2 results match your criteria: "2School of Life Science and TechnologyXidian UniversityXi'an710126China.[Affiliation]"

Objective: Non-invasive respiration detection methods are of great value to healthcare applications and disease diagnosis with their advantages of minimizing the patient's physical burden and lessen the requirement of active cooperation of the subject. This method avoids extra preparations, reduces environmental constraints, and strengthens the possibility of real-time respiratory detection. Furthermore, identifying abnormal breathing patterns in real-time is necessary for the diagnosis and monitoring of possible respiratory disorders.

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Article Synopsis
  • Parkinsonian gait significantly impacts the quality of life for individuals with shaking palsy, necessitating a reliable detection system.
  • The proposed system utilizes S-band perception techniques to differentiate between abnormal and normal walking patterns by analyzing wireless signal variations.
  • Through data preprocessing, principal component analysis, and a support vector machine classification algorithm, the system boasts over 90% accuracy in detecting Parkinsonian gait non-invasively.
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