Wearable Sensors and Data Analytics (Samsung Watch App) & (Diary App)

By Christopher Chi
Slide 1: Title slide for wearable sensors and data analytics project featuring Samsung Watch and Diary apps

Slide-1

Christopher Chi

Dr. Behnaz Ghoraani

Slide 2: Introduction explaining the development of wearable applications for Parkinson's Disease patients

Slide-2

Introduction

  • Develop an application on a wearable device that extracts inertial measurement unit data from sensors, which translates to clinical information about Parkinson's Disease patients' response to their medication.
  • Objective involves personalizing therapeutic treatment on the outside setting of a hospital through this system of analyzing movement in a client's natural living environment.
Slide 3: Samsung Watch selection rationale highlighting availability and user-friendliness

Slide-3

SAMSUNG Watch

  • We selected a SAMSUNG Watch since it is available for everyone and it is very user friendly!
Slide 4: Data collection process from accelerometer and gyroscope sensors with server transmission capabilities

Slide-4

Data

  • The data gathered from the Accelerometer and Gyroscope sensors from the SAMSUNG Watch are sent to a server.
  • The collected data can be temporarily stored on the Watch itself.
    • The watch can store data for up to a week if necessary!
Slide 5: Azure Database integration for data storage and management

Slide-5

Azure Database

This slide shows the integration with Microsoft Azure Database for storing and managing the collected sensor data from the wearable devices.

Slide 6: Data visualization through charts showing accelerometer and gyroscope readings with timestamp and coordinate axes

Slide-6

Charting/Graphing

  • Charts the data that are collected from the sensor in 2 different graphs
    • Accelerometer/Gyroscope
      • X-axis → Timestamp
      • Y-axis → x, y, or z-data values (one for each)

Slide shows data visualization through two charts showing accelerometer and gyroscope readings with timestamp and coordinate axes

Slide 7: Technical challenges including data transmission, local storage, and high-frequency data handling

Slide-7

Challenges

  • Ensuring there was no drop loss in the data as it was being collected/sent
  • Storing the data locally after losing connection to Wifi
  • Implementing an efficient method of sending data to the server with a frequency of 100 Hz without crashing the application
Slide 8: Introduction to the companion diary application for patient data collection

Slide-8

Wearable Sensors and Data Analytics (Diary App)

Slide 9: About section describing mobile app functionality for elderly Parkinson's patients to track daily activities and conditions

Slide-9

About

  • Develop a mobile application that allows elderly people to answer the following questions relating to their physical condition, medication, and how well the sensor performed throughout their day.
  • Exhibit their daily activities and evaluate the severity of their condition, whether they are improving, regressing, or staying neutral.
Slide 10: User authentication system with email and password signup generating unique IDs for watch app integration

Slide-10

Authentication

  • Each user will sign up with an email and password to be able to access the application
  • Signing up will also generate an ID for them to input into the Watch app
Slide 11: App design featuring 30-minute notification intervals for questionnaire completion including medication state, activity, and gait experiences

Slide-11

Design

Client will receive a notification in regards of a questionnaire every 30 minutes.

Client will then be able to fill out the following forms (Medication State, Activity, and Experiences of Gaits).

Slide 12: Example screenshot showing gait complications form being filled out and submitted

Slide-12

Example

Gait Complications form being filled out with submission.

This slide shows a practical example of the mobile application interface where users can input information about their gait complications and submit the form.

Slide 13: Design features showing completed forms turning green and being disabled until next 30-minute interval with Azure integration

Slide-13

Design

  • After the forms are completed, the buttons turn green and are disabled until the next 30 minutes
  • The responses are sent to Microsoft Azure as well
Slide 14: Conclusion and future work outlining system efficiency, trial runs, and application stability goals

Slide-14

Conclusion & Future Work

  • Develop an efficient system of collecting critical information of a patient diagnosed with Parkinson's Disease
  • Perform trial runs with using the watch and mobile application for the entire duration of the day
  • Ensure the Watch application does not crash
Slide 15: Thank you slide concluding the presentation

Slide-15

Thank you!

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For a downloadable version of this presentation, email: I-SENSE@FAU.

Additional Information
The Institute for Sensing and Embedded Network Systems Engineering (I-SENSE) was established in early 2015 to coordinate university-wide activities in the Sensing and Smart Systems pillar of FAU’s Strategic Plan for the Race to Excellence.
Address
Florida Atlantic University
777 Glades Road
Boca Raton, FL 33431
i-sense@fau.edu