Skip to main navigation Skip to search Skip to main content

Optimal locations and computational frameworks of FSR and IMU sensors for measuring gait abnormalities

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Neuromuscular diseases cause abnormal joint movements and drastically alter gait patterns in patients. The analysis of abnormal gait patterns can provide clinicians with an in-depth insight into implementing appropriate rehabilitation therapies. Wearable sensors are used to measure the gait patterns of neuromuscular patients due to their non-invasive and cost-efficient characteristics. FSR and IMU sensors are the most popular and efficient options. When assessing abnormal gait patterns, it is important to determine the optimal locations of FSRs and IMUs on the human body, along with their computational framework. The gait abnormalities of different types and the gait analysis systems based on IMUs and FSRs have therefore been investigated. After studying a variety of research articles, the optimal locations of the FSR and IMU sensors were determined by analysing the main pressure points under the feet and prime anatomical locations on the human body. A total of seven locations (the big toe, heel, first, third, and fifth metatarsals, as well as two close to the medial arch) can be used to measure gate cycles for normal and flat feet. It has been found that IMU sensors can be placed in four standard anatomical locations (the feet, shank, thigh, and pelvis). A section on computational analysis is included to illustrate how data from the FSR and IMU sensors are processed. Sensor data is typically sampled at 100 Hz, and wireless systems use a range of microcontrollers to capture and transmit the signals. The findings reported in this article are expected to help develop efficient and cost-effective gait analysis systems by using an optimal number of FSRs and IMUs.
    Original languageEnglish
    Pages (from-to)e15210
    JournalHeliyon
    Volume9
    Issue number4
    DOIs
    Publication statusPublished - 4 Apr 2023

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Computational framework
    • Gait abnormalities
    • Measurement of gait
    • Sensor location

    Fingerprint

    Dive into the research topics of 'Optimal locations and computational frameworks of FSR and IMU sensors for measuring gait abnormalities'. Together they form a unique fingerprint.

    Cite this