4.3 Article

Sensor Cell Network for Pressure, Temperature and Position Detection on Wheelchair Users

Publisher

MDPI
DOI: 10.3390/ijerph19042195

Keywords

wheelchair user; fiber Bragg grating; pressure and temperature sensors; pressure ulcers; position detection

Funding

  1. FCT/MCTES
  2. EU [UIDB/50025/2020-UIDP/50025/2020, UIDB/50008/2020UIDP/50008/2020]
  3. Scientific Employment Stimulus-Institutional Call [CEECINS T/00026/2018]

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This study proposes an optical sensing network for monitoring pressure and temperature in wheelchairs to prevent pressure ulcers and track the position of the user. Experimental results show that the sensor cells have high sensitivity to pressure and temperature changes. The proposed sensing network is validated for accuracy and reliability through tests on specific relief positions and random position changes.
This work proposes an optical sensing network to monitor pressure and temperature in specific areas of a wheelchair to prevent pressure ulcers and to monitor the position of the wheelchair user by analyzing its pressure distribution. The sensing network is composed of six optical fiber Bragg grating (FBG)-based sensor cells. Each sensor cell is built from a polylactic acid (PLA) base and has two FBGs, one embedded in epoxy resin to monitor pressure variations (FBG(P)) and another without resin to monitor temperature (FBG(T)). Once produced, all sensor cells were experimentally characterized for pressure and temperature variations, resulting in an average pressure sensitivity of 81 +/- 5 pm/kPa (FBG(P)) and -5.0 +/- 0.4 pm/kPa (FBG(T)), and an average temperature sensitivity of 25 +/- 1 pm/degrees C (FBG(P)) and 47.7 +/- 0.7 pm/degrees C (FBG(T)). The sensor cells were then placed in six specific areas of a wheelchair (four in the seat area and two in the shoulder blade area) to carry out experimental tests, wherein the response of the sensors to a specific sequence of relief positions was tested. During the execution of the test, the optical signal of all sensors was monitored, in real time, with the pressure and temperature values detected in each zone of the wheelchair. In addition, random position changes were performed in order to evaluate the precision of the proposed sensing network in the identification of such positions.

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