Page 149 - Kaleidoscope Academic Conference Proceedings 2024

Innovation and Digital Transformation for a Sustainable World

Figure 11: Motion Analysis with Kinovea Tool with tilt drinking activity. The orientation values obtained from the
angle of 8.4 degree Tilt sensor, and the values tracked in kinovea software are
correlated and analyzed to establish the concurrent validity
of the Tilt sensor in accurately monitoring the orientation of
the glass while doing the drinking activity. Figure 13 shows
the statistical correlation between data from tilt sensor and
tilt angle obtained in Kinovea tool.

4.1.3 AI Driven App Development

Artificial Intelligence (AI) utilizes SQL files by analyzing
the data within them to extract insights and make informed
decisions. In our research, the AI-driven app will use SQL
files from data collected from stroke survivors to develop
personalized rehabilitation strategies. The app will parse the
SQL files to access relevant data points, such as
demographics and outcome measures, and analyze them
using machine learning techniques. Based on this analysis,
the app will generate tailored rehabilitation strategies aimed
Figure 12: Motion Analysis with Kinovea Tool with tilt at improving motor function and independence. It will
angle of 36.4 degree
continuously learn and adapt from user data to refine its
recommendations over time. This approach aims to provide
Two cameras record the orientation of the glass during the
effective and personalized rehabilitation guidance to stroke
drinking task: one placed in front and the other providing a survivors, enhancing their functional outcomes and quality
side view of the arm performing the task. Reference lines of
of life.
1m height each are marked on the walls facing the camera.
Participants are allowed to practice the drinking movement
to find a comfortable sitting position. Once the glass is
gripped, participants are instructed to begin the drinking
activity at a comfortable self-paced speed after the command
"start”. Figure 11 and Figure 12 shows the motion analysis
with Kinovea. Variation of angles obtained from tilt sensor
and Kinovea tool shown in Figure 8.

Figure 13: Data correlation between Tilt Angle Sensor
and Tilt angle in Kinovea
Figure 14: Work flow of java backend and sql database
and their interconnection
Concurrent Validity shows the extent of agreement between
two measures taken at the same time. It is used to prove that
The smart drinking device represents a breakthrough in
the tool measures what is supposed to by comparing results
with other test that measures the same. So, here we are patient monitoring, enabling precise tracking of hand activity
crucial for rehabilitation. By capturing deflection angles
comparing the orientation of the tilt sensor fitted glass with
the orientation tracked in kinovea software. Recorded videos along the X, Y, and Z axes, along with count data, this
innovative device records invaluable metrics. Leveraging
of the drinking task from both the views are analyzed in
kinovea software. A straight line is drawn connecting the two Java backend and API Postman, this data seamlessly flows
into an SQL database, forming a comprehensive repository.
markers placed on the glass and orientation of the drinking
glass is continuously tracked throughout the task. The angle This integration not only facilitates data retrieval but also
empowers clinicians to assess patient recovery with
of deviation of the straight line with respect to the reference
vertical line on the wall will be analyzed throughout the unparalleled accuracy. Through SQL operations, including

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