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Related Experiment Video

Updated: Jul 29, 2025

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Design and Implement Strategy of Wireless Bite Force Device.

Jinxia Gao1,2, Zhiwen Su3, Longjun Liu3

  • 1Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an 710004, China.

Bioengineering (Basel, Switzerland)
|May 27, 2023
PubMed
Summary
This summary is machine-generated.

This study developed a 3D-printed wireless bite force device for diagnosing occlusal diseases. The intelligent sensor system shows promise for improving oral and maxillofacial disorder treatment.

Keywords:
engineeringmachine learningocclusal splintsosteoarthritisprintingstress

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Area of Science:

  • Biomedical Engineering
  • Dental Technology
  • Sensor Systems

Background:

  • Abnormal bite force is a significant risk factor for oral and maxillofacial disorders.
  • Current diagnostic methods lack effective solutions for assessing bite force accurately.
  • There is a clinical need for wireless bite force measurement devices.

Purpose of the Study:

  • To design and implement a prototype for a wireless bite force measurement device.
  • To evaluate the feasibility of using 3D printing and embedded stress sensors for bite force detection.
  • To explore quantitative measurement methods for occlusal diseases.

Main Methods:

  • Designed an open window carrier for the bite force detection device using 3D printing technology.
  • Integrated and embedded stress sensors into a hollow structure within the device carrier.
  • Developed a sensor system comprising pressure signal acquisition, main control module, and server terminal.

Main Results:

  • The 3D-printed device carrier demonstrated reasonable parameter metrics.
  • The experimental evaluation confirmed the feasibility of the proposed bite force measurement scheme.
  • The prototype system successfully implemented key components for intelligent bite force detection.

Conclusions:

  • An intelligent and wireless bite force device with an integrated stress sensor system is a promising approach.
  • This technology can aid in the diagnosis and treatment of occlusal diseases.
  • Further development involving machine learning for data processing is planned.