Parkinson Assistant

Inspiration

The disease is a motor disability ,impairing mobility of the patient.There can be a possibility of hazards like tripping on road,slip of hands which can be fatal .Once detected early,the severance of the disease can be minimized with proper rehabilitation from physiotherapists under the guidance of the doctor.Our goal is to provide a reliable,intuitive & unintrusive solution to reduce the severity of the occurrence of the disease.

What it does

The key features of the solution are early detection of the disease occurrence&un-intrusive measurement. Primary symptom of the disease is "Pill Rolling Tremor",distinguished by excessive trembling of the fingers or the entire body.The product is a wearable hardware solution with the facility to feed live data to a web base application.The motion of the patient is assessed on his position and acceleration data obtained from the sensor. Moreover,if already diagnosed ,the solution assists in monitoring the rehabilitation progress .Warnings or alert are provided when the patient surpasses his safe motion limit.

How we built it

A wearable sensor hardware with IoT, is implemented using Arduino nano,Bluetooth module and an IMU(Inertial Measurement Unit) to analyse the live data.Primary objective is to ensure unintrusive data measurement and minimal signal losses.

The live data is then fed to the back-end code developed using Python/Node.js. The raw data is filtered further,analysed with the aid of Data analytics frameworks such as numpy .The filtered data is then compared to the ideal case of a normal person to distinguish the symptoms of the disease.

The relevant data is displayed using an interactive web application that depicts the warnings,alerts and rehabilitation progress monitor.The application is developed using React,Node.js.

Challenges I ran into

The project is an IoT solution with equal importance of hardware and software implementation.Primary challenges faced were : Develop a compact and intuitive wearable hardware with no loose components. Dearth of obtain quality datasets to train the Data analytics module. Ensure connectivity of the wearable hardware to the monitoring system. Creation of an intuitive web application to assess the data Developing a unique patient record for the analyses of the doctors.

Accomplishments that I'm proud of

Developing an integrated wearable IoT sensor solution that provides us with live streaming facility from the motion sensor.The solution provides valuable datasets for the analysis of the occurrence of motor disabilities.

What I learned

Importance of team work,Analyzing problem statements,Hardware interfacing,IoT development and communication,Importance of quality data and analytics engine.