Recent advances in pedestrian inertial navigation based on smartphone: A review

Q Wang, M Fu, J Wang, H Luo, L Sun, Z Ma… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Indoor location-based service is a hot research topic whose application market size is
expected to grow from 41 billion by 2022 and 58 billion by 2023. As a portable …

Recent advances in pedestrian navigation activity recognition: a review

Q Wang, H Luo, J Wang, L Sun, Z Ma… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Pedestrian navigation activity recognition (PNAR) has a significant impact on positioning
and tracking performance. Smartphone-based PNAR utilizes measurements from sensors …

Accurate ambulatory gait analysis in walking and running using machine learning models

H Zhang, Y Guo, D Zanotto - IEEE Transactions on Neural …, 2019 - ieeexplore.ieee.org
Wearable sensors have been proposed as alternatives to traditional laboratory equipment
for low-cost and portable real-time gait analysis in unconstrained environments. However …

Boosting inertial-based human activity recognition with transformers

Y Shavit, I Klein - IEEE Access, 2021 - ieeexplore.ieee.org
Activity recognition problems such as human activity recognition and smartphone location
recognition can improve the accuracy of different navigation or healthcare tasks, which rely …

Pedestrian dead reckoning based on walking pattern recognition and online magnetic fingerprint trajectory calibration

Q Wang, H Luo, H **ong, A Men, F Zhao… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
With the explosive development of pervasive computing and the Internet of Things (IoT),
indoor positioning and navigation have attracted immense attention over recent years …

PDRNet: A deep-learning pedestrian dead reckoning framework

O Asraf, F Shama, I Klein - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
Pedestrian dead reckoning is a well-known approach for indoor navigation. There, the
smartphone's inertial sensors readings are used to determine the user position by utilizing …

StepNet—Deep learning approaches for step length estimation

I Klein, O Asraf - IEEE Access, 2020 - ieeexplore.ieee.org
The case of a user walking with a smartphone in an indoor environment is considered.
Instead of using traditional pedestrian dead reckoning approaches to estimate the user step …

Lidr: Visible-light-communication-assisted dead reckoning for accurate indoor localization

B Hussain, Y Wang, R Chen… - IEEE Internet of …, 2022 - ieeexplore.ieee.org
Pedestrian dead reckoning (PDR) is an inertial navigation system that relies on smartphone
sensors for estimating a pedestrian's step movements. However, such systems suffer from …

A deep learning approach for foot trajectory estimation in gait analysis using inertial sensors

V Guimarães, I Sousa, MV Correia - Sensors, 2021 - mdpi.com
Gait performance is an important marker of motor and cognitive decline in older adults. An
instrumented gait analysis resorting to inertial sensors allows the complete evaluation of …

A bidirectional LSTM for estimating dynamic human velocities from a single IMU

T Feigl, S Kram, P Woller, RH Siddiqui… - 2019 International …, 2019 - ieeexplore.ieee.org
The main challenge in estimating human velocity from noisy Inertial Measurement Units
(IMUs) are the errors that accumulate by integrating noisy accelerometer signals over a long …