Design and implementation of a BSN-based system for plantar health evaluation with exercise load quantification

• Main Authors: Yang Wang, Zhiwen Liu, Jian Yang, Shaodong Ma
• Format: Article
• Language: English
• Published: BMC 2017-08-01
• Series: BioMedical Engineering OnLine
• Subjects: Plantar pressure; Exercise load quantification; Heart rate; Strike frequency
• Online Access: http://link.springer.com/article/10.1186/s12938-017-0389-9

Abstract Background Plantar pressure measurement has become increasingly useful in the evaluation of plantar health conditions thanks to the recent progression in sensing technology. Due to the large volume and high energy consumption of monitoring devices, traditional systems for plantar pressure measurement are only focused on static or short-term dynamic monitoring. It makes them inappropriate for early detections of plantar symptoms usually presented in long-term activities. Methods A prototype of monitoring system based on body sensor network (BSN) is proposed for quantitative assessment of plantar conditions. To further assess the severity of plantar symptoms which can be reflected from the pressure distribution in motion status, an approach to conjoint analysis of pressure distribution and exercise load quantification based on the strike frequency (SF) and heart rate (HR) is also proposed. Results An examination was tested on 30 subjects to verify the capabilities of the proposed system. The estimated correlation rate with reference devices ( $$r>0.9$$ r > 0.9 ) and error rate on the average ( $$R_{AE}<0.08$$ R A E < 0.08 ) of HR and SF indicated equal measuring capabilities as the existing commercial products . Comprised of the conjoint analysis based on HR and SF, the proposed method of exercise load quantification was examined on all subjects’ recordings. Conclusions A prototype of an innovative BSN-based bio-physiological measurement system has been implemented for the long-term monitoring and early evaluation of plantar condition. The experimental results indicated that the proposed system has a great potential value in the applications of long-term plantar health monitoring and evaluation.