1. handwriting. It also affects non-motor functions

1.                 
INTRODUCTION

1.1   
Parkinson’s
Disease

After Alzheimer’s disease, Parkinson’s
is the second most common neurodegenerative disorder. It is a chronic, progressive
neurological disorder that affects a person’s motor functions (voluntary
movements), such as walking, buttoning shirts and handwriting. It also affects
non-motor functions (involuntary movements), such as mood, bowel function and
sleep. In general, the motor functions are symptoms that are visible on the
outside while the non-motor symptoms are less visible, affecting processes
within the body. It is common for non-motor symptoms such as pain, sleep
disturbance, altered sense of smell or mood changes to precede the onset of
motor symptoms and a diagnosis of Parkinson’s. People with Parkinson’s often
report that the non-motor symptoms present a greater challenge to their quality
of life and are harder to deal with compared with the impact of motor symptoms
1.

 

During any kind of neurological disorder the flow of sodium and
potassium ions degenerates in the brain. As a result of which there is
degeneration of action potentials. Degeneration of action potential also
effects the muscle movement of the person. The person lack the desired movement
as the coordination between the EEG and EMG gets disrupted. Simultaneous
recording of EEG and EMG provides great potential for studying human brain
activity with high temporal and spatial resolution. The  area of the 
brain that is affected by PD is the substantial nigra which contains
a  specialized set of neurons that send
signals in the form of neurotransmitter 
called dopamine. This signals travel to the stratium via long fibers
called axons. The activity of this pathway controls movements of the body. When
neurons in the substantia nigra

degenerate, the resulting loss of dopamine causes the nerve cells of
the stratium to fire excessively. This makes it impossible for people to
control their movement, leading to the primary, motor symptoms of PD 2.

 

1.2   
Motor
and Non-Motor complications

The Motor complications in PD
consist of motor fluctuations, as a result of the pharmacological treatment. It
can be either excessive hyperkinesias (e.g. freezing, rigidity, increasing off
times, dysphasia, dysarthria, and respiratory compromise) or excessive hyperkinesias
(e.g. choreiform and dystonic dyskinesia). Motor complications decrease the
patient’s quality of life. They affect emotional health, decrease mobility,
decrease independence for activities of daily living, and cause social stigma
5. The primary goal of treatment of early and later stages of PD is the maintenance
of independent motor function. Such treatment allows the patient to remain
independently mobile for as long as is possible, and greatly improves quality
of life3.

 

The main symptoms of PD are as follows:

 

Motor Symptoms:

Ø  Bradykinesia

Ø   Rigidity

Ø  Tremor

Ø  Postural instability

 

Non-Motor Symptoms:

Ø  Neuropsychiatric

Ø  ICDs Sleep disorder

Ø  Autonomic dysfunction

Ø  Sensory.

 

Table1 shows
the symptoms common to Parkinson’s
disease and major depression.

Figure 1
shows a person suffering from PD.

 

 

2.     
LITERATURE STUDY

 

2.1 Research on Parkinson’s Disease

 

Lisa et. al 24 worked on Freezing of Gait disorder in Parkinson’s
disease patient.  Accelerometer sensors
are widely utilized to measure the patient’s movements. EMG sensors and EEG
sensors are also utilized to accurately detect the FOG episodes. A comparison
of these methods is given in their work. FOG detection can be used in a broad
spectrum of health applications for patient monitoring, to enhance the quality
of life for PD patients, and to erode health care cost.

Mihai
et. al 25 worked on artificial neural network (ANN) classifier for
patients suffering from neurological disorders/diseases.According to them that
correlation size together with Lyapunov exponents estimated from both
electroencephalography (EEG) and electromyography (EMG) signals, are the
crucial variables in the classification of mental tasks.

Rajamanickam
et. al 26 in their study
applied machine-learning algorithms to categorize EEG emotional states in PD
patients that would classify six basic emotions (happiness and sadness, fear,
anger, surprise and disgust) in comparison with healthy controls (HC). In this
work, they made the comparative study of the performance of k-nearest neighbor
(kNN) and support vector machine (SVM) classifiers using the features derived
from HOS and from the power spectrum. These results demonstrate the
effectiveness of applying machine learning techniques to the classification of
emotional states in PD patients in a user independent manner using EEG signals.

 

According to Alexander
et. al 27 the non-linear characteristics of surface electromyogram
(sEMG) and tremor acceleration is a possible diagnostic tool, and is a
predictor for PD. It was found that the non-linear parameters allowed
discriminating some 85% of healthy controls from PD patients. Hence this
approach offers considerable potential for developing sEMG-based method for
pre-clinical diagnostics of PD.

 

John et. al 28 examined the corticomuscular
electroencephalographic-electromyographic (EEG-EMG) coherence elicited using  motor tasks in healthy participants and those
with Parkinson’s disease (PD) . Fast Fourier transform and coherence analysis
was performed. Corticomuscular coherence was analyzed between each EEG
electrode and right and left superior and inferior OO muscles up to 200 Hz. Significant
coherence peaks exceeded 95% confidence limits (.003). Their results supported
task specificity for both groups and, in PD, a diminished modulation
flexibility linked to the sensorimotor area and reduced corticomuscular
coherence at the SMA.

 

Gennaro et. al 29 used a wavelet analysis approach, which was possible to investigate
better the transient and intermittent behavior of multiple electromyographic
(EMG) signals during ballistic movements in Parkinsonian patients. A wavelet
cross-correlation analysis on surface signals of two different shoulder muscles
allowed evidence to relate unsteady and synchronization characteristics. With a
suitable global parameter extracted from local wavelet power spectra, it is
possible to accurately classify the subjects in terms of a reliable statistic
and to study the temporal evolution of the Parkinson’s disease level.        

 

Marsden et.
al 30 examined ten patient
with Parkinson’s disease They were seen following bilateral or unilateral
implantation of microelectrodes into the sub thalamic nucleus. Local field
potentials (LPFs) were recorded from adjacent sub thalamic nucleas
macroelectrodes (STNME) contacts simultaneously with EEG activity over the
supplementary motor (Cz- FCz) and sensorimotor (C3/4-FC3/4) areas and EMG
activity from the contra lateral wrist extensors during isometric and phasic
wrist movements. Significant coherence was seen between STNME LFPs and Cz-Fz,
STNME LFPs and C3/4-FC3/4 and STNME LFPs and EMG over the range 7-45Hz. EEG
phase-led STNME LFPs by 24.4ms (95% confidence interval 19.8 to 29.0 ms). EMG
also led STNME LFPs, but time differences tended to cluster around one of two
values: 6.3ms (-0.7 to 13.3 ms) and 46.5ms (26.2 to 66.8ms). The presence of
coherence between EEG and STNME LFPs in both the beta and gamma band (as
opposed to only the beta band between EEG and cerebellar thalamus) suggests
that there may be some relative frequency selectivity in the communication
between different motor structures.

 

Brown et. al 31 observed that in PD patients, medication
reduced action tremor which contributes to the weakness which can be measured
in some torque. Strength and action changes are seen when action tremor was
expressed as percentage. Tremors were recorded during maximal wrist extension in
peak torque or percentage mean rectified EMG. In parkinsonian patients when
they were on and off and in anti parkinsonian patients off medication, a 10-Hz
synchronizing influence medication, and in age and sex matched healthy subjects
dominates muscle activity at the wrist.

 

 

     

 

Gurfinkel
and Osovets 32 examined the
hypothesis of Parkinsonian tremor arising from instabilities in the control of
upright stance in the body considered as an inverted pendulum. To describe the
vertical position of the body, “a two-link model was investigated consisting of
foot and knee as an inverted pendulum held by the gastrocnemius muscle”, which
they later extended to “other link of the body”. They wondered if pathological
tremor results from passing into a parametric resonance regime from a region of
stability upon changing a parameter that represents the magnitude of a periodic
change in muscle strength at the frequency of physiological tremor. This is a
peripheral mechanism model of tremor, focusing on balance control of muscles.
The idea of a resonance process in their model came from two of their
observations in tremor oscillograms: 1) An abrupt change in amplitude in the
transition between Parkinsonian and physiological tremor and 2) no higher
harmonic components in Parkinsonian tremor, also noting that “the frequency of
the Parkinson tremor is almost exactly half the frequency of the physiological
tremor (8-12 cycles/sec Hz) makes the process similar to that which in the
theory of oscillations is called ‘parametric resonance”.

 

Edwards et.
al 33 worked on a neural network
model under parameter changes that weaken the connection between the network
units. They proposed the hypothesis that the onset of a regular oscillation in
PD is a change in dynamical regime of the network from a normally a periodic
one to a more regular one as the parameter corresponding to dopamine efficacy
decreases”. They explore their hypothesis using a piecewise linear
approximation to a linear neural network. Their work suggested that the
possibility that tremor in PD does not result simply from a particular group of
tremorgenic cells but that it arises from normal tremor via bifurcations in a
dynamical process.

 

Terman et.
al 34 developed a cell-level model
of the external segment of the globus pallidus and the sub thalamic nucleus,
and their interactions. They propose that conductance based cellular models,
rather than firing-rate models are required to capture the dynamic activity of these
structures and that reciprocal connections between the external globus pallidus
and the subthalamic nucleus, along with lateral inhibition within the external
globus pallidus and input from the striatum, could generate the oscillations
seen in Parkinsonian tremor.

 

 

2.2 Research Areas on Parkinson’s disease:

Some of the research areas associated with
Parkinson’s disease: 84

 

 

 

 

 

 

Parkinson’s disease Clinical Studies:

 

It offer an opportunity to help researchers find
better ways to safely detect, treat, or prevent PD and therefore hope for
individuals now and in the future.   But studies can be completed
only if people volunteer to participate.  By participating in a clinical
study, healthy individuals and people living with Parkinson’s disease can
greatly benefit the lives of those affected by this disorder. Current
studies include genetics and PD, search for PD biomarkers, experimental
therapies and other treatment options, diagnostic imaging, brain control and
movement disorders, DBS, and exercise and PD.

 

Animal
models:

These
are valuable tools for scientists studying disease mechanisms to develop new
treatments for people with PD.  For example, a study of the drug
isradipine-which had been shown in animal models to have a protective effect on
dopaminergic neurons, is being tested for a similar neuroprotective effect in
humans.

Cognition
and Dementia: 

Mild
cognitive impairment is common in PD, sometimes in its early stages, and some
people develop dementia in the disease’s later stages.  The agencies have
funded research using neuroimaging to predict which individuals with PD might
develop cognitive impairment.

Deep
Brain Stimulation (DBS): 

The
study and development of DBS, which is now considered a standard treatment
option for some people living with PD whose symptoms no longer, respond to PD
medications.  Researchers are continuing to study DBS and to develop ways
of improving it. A two-part study funded by the NINDS and the Department of
Veterans Affairs first compared bilateral DBS to best medical therapy,
including medication adjustment and physical therapy.  Bilateral DBS
showed overall superiority to best medical therapy at improving motor symptoms
and quality of life.  The second part of the study, involving nearly 300
patients, compared sub thalamic nucleus (STN) DBS to globus pallidus interna
(GPI) DBS.  The two groups reported similar improvements in motor control
and quality of life in scores on the Unified Parkinson’s Disease Rating
Scale.  On a variety of neuropsychological tests, there were no
significant differences between the two groups.  However, the STN DBS
group experienced a greater decline on a test of vasomotor processing speed,
which measures how quickly someone thinks and acts on information. Also, the
STN DBS group had slight worsening on a standard assessment of depression,
while the GPI DBS group had slight improvement on the same test.

 

Other
clinical studies hope to determine the best part of the brain to receive
stimulation and to determine the long-term effects of this therapy.  In
addition, researchers are developing and testing improved implantable pulse
generators and conducting studies to better understand the therapeutic effect
of neurostimulation on the brain.

Environmental
studies: 

Risk
factors include repeated occupational exposure to certain pesticides and
chemical solvents may influence w PD patients.  Researchers analyzed the
occupational histories of twins in which one of the pair developed PD. 
Based on estimates of exposure to six chemicals previously linked to PD,
the researchers concluded that two of the common solvents were
significantly linked to development of PD. 

Exercise: 

Exercise
routines are often recommended to help individuals with PD maintain movement
and balance necessary for everyday living.  A recent study evaluated three
different forms of exercise—resistance training, stretching, and tai chi and
found that tai chi led to the greatest overall improvements in balance and
stability for people with mild to moderate PD.  A current trial is
studying the effects of two levels of exercise in people who have been recently
diagnosed with PD. 

Genetic
studies: 

A
better understanding of genetic risk factors is playing a critical role in
elucidating PD disease mechanisms.  Current clinical studies include the
genetic connection to memory and motor behavior, the search for genes that may
increase the risk of PD and related neurodegenerative disorders, and
identifying biomarkers for PD. 

Mitochondria:  

These
cellular energy factories may play an important role in PD.  Scientists
have found that hundreds of genes involved in mitochondrial function are less
active in people with PD.  Drugs that target genes involved in
mitochondrial function could perhaps slow progression of the disease.

Nerve
growth factors: 

One of the
interests to researchers studying neurodegenerative diseases is growth factors
are proteins involved in nervous system formation. A single clinical trial
will assess the safety, tolerability, and potential clinical effects of gene
therapy with Glial Derived Neurotrophic Factor (GDNF). GDNF is a protein that
may help protect dopamine-producing nerve cells.  This trial for
individuals with advanced PD is based on research showing that an advanced
viral technique for delivery of the GDNF gene into the brain improves the
health and function of the dopamine neurons in animal models of PD.

Neuro-protective
Drugs:  

Basic,
clinical, and translational research aimed at protecting nerve cells from the
damage caused by PD.  The NINDS-funded NeuroNext Network which is designed
to test new therapies and to validate biomarkers in a number of neurological
disorders, including Parkinson’s disease

Stem
cells:   

 

Scientists
are exploring various types of cells, including induced pluripotent stem cells
(iPSCs), as opportunities for PD drug discovery.  iPSC technology is used
to define disease mechanisms and discover the most promising treatments for
sporadic PD. 

 

CONCLUSION

 

              Parkinson’s
disease is common neurodegenerative illness in present scenario. Research shows
that most of the eastern part and north east of the country like-India,
patients having neuronal disorders are PD only. A combination of genetic and environmental
factors is likely to be important in producing abnormal protein aggregation
within select groups of neurons, leading to cell dysfunction and then death.
The diagnosis remains a clinical one, and there should be a high index of
suspicion to exclude other causes of Parkinson’s disease. According to the
clinical intervention and knowledge shared by neurologists, a large number of
agents together with surgical interventions are now available to treat early
and late complications of PD. Increasing attention is being given to the
diagnosis and treatment of non-motor complications in PD. Future developments
in PD are likely to focus on the concept of disease modifying drugs which offer
neuroprotection.