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. 2017 Aug 3;16(1):98.
doi: 10.1186/s12938-017-0389-9.

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

Yang Wang  1 , Zhiwen Liu  2 , Jian Yang  3 , Shaodong Ma  3
Affiliations

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

Yang Wang et al. Biomed Eng Online. .

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 ([Formula: see text]) and error rate on the average ([Formula: see text]) 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.

Keywords: Exercise load quantification; Heart rate; Plantar pressure; Strike frequency.

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Figures

Fig. 1
Fig. 1
Framework of the proposed BSN-based system.
Fig. 2
Fig. 2
Architecture of the mobile client.
Fig. 3
Fig. 3
Sensor bands of the mobile client. a and c are the wrist-type band and ankle-type band, respectively. b and d give examples of wearing methods for (a) and (c), respectively.
Fig. 4
Fig. 4
Software architecture of sensor bands.
Fig. 5
Fig. 5
Algorithm of HR estimation.
Fig. 6
Fig. 6
Algorithm of SF estimation.
Fig. 7
Fig. 7
Architecture of the applications on smart phones.
Fig. 8
Fig. 8
Software interfaces of mobile application on smart phones. a user login; b configuration; c list of searched devices; d upload information.
Fig. 9
Fig. 9
An example of synchronous period selection.
Fig. 10
Fig. 10
r and RAE of HR and SF estimation on all subjects’ recordings. a r; b RAE.
Fig. 11
Fig. 11
Box plot of scores in different motion status.
Fig. 12
Fig. 12
Distribution of plantar pressure in different motion status. a walking status; b jogging status.
Fig. 13
Fig. 13
Comparison of PPV on the left foot among S2, S6 and S15. a and b illustrate the PPV of S2, b and e, c and f are the results of S6 and S15, respectively.
Fig. 14
Fig. 14
Comparison of Pnth with different load exercise.
See this image and copyright information in PMC

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References

    1. Wafai L, Zayegh A, Woulfe J, Aziz SM, Begg R. Identification of foot pathologies based on plantar pressure asymmetry. Sensors. 2015;15(8):20392–20408. doi: 10.3390/s150820392. - DOI - PMC - PubMed
    1. Ledoux WR, Shofer JB, Cowley MS, Ahroni JH, Cohen V, Boyko EJ. Diabetic foot ulcer incidence in relation to plantar pressure magnitude and measurement location. J Diabetes Complicat. 2013;27(6):621–626. doi: 10.1016/j.jdiacomp.2013.07.004. - DOI - PMC - PubMed
    1. Koldenhoven RM, Feger MA, Fraser JJ, Saliba S, Hertel J. Surface electromyography and plantar pressure during walking in young adults with chronic ankle instability. Knee Surg Sports Traumatol Arthrosc. 2016;24(4):1060–1070. doi: 10.1007/s00167-016-4015-3. - DOI - PubMed
    1. Sacco IC, Hamamoto AN, Tonicelli LM, Watari R, Ortega NR, Sartor CD. Abnormalities of plantar pressure distribution in early, intermediate, and late stages of diabetic neuropathy. Gait Posture. 2014;40(4):570–574. doi: 10.1016/j.gaitpost.2014.06.018. - DOI - PubMed
    1. Mann R, Malisoux L, Urhausen A, Meijer K, Theisen D. Plantar pressure measurements and running-related injury: a systematic review of methods and possible associations. Gait Posture. 2016;47:1–9. doi: 10.1016/j.gaitpost.2016.03.016. - DOI - PubMed