Page 146 - Kaleidoscope Academic Conference Proceedings 2024
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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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