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Foundations of DSPBasic Operations: convolutionDigital Filters: FIR and IIRSome Classification methodsBiosignal Libraries and Applications

Practical Demonstrations: Matlab and FiViewReview of Project exercisesFirmware - programming

Today:

Biofeedback: Principles and Applications

Brain Computer Interfaces – Theory and Methods

Sources and further reading:

Winfried Rief, Niels Birbaumer: Biofeedbacktherapie - Grundlagen, Indikation und praktisches Vorgehen, Schattauer, 2000, ISBN 3-7945-1968-X

Brendan Allison - Collected BCI material : http://www.cis.gsu.edu/brainlab/PapersOtherWritings.htm

Biofeedback:

● Transformation of physiological processes into visual, acoustic and / or sensual information

Biofeedbacktherapy:

● Concious regulation of vital processes by learning how to change the feedback values

http://www.hawbs.org/gallery/images/oxqoe_biofeedback.jpg

Potentials of Biofeedbacktherapy:

● Increased relaxation ● Increased self-awareness ● Increased expactation of self-efficiency ● Correction of malpositions ● Prevention of overreactions (physical as mental)

● Support for psycho- and/or physiotherapy ● Reduction of medication ● Reduction of side-effects ● Good (patients-) acceptability

http://www. Biofeedbacktherapie.info

Key-elements for a successful Biofeedback treatment:

● Expierienced therapist knowledge about psycho-physical processes and interrelations knowledge about correct measurement of vital parameters knowledge about problematic levels of vital parameters knowledge about problematic levels of vital parameters knowledge about desired levels of vital parameters ability to establish patient‘s trust and motivation

● Intregration into a holistic Therapy support of a conventional therapy ( medication / psychic treatment ) ● Intregration of achievements into everyday life

Vital Parameters that can be modified by Biofeedback-Training:

Muscle activity EMGHeart rate ECGBreathing patterns breathing beltBlood pressure PlethysmographyVessel constriction and dilationPeripheral blood flowPerspiratory gland activity (sweat) GSR / EDASkin- and body temperature Peripheral Body Temp.Brainwave activity EEG

Biofeedback for treatment of chronic back pain:

Problems:

● very frequent pain illness ● common malpositions: shortening of tonic muscles, degradation of phaseal muscles ● spinal disc deformation

● vicious circle: pain increases muscle tension ● condition to neutral stimuli

Biofeedback for treatment of chronic back pain:

Methods:

● EMG-Feedback

● scanning of relevant muscle groups

● left/ right comparison

● find relations of (psychophysical) cause and tension

● force- and stress tests, stress profiles

● repeated EMG-sessions for distension / relaxation

Biofeedback for tension headache / migraine

Problems:

● muscle tension in the head / neck / chin areas

● instability of blood vessel regulation, high sensitivity to stress excessive vaso-constriction, followed by dilation

● inflammation and excited pain receptors

Biofeedback for tension headache / migraine

Methods:

● EMG, EDA and body temperature feedback: relaxation techniques

● Peripheral blood flow / blood volume pressure feedback: training of vessel dynamics, vasoconstriction-training

● 60 % of the patients achieve a reduction of > 50% migraine attacks [BIR]

Biofeedback for anxiety disorders or psychosomatic syndromes

Problems:

● Somatic pain without any physical or pathological reason ● Hypochondric attention to normal changes or processes ● Drug addiction / addictive behaviour

Methods:

● Biofeedback to increase the self-efficiency hypothesis / awareness ● change the organic explanatory model into a psychophysical one ● accomplish stress (exposition-) tests with biofeedback monitoring ● relaxation training and systematic de-sensitization ● biofeedback as a support for psychic therapy

Biofeedback for Tinnitus

Problems:

● permanent handicap due to loud tones / noise ● loss of hearing / deception ● bruxism (tooth chrunching) ● sleep disorders / depression

Methods:

● EMG training of chin and neck muscles ● EDA and peripheral body temperature training: relaxation

Biofeedback for Problems of Incontinence

Problems:

● dysfunctional pelvic floor ● pelvic floor degeneration after birth / due to high age ● problems with urine and stool retention ● common handicap but big social problem

Biofeedback for Problems of Incontinence

Methods:

● training of detrusor activity using a pressure sensor in the bladder ● training of pelvic floor / sphincter muscles ( rectal/vaginal EMG – probes, ballon-catheter ) ● training of coordination of the abdominal muscle ( surface and rectal / vaginal EMG )

-> increase of contraction strength, -duration and coordination

Biofeedback for neural lesions

Problems:

● motor-disabilities after stroke or ischemic insult ● neural / muscle degeneration after accidents ● loss of control / muscle spasms

Methods:

EMG Biofeedback to support rehailitation training : ● bridge lost (physical) feedback mechanisms ● regain muscle control due to improvement of intrinsic perception and constant training (feedback gives motivation) ● active support: EMG triggered functional electro stimulation (FES)

Neurofeedback

● re-establish physiological distribution of brainwave frequencies in ADHD-patients (Attention deficit hyperactivity disorder) :

- increased Theta, decreased Beta - strong asymmetric distributions - strong frontal alpha waves

● treatment of sleep disorders, stroke, depression, tourette syndrome

● training of positivation of slow cortical potentials can lower epileptic seizures

● relaxation, meditation and peak performance training (Alpha / Theta – feedback )

Brain Computer Interfaces (BCIs)

Brain Computer Interfaces

● allow patients to control a computer by concious changes of brain activity

● provide a means of communication to completeley paralysed patients: amyotrophic lateral sclerosis (ALS), cerebral palsy, locked in syndrome

● can be used to control a cursor, select symbols, control external devices like orthesis / prothesis (depending on type of BCI)

● have a very low data rate, typical a few bit per second or less

● first results in the 1970ies (Vidal, visual evoked potentials, VEP-BCI)

Brain Computer Interfaces - Brain / Cortex Topography:

http://www.neuroskills.com/brain.shtmlSensomototic humunculus: (top) frontal lobe, gyrus precentralis

Brain Computer Interfaces - Brain / Cortex Topography:

Right and left brain map http://members.shaw.ca/hidden-talents/brain

Brain Computer Interfaces Principles of operation:

Brain Computer Interfaces – Major Types

● SCP Slow Cortical Potentials ● Mu Movement Imagination ● P300, SSVEP ERP-Analysis

● cortical neurons, direct brain interfaces

http://www.wired.com/news/images/full/thoughtlock1_f.jpgThe control informationis extracted from thereal time EEG-recording

Brain Computer Interfaces – SSVEP

● Steady State Visual Evoked Potentials derived from the visual (occipital) cortex

● focussing attention to visual stimuli of different frequency shows up in the EEG freqeuncy bands

● relibable and high transfer rate, but some prerequisites (eyes)

http://www.iua.upf.es/activitats/ semirec/semi-Reilly/

Brain Computer Interfaces – SCP BCIs

● detection of slow cortical potentials (SCPs)

● needs DC EEG Amplifiers (no highpass filter)

● first successful device end 1990‘s: Niels Birbaumers Thought translation device intensive training with necessary to gain control over the SCP waves

Patinet using TTD to write a letterhttp://www.heise.de/ct/06/18/088/bild1.jpg

SCPs:

DC-shifts, slow negativation of cortical areas

Preparation of movement and cognitive tasks,

Several hundert milliseconds before the task

Brain Computer Interfaces - μ-rhythm BCIs

● μ–rhythm is the idle-rhythm of the motor cortex

● frequencies around 10 and 18 Hz, location : gyrus praecentralis individual differences -> multichannel EEG (QEEG) for offline analysis

● ERD / ERS – event related desynchronisation / synchronisation movements or imagination of movements inhibit the μ–rhythm

Berlin-BCI, http://www.fraunhofer.de/ERD/ERS at around 10, 22 Hz

Brain Computer Interfaces - μ-rhythm BCIs

● two dimensional cursor control using different frequency bands for vertical horizontal movements (Wadsworth BCI)

● control of an orthesis, adaptive algorithm (Graz BCI)

Wadsworth BCI, 2 dimensional control Graz BCI, orthesisCSA of Mu-rhythms,http://www.robots.ox.ac.uk/

Brain Computer Interfaces - P300 BCIs

● P300 wave – posivite component in the event related potential, 300ms after a stimulus ● natural response to events considered as important

● selection of a symbol: count the flashes, algorithm averages trails and finds a P300

P300 runtime user interface

Brain Computer Interfaces - μ / P300 comparison

μ - BCIs P300 BCIs

Require training do not require training Work in realtime require averaging2d-control possible 1D control onlyContinous control discrete control

movement imagination concentration / decision affected by movement affected by distraction

Brain Computer Interfaces - direct brain interfaces

ECoG electrode grid photo by Gerwin Schalk (Wadsworth Center, Albany, USA), Kai Miller, Jeff Ojemann (University of Washington)

Components of a DBI system, P.R. Kennedy, R.A. Bakey, M.M. Moore, 1987, IEEE Trans Rehabil Eng. 8 (2):198-202

● Electrocorticogram: implanted electrode array● better signal quality , increased SNR radio transmission of signals● problems: decreasing signal quality, risk of infection, invasive technique

Brain Computer Interfaces - μ / P300 comparison

The first commercially available BCI system is actually an Austrian product:

● Mobile BCI using a pocket PC● Matlab-based software for host-PC operation● μ-BCI with training phase● Supports digital I/O-lines● Wireless transmission

http://www.gtec.at/content.htm

Brain Computer Interfaces - BCI2000

● Research Platform for BCI Systems● Written by Gerwin Schalk, Wadsworth Center, Albany (NY)● Modular structure: Signal Aquisition, Signal Processing and User Application communicatie via TCP/IP● Operator module used for configuration of the other modules● various user tasks availbale: 1D/2D cursor, Speller, P300, SCP ● free for academic use● driver for OpenEEG available

http://www.bci2000.org/

Brain Computer Interfaces - ten ways to improve BCIs:

● Better recording techniques ● Better understanding of EEG ● New brainwave parameters / hybrid BCI ● Customization of BCIs to each user ● Better pattern recognition ● Improved interfaces ● Better noise rejection ● Further testing with patients ● Studies on effects of training and long term use ● Improvements in computing and electronics

„BCI development is an interdisciplinary problem, involving neurobiology, psychology, engineering, methematics, computer

science and clinical rehabilitation“ Wolpaw et al, 2002