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Technological Innovations in Neurology 2 - Sanjoy Sanyal
 

Technological Innovations in Neurology 2 - Sanjoy Sanyal

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Latest techno-gadgets in Neurological illnesses- Deep Brain Stimulation, DBS, Bionic Eye, Limb Prosthesis ...

Latest techno-gadgets in Neurological illnesses- Deep Brain Stimulation, DBS, Bionic Eye, Limb Prosthesis

Tags: argus, bci, bionic arm, bionic eys, brain computer interface, brainport, chronic traumatic encephalopathy, cte, lokomat, magnetoencephalography, meg, neuralynx, neuro-feedback, neuroheadset detection suites, neuroswitch, orthosis, sensors, smarthand, speech synthesizer, virtual reality

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  • ECoG- electrocorticography

Technological Innovations in Neurology 2 - Sanjoy Sanyal Technological Innovations in Neurology 2 - Sanjoy Sanyal Presentation Transcript

  • Technological innovations in Neurology – 2 Dr Sanjoy Sanyal sanyal.sanjoy8@gmail.com Professor – Neuroscience An outline of techno-gadgets used / tried / tested / in Neurological disorders Med 3 Neuroscience students from Summer 2009 to Summer 2010 semesters of Medical University of Americas (MUA), Nevis, St. Kitts-Nevis, W.I., contributed partly to the material for this presentation September 2010
  • • Magnetoencephalography (MEG) in Epilepsy (Slides 3 – 16) • Brain computer interface (BCI) (Slides 17 – 27) • Neuroswitch in Locked-in (Slides 28 – 29) • Speech synthesizer – Neuralynx (Slide 30) • Lokomat orthosis in Cerebral palsy (31 – 38) • Virtual reality in paralysis (Slide 39) • Brainport in bilateral vestibular damage and blindness (Slides 40 – 52) • Bionic eye – Argus II in Retinitis pigmentosa (Slides 53 – 56) • Bionic arm – SmartHand (Slides 57 – 61) • Neuro-feedback sensors and Neuro-headset detection suites in video gaming (Slides 62 – 66) • Helmet force sensors in CTE (Slides 67 – 69) Contents
  • MEG A SQUID (Super- conducting Quantum Interference Device) is a very sensitive magneto- meter used to measure extremely weak magnetic fields, based on supercon- ducting loops containing Josephson junctions
  • • MEG helmet has an array of SQUID sensors and super- conducting lead shell, which are cooled by liquid helium • Each SQUID sensor contains a pickup coil of superconducting wire that receives brain magnetic fields • It is magnetically coupled to the SQUID, which produces a voltage proportional to magn- etic field received by the coil • A computer program converts the SQUID data into maps of the currents flowing through- out brain as function of time MEG helmet
  • • The colored contours show how the magnetic field produced by neural brain currents (dashed arrows) changes intensity and polarity over the skull‟s surface • In the red region, the field is most intense in a direction pointing out of the skull •In the blue region, the field is most intense in a direction pointing into the skull (R-hand rule) SQUID sensor
  • SQUID • A SQUID is 10 to 100 micrometers • Feedback coil in the SQUID magnetically couples it to the pickup coil in the SQUID sensor • Magnetic field lines pass through square hole in SQUID‟s center
  • • This determine the phases of electron waves circulating in the SQUID‟s superconducting region (green region in previous slide) • The electron waves‟ interference is proportional to magnetic flux over the SQUID‟s square hole • Superconductors have no electrical resistance; the interference can only be measured by interrupting the superconductor with small regions that have electrical resistance, the 2 Josephson junctions, so that voltage drops will develop across them • Voltage measured across the junctions is proportional to the magnetic flux over the SQUID‟s square hole Superconducting Quantum Interface Device (SQUID)
  • Magneto- encephalo- graphy (MEG)
  • • MEG is used for identifying and analyzing brain activity based on magnetic fields produced by it • Principle: MEG is sensitive to the magnetic fields generated by intra-neuronal currents generated in the brain (Slide 8); Resultant magnetic field contours in brain are captured by SQUID sensors (Slide 6) in MEG helmet (Slides 4,8), which are rendered in the form of computer-generated image • Applications: – Demonstrate functional activity of brain regions (next slide) – Localize seizure focus (Slide 14) – Demonstrate functioning of Orthosis system through Brain-computer interface (Slide 19) Magnetoencephalography (MEG)
  • MEG – functional areas Showing face-arm area of superolateral cortex and leg area on medial cortex
  • • MEG is used for localizing the epileptic focus during pre-surgical evaluation of patients with medically intractable epilepsy • MEG is non-invasive and is complementary to EEG • The following case study demonstrates the role of MEG in a 22-year old female with refractory epilepsy that did not respond to drugs • She had undergone a number of investigations to try to delineate the epileptic focus; MRI; interictal and ictal scalp EEGs; FDG-PET; MEG; Wada Test • MRI showed no anatomical abnormality (Slide 13) MEG in epilepsy
  • • Inter-ictal scalp EEG showed continuous right temporal spikes • Ictal scalp EEG showed attenuation of the inter- ictal spike activity but did not show a localized onset area • Fluoro-DeoxyGlucose (FDG)-PET scan indicated right temporal hypo-metabolism • MEG, conducted after seeing a normal MRI and abnormal EEG / PET scan showed a hyperintense signal localized in right insular region (Slide 14) • MEG finding was used for identification of the epileptic zone which enabled surgical removal and seizure-free status MEG in epilepsy
  • Coronal T2 MRI showing no abnormality in right temporal region
  • CoronalMEG–Seizurefocusinrightinsula
  • • The localisation accuracy of MEG was comparable to that of invasive intracranial recording • MEG was found to be more sensitive than scalp EEG in neocortical epilepsy • MEG also showed a high degree of concordance (87%) with the Wada test in another study • MEG is an advance in the non-invasive pre- surgical evaluation of epilepsy, and although is in use for several decades, has only recently been used for analysis of the entire head • A MEG-guided review of MRI may reveal subtle abnormalities and permit a precise surgical excision of the irritative epileptic focus that would not have been picked up by MRI alone MEG in epilepsy
  • • Application of MEG in MRI-negative non-lesional cases provides additional information needed for decision-making before surgery can be attempted • The rate of +ve findings after MEG-guided review of previously MRI-negative films is ~ 17.5% • Because MEG is primarily sensitive to magnetic fields generated by intracellular currents, it limits inaccurate readings from outside sources • Drawbacks: Major costs associated with operating it as well as its limited availability Poon TL, Cheung FC and Lui CH. Magnetoencephalography and its role in evaluation for epilepsy surgery. HKMJ. 2010 February [cited 2010 March 29]; 16(1):44-47[4 pages]. Available from: http://www.hkmj.org/article_pdfs/hkm1002p44.pdf MEG in epilepsy
  • Brain computer interface (BCI) For commu- nication (mute, quadriplegic) (this slide); or for limb movement (amputee, paralytic) (next slide)
  • Braincomputerinterface
  • Brain computer interface (BCI)
  • Brain computer interface (BCI) In right cortical stroke, intact left Pre-motor (motor planning) cortex sends impulses via BCI to left External effector, which in turn activates either a Robotic hand or sends FES to paralyzed muscle
  • • BCI is gateway between brain and external device • Brain signals can be translated to commands to control this device (External effector), reflecting the intentions of the user (Slide 20) • Previous primate studies demonstrated that motor cortex neurons can predict the direction and speed of arm movements • Recent human studies translated these findings to increased levels of brain-derived control • Because there is a lesion in the brain, BCI cannot use normal cortical pathways to interact with environment; it creates a completely new output pathway for the brain; e.g., quadriplegic controlling cursor on screen with signals derived from Pre- motor cortex (Slides 17, 19) Brain computer interface (BCI)
  • There are 4 functional components of BCI: 1. Signal acquisition: Information input from Pre- motor cortex is recorded into the BCI • Measurement of brain activity is usually via electrodes, either invasive or non invasive • Signal acquisition can be EEG-based, ECoG- based, „Single unit‟ microelectrode-based 2. Signal processing: Conversion of raw informa- tion into useful device command; Requires complex array of analyses (Slide 19); • Assessment of frequency power spectra • Event-related potentials • Cross correlation coefficients for EEG analysis • These are to determine the relationship between an electro- physiological event and a given cognitive or motor task BCI
  • 3. Device output: The control function produced by the BCI system • Moving cursor on screen • Choosing letters for communication • Controlling a robotic arm or bowel / bladder sphincters 4. Operating protocol: The manner in which the user controls how the system functions • Turning the system on and off • Switching between prosthetic limbs BCI
  • • Based on source from which the brain signal is obtained (Signal acquisition) 1. EEG-based: Electrical activity from the scalp 2. Single unit-based: Microelectrodes in brain parenchyma that detect action potential of individual neurons 3. ECoG-based: Electrodes from cortical surface directly (above or below dura) BCI Platforms
  • • EEG-based: Most common technique – Detects only Mu (8-12 Hz), Beta (18-25 Hz) wave-forms (rhythms), which are produced by sensorimotor cortex and thalamo-cortical circuits – Pros: Convenient, safe, and inexpensive – Cons: Poor spatial resolution; No specific information about details such as position or velocity of hand movements • Single unit-based: Micro-electrodes penetrate into brain parenchyma – Very successful in recording electrical activity for limited time periods – Pros: High spatial / temporal resolution – Cons: Highly invasive, can cause neural and vascular damage, chances of infections BCI platforms
  • • ECoG-based: More practical and robust platform for clinical applications – Signal is 5 times larger than EEG signal – Higher spatial resolution, and detects higher frequency waveforms (rhythms) – Lower frequencies, known as Mu (8-12 Hz) and Beta (18-25 Hz), detectable by EEG, are produced by thalamo-cortical circuits – Higher frequencies appreciable only with ECoG, a.k.a. Gamma band activity, show close correlation with action potential of neurons of Primary motor cortex; Also associated with numerous aspects of speech BCI platforms
  • • BCI is really helpful in motor-disabled patients – Spinal cord injuries – Peripheral neuromuscular dysfunction • However, BCI is limited in patients suffering from hemiparesis from hemispheric stroke or traumatic brain injury • The field of neuroprosthetics is growing rapidly • It can be further expanded to language function and plasticity BCI future
  • NeuroSwitch – Locked-in syndrome
  • NeuroSwitch – Locked-in syndrome
  • Speechsynthesizer
  • • Cerebral palsy: Damage to Precentral gyrus (PrCG) of the developing brain up to 3 years of age; Results in motor palsy in developing children • Motor disorders are often accompanied by secondary musculoskeletal problems, and disturbances of sensation, perception, cognition, communication, behavior, and epilepsy • Lokomat gait orthosis: Developed by Swiss scientists at University Hospital of Zurich in January 2006 • It is a virtual gate training therapy for children with neurological gate impairments like CP, which incorporates sensory and external motor stimuli Cerebral palsy (CP)
  • Lokomat – Cerebral palsy Koenig, Wellner, Koneke, Meyer-Heim, Lunenburger, and Riener. "Virtual gait training for children with cerebral palsy using the Lokomat gait orthosis." National Center for Biotechnology Information. PubMed.gov, U.S. National Library of Medicine National Institutes of Health, 2008. Web. 21 Nov. 2009. http://www.ncbi.nlm.nih.gov/pubmed/18391287 .
  • Lokomat – Cerebral palsy
  • Lokomat – Cerebral palsy Meyer-Heim, Andreas. "Robotic-assisted locomotor training in gait rehabilitation of children." Research Portal. Stud Health Technol Inform, Jan. 2006. Web. 21 Nov. 2009. http://www.researchportal.ch/unizh/p9021.htm . "Robot-Assisted Walking Therapy Using the Lokomat." Rehabilitation Institute of Chicago. 25 Sept. 2009. Web. 21 Nov. 2009. http://www.ric.org/conditions/pcs- specialized/lokomat/index.aspx
  • • Patient is placed in harnesses over the treadmill part of the machine and connected to all the sensory receptors (1st 2 Lokomat slides) • 4 different virtual scenarios are played on the screen in front of patient (3rd Lokomat slide) – Wading through water -Playing soccer – Overstepping obstacles -Walking in traffic • Virtual projection mimics everyday situations that allow a sense of reality to the patient (next slide) • The variation of position control allows the use of different muscles. Levels of difficulty can be varied by changing the resistance and force exerted Lokomat – Cerebral palsy
  • • Data is collected for each patient to record their progress in terms of Gait distance, Gait speed, Produced force, Body weight, Time of effective training • A surface Electromyography (sEMG) is used to record muscle potentials by placing electrodes on skin surface (next slide) • The repetition of task specific training through the different scenarios allows the brain and the spinal cord to re-route signals that were previously interrupted. It helps in strengthening muscles Lokomat – Cerebral palsy
  • Lokomat – sEMG recording Differences in the amplitude represent various levels of effort
  • Paralyzedmantakinga walkinvirtualreality
  • • Brainport system provides electrotactile stimulation for sensory augmentation which uses encoded electric current to represent actual sensory information that is deficient • By sending this current to the skin, the brain adapts to interpret the sensory information as if it were coming from the original organ • This is because sensory information is carried by nerve fibers in the form of impulse patterns that are then interpreted by their respective brain centers • Brainport works via an Electrode array that receives input from a non-tactile source, which then applies controlled currents to the skin in a precise pattern at a precise location Brainport
  • • Tongue: Research done with the Brainport technology found that the tongue is an ideal skin surface; its nerve fibers are closer to the surface, it lacks a stratum corneum, has more nerve fibers • Additionally, less voltage is required on the tongue because the saliva acts as a natural conducting material. Brainport • Finally, in the sensory homunculus, the area of the cortex that interprets tongue sensations is much larger than other areas of the body
  • • The initial application of the Brainport device was in the field of balance correction • Trial patients had damage to their inner ears, due to Bilateral vestibular disorders (BVD), Acoustic neuromas, or Meniere‟s disease, and had resultant loss of balance • In the absence of a functional vestibular system, the brain has difficulty correctly integrating visual and proprioceptive cues, leading to problems with posture control and movement • They have difficulty in engaging in daily activities; walking in low-light or busy environments, walking on uneven surfaces, bending forward to pick something up, driving a car, or reading a book Vestibular dysfunction
  • Brainport–vestibular
  • • These patients adopted correctional mechanisms on their own; gripping sides of the wall, guarded stance, slow, shuffling steps, which offer minimal compensation • Brainport aided them to interpret their balance information (proproceptive cues) as coming from their tongue instead of inner ear. • Brainport integrates an Accelerometer with output device, which provides input to the Facial and Lingual nerves via the anterior 2/3rd of tongue • The Accelerometer measures tilt with respect to pull of gravity. It is on underside of 10 x 10 Electrode array, and transmits data about head position to CPU through communication circuitry Brainport – vestibular use
  • • When the head tilts right, the CPU receives the „right‟ data and sends a signal telling the Electrode array to provide current to the right side of tongue. When the head tilts left, the device buzzes the left side of tongue. When the head is level, Brainport sends a pulse to the middle of tongue • Wicab, manufacturer of Brainport, used the device on 28 subjects suffering from BVD • Subjects were told the accelerometer would detect their head position and relay that information to the electrode array on their tongue; Stimulation would cause a tingling that feels like “bubbles” on their tongue Brainport – vestibular use
  • • Their goal during training was to keep the signal in the center of the array by responding to the direction of signal on the tongue, and to use the feedback to maintain posture with Brainport device • All subjects regained sense of balance for variable periods, > 6 hours for every 20 minute session • After multiple sessions with the device, the subject's brain starts to interpret the signals as indicating head position (balance information that normally comes from the inner ear) instead of just tactile information from the tongue Brainport – vestibular use
  • Brainport – visual use
  • • Wicab adapted the technology to produce tactile vision via a camera to capture visual data • Optical information picked up by the Camera is converted by CPU into binary code • Each set of pixels in camera‟s sensor corresponds to an electrode in the array
  • • These signals represent differences in pixel data such as frequency, amplitude and duration. When fully converted, the image takes the form of variations in pulse current, voltage, duration, and intervals between each pulse • Electrode array receives the resulting signal via the stimulation circuitry and applies it to the tongue • Wicab trained 15 subjects; Training sessions included several brief trials of 1-5 minutes each, followed by one 20-minute trial involving the patient in progressively challenging positions while using the device • Scientists evaluated the subjects before training began and after the last training session; In all improvement occurred in at least one area Brainport – visual use
  • • Users described it as pictures drawn on their tongue with champagne bubbles. With training users may perceive shape, size, location and motion of objects in their environment • The brain eventually learns to interpret and use the information coming from the tongue as if it were coming from the eyes • Results were confirmed with an independent study that conducted PET scans of congenitally blind people while they were using the Brainport device Brainport – visual use
  • Original Image Brainport Image Brainport – visual use • With the current array of 100 to 600+ electrodes, subjects can recognize high-contrast objects, their location, movement, and some aspects of perspective and depth
  • • Blind subjects can perceive looming, depth, perspective, size and shape. They could still feel the pulses on their tongue, but they could also perceive images generated from those pulses by their brain • Subjects perceived the objects as "out there" in front of them, separate from their own bodies. They perceived and identified letters of alphabet • Currently, the Brainport is intended to augment rather than replace the white cane Brainport – visual use
  • Retinitis pigmentosa (RP) Hereditary (Autosomal dominant / recessive); Rods predominantly destroyed; Leads to progressive annular (ring) scotoma („Tunnel vision‟) and Nyctalopia („Night blindness‟) Retinitis P is ideal test-bed for Bionic eye
  • Bionic eye: Camera: included in spectacles; Receives light; Sends impulses to Computer Retinal implant: Tacked to retina; Has microelectrode array which stimulates surviving retinal receptors
  • Bioniceye
  • • Retinal prosthesis: Restores partial vision to those who are blind, and allows those who are blind to see flashes of light • Argus II 60 Electrode Epiretinal System includes Spectacles, small video camera, tiny computer, and 60 electrodes (previous 2 slides) • Video camera: Picks up images • Computer: Takes the input from camera and relays output to electrodes • Microelectrode array (retinal implant): 60 independent electrodes tacked to retina; Stimulation current of each electrode is determined by the brightness at the corresponding area; stimulates surviving retinal receptors Bionic eye – Argus II
  • Bionic arm – TMR Targeted muscle re-innervation: After amputation, Musculocutaneous, Median, Radial nerves are re-routed to innervate clavicular and sternocostal heads of pectoralis major. EMG electrodes from these muscles transmit impulses to Microprocessor controller, which activates a Robotic arm
  • • The first commercially available bionic hand became available in 2007 by Touch Bionics™ • Targeted muscle reinnervation (TMR): Surgeons move the ends of the nerves to the chest, which earlier connected to the arm (previous slide) • Electrodes on a harness detect EMG signals from those muscles and transmit them to a miniature Computer (microprocessor controller) • The computer translates these into signals that control small electric motors in the Robotic arm and hand (previous slide) • When patient wants to pick up an apple from the kitchen table, he/she thinks it and their arm, hand and fingers do it (next slide) Bionic arm
  • Bionic arm
  • Bionic arm – Smart Hand®
  • • The main limitation of previous models was the deficit in sensory function • New models now convey sensation from the device to neural receptors in the chest (and to the brain) to allow sensation of Feeling, Touch, Pressure, Vibration • SmartHand®: Smart bio-adaptive hand prosthesis; this „intelligent‟ hand mimics movement of a real human hand and gives the wearer a true sensation of feeling and touch. Four electric motors and 40 sensors are linked to the brain and activated when a SmartHand touches an object • When patient grabs something hard, he feels it in the „fingertips‟, which he doesn't have anymore • Robin Ekenstam of Sweden was the project's 1st human wearer (previous slide) Bionic arm – SmartHand®
  • Neuro- feedback sensors Some believe that playing video games with neuro- feedback provides therapy for children with Brain injuries, ADHD and Learning disabilities Neuro-feedback enables a form of conditioning that rewards people for producing specific brain waves
  • • The Emotiv Game Developer SDK consists of a neuro- headset and toolkit, which incorporates a unique set of detection suites • Detection suites can be used alone or combined for a more spectacular game play experience (For video gamers, employing AI to enhance gaming experience in virtual reality) Neuro-headset detection suites
  • • Affectiv suite monitors player‟s emotional states / state of mind in real-time • It provides extra dimension in game interaction by allowing the game to respond to a player's emotions • Characters can transform in response to player's feeling • Music, scene lighting and effects can be tailored to heighten the experience for the player in real-time • Affectiv suite can be used to adjust difficulty to suit each situation Affectiv™ suite
  • • Expressiv suite uses the signals measured by the neuro-headset to interpret player‟s facial expressions in real-time • When a player smiles, their avatar can mimic the expression even before they are aware of their own feelings • It provides a natural enhancement to game interaction by allowing game characters to come to life • Artificial intelligence (AI) can now respond to players naturally, in ways only humans have been able to until now Expressiv™ suite
  • • Cognitiv suite reads and interprets a player's conscious thoughts and intent • Gamers can manipulate virtual objects using only the power of their thought • The fantasy of magic and supernatural power can be experienced Cognitiv™ suite
  • Chronic traumatic encephalo- pathy (CTE) Pathological changes in brain of professional American football players and professional boxers, due to repeated trauma
  • Force sensors in helmet In order to determine the force that American footballers are subjected to, their helmets are now being fitted with force sensors (To obviate the problem of CTE)
  • Force sensors in helmet