Publication: Load Cells Application for Developing Weight-Bearing Detection via Wireless Connection
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Issued Date
2018
Resource Type
Language
eng
File Type
application/pdf
Access Rights
open access
Rights
ผลงานนี้เผยแพร่ภายใต้ สัญญาอนุญาตครีเอทีฟคอมมอนส์แบบ แสดงที่มา-ไม่ใช้เพื่อการค้า-ไม่ดัดแปลง 4.0 (CC BY-NC-ND 4.0)
Rights Holder(s)
มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
The Open Biomedical Engineering
Journal, Volume 12 : 2018 (101-107)
Suggested Citation
Tossaphon Jaysrichai Load Cells Application for Developing Weight-Bearing Detection via Wireless Connection. The Open Biomedical Engineering
Journal, Volume 12 : 2018 (101-107). doi:10.2174/1874120701812010101 Retrieved from: https://hdl.handle.net/20.500.14740/11854
Author(s)
Organization
Abstract
Objective:
To focus on a device development for measuring the weight-bearing on feet while simultaneously reporting data on smartphone usage. Secondly, the output data from this device are tested for the accuracy.
Methods:
Researcher used eight pieces of 50 kg Body Load Cell Weighing Sensor Resistance strain Half-bridge Original (four pieces per foot), two pieces of HX711 amplifier, MCS-51 AT89 C51 microcontroller and HC-05-Bluetooth to develop the device. This device is called the Wireless Weight-Shifting Detector (WWSD) which is used to measure weight-bearing on feet by being attached to sandals. The output data are simultaneously reported on smartphone via line-graphs [load (kg) per sampling data] and numeric by FootpressV1 application. The device was tested using accurate measuring data with standard weights and calculated in percentage of accuracy (%). After that, WWSD was used to compare the weight-bearing measurement during standing with forceplate (AMTI; OR6-7 Platform).
Results:
The percentage of accuracy of WWSD was more than 97% and the error values from the measuring standard weights ranged under ±0.23 kg. The accuracy of measurement was more than 95% when compared with the force plate.
Conclusion:
WWSD can report simultaneously the weight-bearing on feet with rather accurate data on smartphone. It may be helpful in assisting physical therapists while training patients in clinic.