Early detection of Alzheimer's Disease.

1. Department of Biomedical Engineering
Comparison of different EEG markers for
the diagnosis of Alzheimer’s Disease
Group Members: 03
Falak Anjum 2848
Fazal Ullah 2760
Shakeel Abbasi 2855
Supervisor Name: Mr. Hamza Toor

2. Department of Biomedical Engineering
Problem Statement
 Alzheimer’s disease (AD) is the most common cause of brain
dementia among elderly.
 Currently, there is no single clinical test available for accurate
diagnosis of AD.
 Study has shown that Electroencephalography (EEG) has
potentials in differentiating between healthy elderly and probable
AD patients
 Unfortunately EEG systems are very expensive to be a viable
options in clinical setups in developing countries like Pakistan
 Efficacy of low-cost EEG Systems in measuring EEG Signals for
diagnosis of AD is yet to be tested
Fig.[3] Healthy brain and
Alzheimer [1]

3. Aims & Objectives
• There is No single test for Alzheimer’s Disease
• Physicians, often seek help of specialists
 Such as neurologists and geriatricians
• A thorough medical evaluation includes
 Obtaining a medical and family history from the individual, including cognitive
and behavioral changes
 Asking a family member to provide input about changes in thinking skills and
behavior
 Conducting cognitive tests and physical and neurologic examinations
 Having the individual undergo blood tests and brain imaging to rule out other
potential causes of dementia symptoms, such as a tumor or certain vitamin
deficiencies.
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4. AIM OF STUDY
Department of Biomedical Engineering
AD Probable
Healthy
32 Channel
EEG
Feature /
Classification
Blood Markers/
BDNF
Comparison

5. Literature Study / Data
Collection
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2660 Papers were
identified
2300 excluded
paper
IEE=100
Google Scholar=1000
NCBI= 160
Hindawi = 800
Microsoft = 500
Core = 100
339 Papers
excluded
360
Keywords
screened
21
Abstract
screened
21 papers are included for
Literature review

6. Methodology
 Devices:
 EEG Headset, Neuro Scanner, Electrolyte Gel
 Software:
 Matlab, SKAN software
 Procedure:
1. Subject was asked to sign Consent form
2. EEG cap was placed on his/her head
3. Data was recorded for 20 minutes, it was
comprised of 2 sessions and of 4 segments
each with 5 minutes
4. All the data was stored in SKAN software for
further analysis
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Self captured
Self captured
Self captured

7. Data Collection Protocol:
 Neuro sensing setup
 EEG Headsets
 Recording EEG signal
 Applying soft tools on recorded data
 Also analyzing blood samples on the basis of Neuro proteins.
 Interpreting results from collected data
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8. CHALLENGES:
Problems:
 Oily skin
 Dandruff
 Long Hairs
 Subjects were old
 They feel severe pain in prolong sitting, so we helped them with
massage
 Electrolyte gel was not viscous, as a result the probability of
interconnection of electrodes was great. Which leads to emergence
of false data
 Covide factor played role, as a result our data collection is in
progress
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9. Proposed Design Block Diagram
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MCI Patients
EEG
Collection
EEG Markers
Blood Sample
Collection
Protein
Markers
MMSE
(Clinical
Evaluation)
Bio Markers Calculation
Comparison
of
Biomarkers
for detection
of
Alzheimer’s
Disease

10. Executed Work
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Data Collection

11. Remaining Work
 Now we are in our first phase of data collection. After this phase we will
jump towards second phase
 Second phase is related to BDNF
 Our data collection is in progress (Covide Lockdown)
 Then we will go for data Comparison/Analysis
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12. Expected Results
 After literature review, we are highly motivated, that we will be able to
conclude our Problem statement in a positive way.
 Which will help us in finding a theory, which could be use in early detection
of Alzheimer Disease.
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13. Gantt Chart
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2021

14. References
 https://www.healthworks.my/wp-content/uploads/2014/07/alzheimers.jpg[1]
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15. Thank you
Any Questions ?
Department of Biomedical Engineering