Artificial Intelligent Predicated wearable device for detecting and assisting with FoG in Parkinson\'s patients using Cueing techniques and neural networks.

Parkinson's disease is a brain disorder that leads to shaking, stiffness, and difficulty with walking, Parkinson's symptoms usually begin gradually and get worse over time. FOG is the condition when the patient feels like his feet have been glued to the ground and he cannot take a step further. 83%

Project Title

Artificial Intelligent Predicated wearable device for detecting and assisting with FoG in Parkinson\'s patients using Cueing techniques and neural networks.

Project Area of Specialization

Wearables and Implantable

Project Summary

Parkinson's disease is a brain disorder that leads to shaking, stiffness, and difficulty with walking, Parkinson's symptoms usually begin gradually and get worse over time. FOG is the condition when the patient feels like his feet have been glued to the ground and he cannot take a step further. 83% of all PD patient suffers from this condition. We are hoping to design a wearable a device for PD patient which will assist them during the condition of FG. The device will work on the phenomena of Cueing. Cueing in simple words is giving a hint to the brain to take the step when FOG occurs. There are 3 types of cueing which we found in different research papers that include: visual cues, auditory cues, and somatosensory cues.

Project Objectives

Our foremost motive was to detect Parkinson's disease (to be precise the condition of gait) and to evaluate gait features. As walking can be challenging for aging individuals and people with neurological disorders such as Parkinson's disease (PD). Gait impairment characterized by reduced speed and higher variability destabilizes gait and increases the risk of falls. External auditory cueing provides an effective strategy to improve gait, as matching footfalls to rhythms typically increases gait speed and elicits larger steps, but they need to synchronize to an outside source often has a detrimental effect on gait variability. In the present study, we compare the effects of internal and external cueing techniques on walking for both people with PD. Gait is one of the most affected characteristics of this disorder although symptoms of Parkinson's disease are varied. Parkinson Ian's gait is characterized by small shuffling steps and general slowness of movement (hypokinesia), or even the total loss of movement (akinesia) in extreme cases. We by using an electrical and electronic system detect the condition of gait which is the foremost objective of our FYP then when our phase 1 got done we come towards cueing. In cueing, we use a visual sensor (laser) to give a signal to the patient’s brain to move the legs rather than staying in that condition. Our main focus shall be on visual cueing while auditory and somatosensory cueing will be our secondary goal.

Project Implementation Method

We have divided our project into two major tasks, the first one is the detection of Freezing of Gait (FoG) in real-time and the second task is to assist the patient during FoG using Cueing techniques. Now for the detection of FoG, we are using a system consisting of an accelerometer, gyroscope, and EMG sensors. We will be using AI neural networks to make our algorithm more accurate and efficient. Once we are done with the detection phase, we will start working on cueing techniques i.e. visual cues and somatosensory cues. For this purpose, we will be using a vibration module and a set of the laser. Our device will be working in Master-slave topology, the master unit being the main brain of the system is responsible for the detection of FoG in real-time and once the FoG is detected by the master unit, it will send a signal to the two slave units to assist the patient by mean of visual and somatosensory cues.

Benefits of the Project

With this project, we aim to help millions of patients in the world suffering from Parkinson’s disease. The falls that occur during FoG are expected to greatly reduce using our device improving the quality of life and safety of the users. ? The data and analytics that our device shall gather through daily use will help the researchers discover new and optimal solutions to the various problems related to Parkinson's. ? The current solutions and treatments that exist for Parkinsons patients are either costly or ineffective. Our device shall go towards providing a safe and effective means to help Parkinsons' patients while maintaining a sense of budget-friendliness.

Technical Details of Final Deliverable

. With this project, our purpose is to assist the hundreds and thousands of people who suffer every day from Parkinson’s disease. The falls that arise due to FoG are expected to substantially lessen by use of our tool thereby enhancing the quality of life and protection of the users.

• The records and analytics that our device shall accumulate through everyday use will assist the researchers to find out new and most reliable answers to the numerous issues associated with Parkinson’s.

• The modern answers and remedies that exist for Parkinson’s sufferers are both high priced or ineffective (in the long term). Our device shall move closer to supplying a secure and powerful way to assist Parkinson’s sufferers even as keeping an experience of cost-effectiveness cueing.

Final Deliverable of the Project

Hardware System

Core Industry

Medical

Other Industries

Core Technology

Wearables and Implantables

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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