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EPILLOW: A FABRIC-BASED PRESSURE SENSOR ARRAY FOR TETRAPLEGIC PATIENT CALL DETECTION SYSTEM
Author(s) -
Normazlianita Mohamad Alias,
Zakiran Abd Razak,
Munirah Janjori,
Mohd Yazed Ahmad,
Julia Patrick Engkasan,
Nur Azah Hamzaid
Publication year - 2021
Publication title -
jurnal teknologi/jurnal teknologi
Language(s) - English
Resource type - Journals
eISSN - 2180-3722
pISSN - 0127-9696
DOI - 10.11113/jurnalteknologi.v84.17381
Subject(s) - tetraplegia , pressure sensor , computer science , tactile sensor , signal (programming language) , interface (matter) , sensitivity (control systems) , acoustics , simulation , artificial intelligence , engineering , medicine , spinal cord injury , mechanical engineering , physics , robot , electronic engineering , bubble , psychiatry , parallel computing , spinal cord , programming language , maximum bubble pressure method
Call bell systems play an essential role in patient and nurse interaction in hospitals and at homes. However, many hospitalized patients, especially patients with tetraplegia, cannot press a call bell button for assistance due to hand weakness or paralysis from the neck down. This problem has motivated developing a fabric-based multi-array pressure sensor as a call bell garment, named ePillow, that works by detecting the pressure pattern on a pillow surface where the patient is lying down. In this study, off-the-shelf materials were utilized to form: i) a fabric-based multi-array pressure sensor system, ii) an acquisition circuit along with an interface, and iii) a signal processing algorithm to acquire and interpret the sensor data. To ensure the functionality of the proposed ePillow, a color-coded mesh plot was developed to visualize the sensor data. The reliability of the system was tested with two individuals. The pressure profile of the proposed ePillow shows a comparable profile to that of the commercialized pressure sensor. Findings from this case study have demonstrated the ability to map the force on the surface of the pillow and subsequently the location of the force applied with 71% accuracy and 70% sensitivity. 

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