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Smart Shoes: Sensors in Footwear
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Smart Shoes: Sensors in Footwear

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 3248

Special Issue Editors

Dr. Simon Taylor

E-Mail Website
Guest Editor
Victoria University Melbourne, Institute for Health and Sport, Melbourne, Australia
Interests: gait control; gait biomechanics; smart shoes; gait biofeedback
Dr. Daniel Lai

E-Mail Website
Guest Editor
Smart Electronics Systems Research Group, College of Engineering and Science, Victoria University, Melbourne, Australia
Interests: new sensing, communication technologies and computational intelligence for applications in health and sports
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The quality of life and health of the human society is dependent on healthy mobility, independence, and the autonomy of its citizens. Recording and monitoring an individual’s mobility in real time, and in the real-world context, is considered a valid surrogate for health assessment. Advances in sensor technology applied to footwear design are one field of research that is considered a major future contributor to the Internet of Health Things (IoHT). An intelligent smart shoe can serve as an unobtrusive wearable computing system that enables the advancement of healthy movement. While there are a range of issues that are progressing this field forward—which includes technical and medical requirements, data communication, user adherence requirements, and manufacturing—this edition addresses all aspects related to the hardware and software associated with sensor integration into the smart shoe.

Dr. Simon Taylor
Dr. Daniel Lai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Assistive footwear
  • Sensor-based gait analysis
  • Smart shoe
  • Machine learning
  • Activity recognition
  • Inertial sensor
  • Foot pressure

Published Papers (1 paper)

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Research

12 pages, 989 KiB  
Article
Measurement of Physical Activity by Shoe-Based Accelerometers—Calibration and Free-Living Validation
by Jonatan Fridolfsson, Daniel Arvidsson and Stefan Grau
Sensors 2021, 21(7), 2333; https://doi.org/10.3390/s21072333 - 26 Mar 2021
Cited by 2 | Viewed by 2288
Abstract
There is conflicting evidence regarding the health implications of high occupational physical activity (PA). Shoe-based accelerometers could provide a feasible solution for PA measurement in workplace settings. This study aimed to develop calibration models for estimation of energy expenditure (EE) from shoe-based accelerometers, [...] Read more.
There is conflicting evidence regarding the health implications of high occupational physical activity (PA). Shoe-based accelerometers could provide a feasible solution for PA measurement in workplace settings. This study aimed to develop calibration models for estimation of energy expenditure (EE) from shoe-based accelerometers, validate the performance in a workplace setting and compare it to the most commonly used accelerometer positions. Models for EE estimation were calibrated in a laboratory setting for the shoe, hip, thigh and wrist worn accelerometers. These models were validated in a free-living workplace setting. Furthermore, additional models were developed from free-living data. All sensor positions performed well in the laboratory setting. When the calibration models derived from laboratory data were validated in free living, the shoe, hip and thigh sensors displayed higher correlation, but lower agreement, with measured EE compared to the wrist sensor. Using free-living data for calibration improved the agreement of the shoe, hip and thigh sensors. This study suggests that the performance of a shoe-based accelerometer is similar to the most commonly used sensor positions with regard to PA measurement. Furthermore, it highlights limitations in using the relationship between accelerometer output and EE from a laboratory setting to estimate EE in a free-living setting. Full article
(This article belongs to the Special Issue Smart Shoes: Sensors in Footwear)
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