stroke. Device after Claim 1 to 22 characterized in that the device comprises graphene and photonic sensors in fabric or stainless steel embedded in a pad to allow monitoring of brain flow and blood flow to the brain in the sleeping position of a person. Device after Claim 23 characterized in that the detection of muscle contraction by photonic or graphene sensors allows this device to use it independently of the headband or pad component. Device after Claim 1 to 24 characterized in that the photonic and graphene-enabled sensor ring component of the device is adapted to detect deoxygenation, slow pulse, slowed respiratory rate and muscle contraction or weakness in the fingers during seizures or stroke and to be used independently or as part of the overall device , Device after Claim 1 to 24 , characterized in that the device is useful in research on blood flow and brain function in those affected by types of dementia.

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