Page 146 - Kaleidoscope Academic Conference Proceedings 2024

2024 ITU Kaleidoscope Academic Conference

kinematics of stroke patients as they interact with things,
specifically a “a cup of coffee,” in real time. Six stroke
survivors and six healthy individuals manipulated a 3D
printed cup with a ball moving inside that simulated sloshing
coffee at three different levels of difficulty. Performance is
assessed using both traditional kinematic measurements
(movement time and smoothness) and new kinematic metrics
that took object interaction into account (risk and
predictability) [7]. In another work MA Murphy et al.
proposed a study to determine the relationship between
movement kinematics from the drinking task and the
impairment or activity limitation level after stroke assessed
with traditional clinical outcome measures. They concluded
that kinematic movement performance measures obtained
during the drinking task are strongly associated with activity
capacity than with impairment [8]-[10].
Figure 1: Developed device with hook and loop fastener
Major challenges faced by stroke patients are
The glass, equipped with the tilt sensor device, is placed on
 Difficulty to grasp the glass the table. The device is switched on. When the glass is lifted
 Challenges in positioning the glass upright and from the table, the sensor starts tracking the orientation of
transferring to mouth the glass with respect to the zenith angle. The device's
 Difficult to empty the glass without spill functionality is programmed in Node MCU, a
microcontroller with an inbuilt Wi-Fi module. LEDs
The proposed work focuses on developing and validating a illuminate based on predefined threshold values: green for 0
tilt sensor device designed to monitor the orientation of to 20 degrees, yellow for 21 to 30 degrees, orange for 31 to
drinking glasses during activities involving stroke survivors. 50 degrees, and red for greater than 50 degrees. Continuous
The study will also evaluate the device's reliability in a tracking of the glass's orientation and movement frequency
sample of healthy individuals by establishing its concurrent readings is performed, and the data output is monitored in
validity in stroke survivors. Additionally, the research aims the serial monitor of the arduino software. This data is
to assess the effectiveness of the device in providing real- wirelessly transmitted to the cloud platform for further
time feedback during drinking tasks and to explore its development of AI driven applications.
potential for enhancing rehabilitation outcomes in this
population. The tilt sensor device design consists of MPU6050, Node
MCU, Lithium polymer battery, super debug TP4056, LEDs,
2. DESIGN AND WORKING PRINCIPLE and ON/OFF switch. The components are fixed in a 3D print
fabricated cylindrical model and its sealed. Component
The tilt sensor device is attached to the glass is custom-fitted design with LED is shown in Figure 2. Figure 4 shows the
and developed using a Gyroscope and Accelerometer based development flow chart of device development.
sensor. The design of electronic enclosure carried out using
the CAD tool CATIA as show in the Figure 3, with the
resulting model converted to an STL file for 3D printing. The
device is then 3D printed and integrated into an Internet of
Things (IoT) based software for real-time monitoring as
shown in the Figure 1.

Figure 2: Component design with enclosure for
Proposed Device

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