Comparison of Biomarkers for Diagnosis of Alzheimer\'s Disease

Project Title

Comparison of Biomarkers for Diagnosis of Alzheimer\'s Disease

Project Area of Specialization Biomedical EngineeringProject Summary

The possibility to diagnose Alzheimer's disease with complete certainty is only after death when a microscopic examination of the brain can reveal the characteristic plaques and tangles of nerve fibers. In our FYP, we developed a way to diagnose Alzheimer's disease at its early stages so that the patient may receive accurate treatment.  An electroencephalogram (EEG) is a test that detects electrical activity in your brain using small, metal discs (electrodes) attached to your scalp. In this test, brain cells communicate through electrical impulses and are active all the time, even in sleep mode. This activity shows up as wavy lines on the screen.

Also, these EEG signals show the population of neurons this is how it plays a role in the diagnosis of AD as AD is a neurodegenerative disease. We have performed this EEG test using a 32-channel EEG cap with a Nu-AMP amplifier having a 2000 sampling rate. NeuroScan software installed on a laptop was used to acquire the data. The EEG data of patients are recorded at Railway General Hospital, Rawalpindi. The 32-channel cap was placed on the patient's scalp and a reference electrode was placed behind the subject's earlobe. We have collected the data from almost 70 patients. Lastly, we performed the data analysis using MATLAB software. Data analysis means the extraction of important information from EEG signals. There are irregular patterns in EEG signals of dementia patients which were indicated by EEG data analysis. This step involves the identification of EEG markers that were used for the diagnosis of Alzheimer's disease. On the basis of this data analysis, we gave our results in accordance with our research hypothesis.

"EEG markers can be used to identify the onset of Alzheimer's disease among dementia patients."

On the basis of our results, EEG proved to be an effective way to differentiate between healthy elder people and AD patients.

Project Objectives

There is no accurate way to diagnose Alzheimer's disease at its early stages (https://pubmed.ncbi.nlm.nih.gov/20455865/). Our project aims at developing an accurate way to diagnose Alzheimer's disease at its early stages. The aim of our project is to diagnose Alzheimer's disease using EEG signals and also a comparison of these EEG signals with the blood markers to develop an efficient way to diagnose Alzheimer’s disease at its early stages. Electroencephalography (EEG) equipment is used in this project which is the clinical diagnostic tool used to record brain activity. This EEG equipment is used for screening neuronal cell death among AD patients so this decline in brain activity acts as a biomarker for the early diagnosis of Alzheimer's disease.

Project Implementation Method

Dementia patients were recruited and the screening of these patients was conducted by trained clinicians using MOCA (Montreal Cognitive Assessment) test scores. After the screening of patients, their electroencephalographic (EEG) data has been recorded by following an efficiently designed data acquisition protocol. This protocol involves the state of the patient during the data recording. After collecting the EEG data of patients, pre-processing of data and data analysis was performed. After the analysis of this data, we were able to identify EEG markers and compare these biomarkers with the clinical test results. This comparison helped us formulate a conclusion of whether the patient has Alzheimer's disease or not. Hence, we were able to find a definite way to timely diagnose Alzheimer's disease.

Benefits of the Project

Alzheimer's disease is the most common cause of dementia in elderly people and one of the most common causes of death around the world. In 2019, approximately 11 thousand people died due to Alzheimer’s dementia (https://ourworldindata.org/causes-of-death). By identifying a definite way to diagnose Alzheimer's disease, we will be able to treat patients with dementia in time and hence can make a difference in the number of deaths caused due to Alzheimer's disease. We will be able to timely diagnose whether Alzheimer's disease is the cause of dementia for a certain patient or not. The early diagnosis of Alzheimer's disease is extremely important to decrease the death rate due to this disease. By completing this project, we will be able to identify electroencephalographic biomarkers (EEG markers) in order to find a proper way of diagnosing  Alzheimer's disease. The doctors will then be able to timely give treatment to the dementia patients and hence lower the death rate to some extent. If this disease is timely diagnosed, patients can be saved from prolonged treatment which may help vacant hospital beds for other patients suffering from life-threatening diseases and also save 50 percent of the cost reserved for major health hazards. The caregivers will be saved from fatigue and mental distress and the payment for a full-time caregiver can also be reserved if the disease is diagnosed and treated in time. Medical expenses of the patient will also reduce. In this way, not only the patient will benefit from the early diagnosis of Alzheimer's disease, but the doctors and caregivers will also get advantages.

Technical Details of Final Deliverable

To assess symptoms, we ask questions or perform tasks associated with cognitive skills, such as memory, abstract thinking, problem-solving, language usage, and related skills.

The doctor conducts mental status tests to test the thinking (cognitive) and memory skills of AD Patients. We use the scores on these tests to evaluate the degree of cognitive impairment.

We are working on new diagnostic tools that may enable doctors to diagnose Alzheimer's dementia earlier in the course of the disease, when symptoms are very mild or before symptoms even appear.

We are investigating a number of disease markers using EEG and biomarkers that indicate whether patients have Alzheimer's dementia.

 The EEG is recorded is taken from 32-channel EEG equipment with better quality signals and specified biomarkers for its diagnosis.

Final Deliverable of the Project Software SystemCore Industry MedicalOther IndustriesCore Technology OthersOther TechnologiesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	80000
EEG cap	Equipment	1	60000	60000
EEG gel	Equipment	2	5000	10000
Consumable electrodes	Miscellaneous	6	150	900
Travel cost	Miscellaneous	13	700	9100