ArticleSensors (Basel, Switzerland)2021
Prediction of Lower Extremity Multi-Joint Angles during Overground Walking by Using a Single IMU with a Low Frequency Based on an LSTM Recurrent Neural Network.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 55 citations in OpenAlex.
- Concurrent validity of wearable IMUs for sagittal plane lower-limb range of motion during walking and estimated ground reaction forces: a systematic review and meta-analysis.Journal of orthopaedic surgery and research · 2025Pooled it
- Real-Time Prediction of Lower-Limb Joint Kinematics, Kinetics, and Ground Reaction Force Using Wearable Sensors and Machine Learning.Sensors (Basel, Switzerland) · 2026Article
- An IMU and sEMG dataset of induced stumble events during treadmill walking in transfemoral amputees.Scientific data · 2026Article
- A Motion Intention Recognition Method for Lower-Limb Exoskeleton Assistance in Ultra-High-Voltage Transmission Tower Climbing.Sensors (Basel, Switzerland) · 2026Article
- Long short-term attention memory (LSTAM): a global-feature-integrated model for joint moment prediction in human rehabilitation.Scientific reports · 2026Article
- Validity, Reliability and Interpretability of an IMU-Based System to Measure 3D Lower Limb Kinematics of Patients with Heterogeneous Gait Disorders.Sensors (Basel, Switzerland) · 2026Article
- Validity of Poststroke Gait Spatiotemporal and Joint Excursion Metrics Between Inertial Measurement Units and a Marker-Based System.Journal of applied biomechanics · 2025Article
- Bridging the Methodological Gap Between Inertial Sensors and Optical Motion Capture: Deep Learning as the Path to Accurate Joint Kinematic Modelling Using Inertial Sensors.Sensors (Basel, Switzerland) · 2025Article
- Validity of a Single Inertial Measurement Unit to Measure Hip Range of Motion During Gait in Patients Undergoing Total Hip Arthroplasty.Sensors (Basel, Switzerland) · 2025Article
- Use of Technologies for the Acquisition and Processing Strategies for Motion Data Analysis.Biomimetics (Basel, Switzerland) · 2025Review
- Gait Speed and Task Specificity in Predicting Lower-Limb Kinematics: A Deep Learning Approach Using Inertial Sensors.Mayo Clinic proceedings. Digital health · 2025Article
- Molecular Signaling Pathways and MicroRNAs in Bone Remodeling: A Narrative Review.Diseases (Basel, Switzerland) · 2024Review
- Machine Learning Based Abnormal Gait Classification with IMU Considering Joint Impairment.Sensors (Basel, Switzerland) · 2024Article
- Article
- Enhancing accuracy and convenience of golf swing tracking with a wrist-worn single inertial sensor.Scientific reports · 2024Article
- Estimation of Lower Limb Joint Angles and Joint Moments during Different Locomotive Activities Using the Inertial Measurement Units and a Hybrid Deep Learning Model.Sensors (Basel, Switzerland) · 2023Article
- Recurrent Neural Network Methods for Extracting Dynamic Balance Variables during Gait from a Single Inertial Measurement Unit.Sensors (Basel, Switzerland) · 2023Article
- Effect of Foot Orthoses on Angular Velocity of Feet.Sensors (Basel, Switzerland) · 2023Article
- Extended Application of Inertial Measurement Units in Biomechanics: From Activity Recognition to Force Estimation.Sensors (Basel, Switzerland) · 2023Review
- Criterion Validity of Linear Accelerations Measured with Low-Sampling-Frequency Accelerometers during Overground Walking in Elderly Patients with Knee Osteoarthritis.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
The joint angle during gait is an important indicator, such as injury risk index, rehabilitation status evaluation, etc. To analyze gait, inertial measurement unit (IMU) sensors have been used in studies and continuously developed; however, they are difficult to utilize in daily life because of the inconvenience of having to attach multiple sensors together and the difficulty of long-term use due to the battery consumption required for high data sampling rates. To overcome these problems, this study propose a multi-joint angle estimation method based on a long short-term memory (LSTM) recurrent neural network with a single low-frequency (23 Hz) IMU sensor. IMU sensor data attached to the lateral shank were measured during overground walking at a self-selected speed for 30 healthy young persons. The results show a comparatively good accuracy level, similar to previous studies using high-frequency IMU sensors. Compared to the reference results obtained from the motion capture system, the estimated angle coefficient of determination (R2) is greater than 0.74, and the root mean square error and normalized root mean square error (NRMSE) are less than 7° and 9.87%, respectively. The knee joint showed the best estimation performance in terms of the NRMSE and R2 among the hip, knee, and ankle joints.
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.