Rehabilitation of Post Cerebro-Vascular Accident Patients
With EEG and EMG Biofeedback.
Jean E. Horn
Cerebro-Vascular accident (more commonly known as stroke) is the third
leading cause of death in the United States, after heart disease and cancer.
Cerbro-vascular accident occurs when there is a blockage of blood vessels from
fatty deposits or blood clots. Another leading cause of CVA is uncontrolled
hypertension or high blood pressure. Of those patients who survive, about half
remain disabled and experience another stroke (DiMatteo, 1991). DiMatteo
(1991) quotes Krantz & Deckel (1983) as saying that CVA patients may suffer
paralysis, the inability to speak, and some may experience cognitive deficits
such as the inability to identify certain objects with words.
Patients who have suffered from cerbro-vascular accident may be treated
with EEG (Electroencephalographic) biofeedback. An electrode (sensor) is
placed on the patient's scalp where their brain waves can be read. There are
four types of brain waves: alpha, beta, theta, and delta. Alpha brain waves are
associated with an alert but relaxed state. Beta brain waves are associated
with concentration. Theta brain waves are associated with daydreaming.
Delta brain waves are associated with stages three and four of deep sleep. Levi
(1975) cites a study done by (Brown, 1970) which relates brain waves to
mood. In the experiment alpha, beta and theta were connected to three
colored lights. Participants were asked to describe their association to the
lights (Levi, 1975). Levi (1975) says that the results supported those findings
by Kamiya: alpha was a pleasant, tranquil, and a self-aware state. Theta was a
state that was full of daydreaming and memories. Beta could lead to a state of
anger, fearfulness, and tension. Von Bozzay (1980) says that none of the
brain waves are emitted alone, and patient's state of mind may make one
frequency more pronounced. According to Von Bozzay (1980) other
treatments with EEG are mental relaxation, concentration enhancement, and
attention enhancement. Concentration and attention difficulties require a
procedure of alpha training followed by alpha suppression (Von Bozzay,
1980). Patients can improve their concentration, memory and reading skills
through learning the differences between alpha and beta waves.
The treatment of head injuries and stroke has improved greatly in the last
3,000 years. Ancient Egyptians treated strokes and other head injuries with
the drilling of a hole in the skull, combined with ritual and prayer. The
Egyptians recognized that a blow to the right side of the head would affect the
left side of the body, while a blow to the left side of the head would affect the
right side of the body.
Today CVA patients who are treated with biofeedback are treated with
EMG (Electromyograph) for paralysis, as with the case study done by Schwartz
(1995). The EMG (Electromyograph) measures the amount of electrical
charge in the muscle, the individual realizes the electrical charge as a muscle
contraction.
Schwartz (1995) treated a 65-year-old woman with EMG biofeedback, who
had suffered from a ruptured aneurysm for one year before seeking help.
According to Schwartz (1995) the treatment goal was to promote independent
ambulation and to increase the function of her left arm. The treatment took
place twice a week for a total of four months, after the four months the patient
had improved functional control over her hand and left arm.
This case study shows how EMG biofeedback can be useful in the
rehabilitation of CVA patients. The patient was able to regain the use of her
left arm with EMG biofeedback in only four short months.
Unlike Schwartz (1995), the researchers in Berlin, Germany had studied the
treatment of CVA patients with mild paralysis of the arm with multi-modal
EEG. Platz, Kim, Engel, Kieselbach and Mauritz (2002) selected nine
inpatients, (who were all under the age of 80 years of age) from the
Department of Neurological Rehabilitation at the Free University, Berlin,
Germany. Platz et al (2002) selected their patients (for a three week training
program) with the following criteria: (1.) a first unilateral anterior circulation
ischemic stroke in the subacute phase from 3 weeks to six months post stroke.
(2.) mild to moderate central arm paresis (Motricity Index [6] with a arm score
of less than 100; shoulder abduction and elbow flexion muscle strength greater
than 3/5, thumb-index finger-opposition strength greater than 2/5 according to
Medical Research Council criteria [38]; selected finger movements and
precision grip preserved; no major somatosensory disturbance, i.e. no or only
slight reduction of sensation to light touch and no position sense deficit.
Before training, Platz et al (2002) measured the patient's movement-related
brain wave activity with the following data set: slow movement-related DC
potentials (DC), and event-related desynchronisation of rhythmic brain
activity both at frequencies, that was in the alpha (alpha-ERD) and beta band
(beta-ERD). Platz et al (2002) believed that these different analyses revealed
different spatiotemporal cerebral activation patterns related to movement and
might reflect different neural mechanisms related to motor control. Platz et al
(2002) gave the nine patients the TEMPA (which is an upper extremity
performance test for the elderly). The researchers believe that the TEMPA is
the best test that measures upper extremity performance with tasks that
represent daily living activities.
The researchers had the patients seated in a semi-reclining chair. The
researchers recorded the movement-related potentials using multi-channel EEG
equipment (SynAmps amplifier and Scan software by NeuroScan Inc., Sterling
VA, USA). The researchers prepared the skin using Abralyt LIGHT, which
resulted in impedance below 3kOhm for all recording sites. On the patient's
scalp they placed 27 AgAgCL sinter electrodes spaced according to a modified
international 10-20 System montage (FP1, FP2, F7, F3, FZ, F4, F8, FC5, FC1,
FC2, FC6, T3, C3, CZ, C4, T4, CP5, CP1, CP2, CP6, T5, P3, PZ, P4, T6, O1,
O2,) [12,14]. The researchers used a Vertical (VEOG) and horizontal
electroculogram (HEOG) which recorded separate recordings. Platz et al
(2002) say that their data was continuously registered with DC to 100 HZ
filtering and 500 HZ AD conversion rate with either A1 or A2 as reference
electrode (ipsilateral to moving hand). Platz et al (2002) report that
movement onset was marked off-line according to rectified surface EMG
recording of the extensor digitorum communis muscle. The researchers
recorded data sweeps generated for a period starting 5 seconds before
movement onset until 18 seconds after movement onset. Platz et al (2002)
results were, the nine CVA patients took longer on the TEMPA task than did
healthy individuals. The researchers found that the patients who were more
impaired at baseline had the greatest gains with the Arm Ability Training.
Platz et al (2002) report that the multi-modal EEG analysis of movement-
related electric brain activity was a powerful predictor of motor recovery for a
comparable patient group. They reported that patients who expressed alpha-
ERD at frontal and parieto-occiptal recording sites and patients who expressed
beta-ERD at temporoparietal recording sites showed less motor improvement
with training. Those patients who did not show activation (ERD) at these sites
according to Platz et al (2002) had the greatest gains in training.
This study showed that EEG biofeedback could be combined with EMG
biofeedback to help post CVA patients to recover motor control. The patients
could learn to alter or relearn the brain waves that are used for motor control
through the use of EEG biofeedback.
Rozelle and Budzynski (1995) have done a case study of a 55-year old male
CVA patient, who had no previous history of cerbro-vascular accident. Rozelle
and Budzynski (1995) did a medical examination of the patient and found
that the left posterior temporal/parietal infractions secondary to occlusion of
the left lentiform nucleus and genu of the right internal capsule. The
researchers reported that there was a 50% stenosis in the right internal carotid.
Rozelle and Budzynski (1995) reported the patient's symptoms as the
following: partial loss of control of his right arm, leg, and right eye, garbled
speech, short-term memory loss, fatigue weakness, impaired gait, and
numbness of the right leg, arm, and face. The researchers reported that the
patient's blood pressure was liable and he complained of tinnitus (ringing) in
his right ear.
The EEG approach used by Rozelle and Budzynski (1995) was a
combination of active and passive biofeedback techniques. The technique used
by the researchers was EDS (EEG driven stimulation). The researchers used a
more conventional EEG biofeedback approach that was to inhibit slow-wave
and increase fast wave EEG. Rozelle and Budzynski (1995) recorded brain
electrical activity from 19 surface electrodes in a full referential montage
according to the International 10-20 System of electrode placement, using an
electro-Cap referenced to link ears. The EEG was recorded with the patient
awake, eyes open and with eyes closed. Rozelle and Budzynski (1995)
reported that they measured their data in the following way: 128 Hz in 2-s
epochs with a gain of 32,000. Their pretesting data was collected over 300
epochs and posttesting data was collected for 500 epochs.
Rozelle and Budzynski (1995) treated the patient for 22 weeks and for a
total of 48 treatments. They reported that the patient found it was easier to
concentrate on inhibiting theta than on increasing beta. Rozelle and
Budzynski (1995) found that the patient had significant reductions in slow
wave activity. They reported that the patient improved in his speech fluency,
word finding, reading, and writing. His attention and concentration improved
as well. The patient's balance and coordination were to have improved
according to Roselle and Budzynski (1995). The patient's depression, anxiety,
and tinnitus were also greatly reduced. The researchers found that the learning
to control the EEG brain waves was an empowering process for the patient.
He reported that he felt a renewed sense of self and was optimistic for the
future.
Using EEG and EMG in the rehabilitation of patients is an empowering
process that helps the patient to regain control over their own bodies. The
EMG biofeedback enables the patients to regain muscle control, but sometimes
other modes of biofeedback maybe needed. EEG is very important in the
function of motor control. The EEG helped the patients to regain their arm
movements and one 55-year old male patient to regain his sense of balance.
EEG helped the 55-year old patient with his speech, attention, and
concentration. Through EEG the patients became aware that they could
control their own brain wave patterns, which then helped them to control their
body movements. The use of EEG and EMG biofeedback showed patient
improvement in a very short period of time, the longest session was 48 weeks.
EEG and EMG may be combined with other medical treatments, as there is no
medication involved.
References
Basmajian, J.V. (1989). Biofeedback Principles and Practice for Clinicians,
Third Edition. Baltimore, MD: Williams and Wilkins. 68.
DiMatteo, M.R. (1991). The Psychology of Health, Illness, and Medical
Care . . . An Individual Perspective. Pacific Grove, CA: Brooks/Cole Publishing
CO.
Levi, A. H. (1975). EEG Biofeedback and Its Effects on Psychological
Functioning. Ann Harbor, Michigan: Adelphi University, Xerox University
Microfilms.
Morgan, J. (2003). Psychology 476. Class Lectures. Spring (2003).
Platz, T., Kim, I-H., Engel, U., Kieselbach, A., and Mauritz, K-H. (2002).
Brain activation pattern as assessed with multi-modal EEG analysis predict
motor recovery among stroke patients with mild arm paresis who receive the
Arm Ability Training. Restorative Neurology and Neuroscience.
20, (3). 211-228.
Robbins, J. (2000). A Symphony in the Brain: the Evolution of the new
Brain Wave Biofeedback. New York, NY: Atlantic Monthly Press. 9 and 10.
Rozelle, G. R., and Budzynski, T. H. (1995). Neurotherapy for Stroke
Rehabilitation: A Single Case Study. Biofeedback and Self-Regulation. 20,
(3). 211-228.
Schwartz, M. S. (1995). Biofeedback A Practitioner's Guide, Second
Edition. New York, NY: The Gildford Press. 586-589.
Von Bozzay, G. D. F. (1980). Projects in biofeedback a Text/Workbook.
Dubuque, Iowa: Kendal/Hunt Publishing Co. 22 and 25.
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