ArticleSensors (Basel, Switzerland)2020
Cost-Effective Wearable Indoor Localization and Motion Analysis via the Integration of UWB and IMU.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Conversion of Upper-Limb Inertial Measurement Unit Data to Joint Angles: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- The potential of AI inspired approaches for patient monitoring in drug development for Huntington's disease: capturing the digital exhaust for activities of daily living.Frontiers in molecular medicine · 2026Review
- Joint Function and Movement Variability During Daily Living Activities Performed Throughout the Home Setting: A Digital Twin Modeling Study.Sensors (Basel, Switzerland) · 2025Article
- Integrated UWB/MIMU Sensor System for Position Estimation towards an Accurate Analysis of Human Movement: A Technical Review.Sensors (Basel, Switzerland) · 2023Review
- IMU/UWB Fusion Method Using a Complementary Filter and a Kalman Filter for Hybrid Upper Limb Motion Estimation.Sensors (Basel, Switzerland) · 2023Article
- Microwave Devices for Wearable Sensors and IoT.Sensors (Basel, Switzerland) · 2023Review
- Flight Controller as a Low-Cost IMU Sensor for Human Motion Measurement.Sensors (Basel, Switzerland) · 2023Article
- Markerless Radio Frequency Indoor Monitoring for Telemedicine: Gait Analysis, Indoor Positioning, Fall Detection, Tremor Analysis, Vital Signs and Sleep Monitoring.Sensors (Basel, Switzerland) · 2022Review
- Experimental Evaluation of Sensor Fusion of Low-Cost UWB and IMU for Localization under Indoor Dynamic Testing Conditions.Sensors (Basel, Switzerland) · 2022Article
- A Low-Cost Foot-Placed UWB and IMU Fusion-Based Indoor Pedestrian Tracking System for IoT Applications.Sensors (Basel, Switzerland) · 2022Article
- Capturing Upper Body Kinematics and Localization with Low-Cost Sensors for Rehabilitation Applications.Sensors (Basel, Switzerland) · 2022Article
- Gait Recognition for Lower Limb Exoskeletons Based on Interactive Information Fusion.Applied bionics and biomechanics · 2022Review
- Wearable Sensors and Systems in the IoT.Sensors (Basel, Switzerland) · 2021Article
- High-Precision RTT-Based Indoor Positioning System Using RCDN and RPN.Sensors (Basel, Switzerland) · 2021Article
- Accuracy Evaluation of Selected Mobile Inspection Robot Localization Techniques in a GNSS-Denied Environment.Sensors (Basel, Switzerland) · 2020Article
- Local Bearing Estimation for a Swarm of Low-Cost Miniature Robots.Sensors (Basel, Switzerland) · 2020Article
- Physiological and Behavior Monitoring Systems for Smart Healthcare Environments: A Review.Sensors (Basel, Switzerland) · 2020Review
- Artificial intelligence approach for detecting and classifying abnormal behaviour in older adults using wearable sensors.Journal of rehabilitation and assistive technologies engineeringArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Wearable indoor localization can now find applications in a wide spectrum of fields, including the care of children and the elderly, sports motion analysis, rehabilitation medicine, robotics navigation, etc. Conventional inertial measurement unit (IMU)-based position estimation and radio signal indoor localization methods based on WiFi, Bluetooth, ultra-wide band (UWB), and radio frequency identification (RFID) all have their limitations regarding cost, accuracy, or usability, and a combination of the techniques has been considered a promising way to improve the accuracy. This investigation aims to provide a cost-effective wearable sensing solution with data fusion algorithms for indoor localization and real-time motion analysis. The main contributions of this investigation are: (1) the design of a wireless, battery-powered, and light-weight wearable sensing device integrating a low-cost UWB module-DWM1000 and micro-electromechanical system (MEMS) IMU-MPU9250 for synchronized measurement; (2) the implementation of a Mahony complementary filter for noise cancellation and attitude calculation, and quaternions for frame rotation to obtain the continuous attitude for displacement estimation; (3) the development of a data fusion model integrating the IMU and UWB data to enhance the measurement accuracy using Kalman-filter-based time-domain iterative compensations; and (4) evaluation of the developed sensor module by comparing it with UWB- and IMU-only solutions. The test results demonstrate that the average error of the integrated module reached 7.58 cm for an arbitrary walking path, which outperformed the IMU- and UWB-only localization solutions. The module could recognize lateral roll rotations during normal walking, which could be potentially used for abnormal gait recognition.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.