ArticleSensors (Basel, Switzerland)2018
On-Body Sensor Positions Hierarchical Classification.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Inertial Sensor Reliability and Validity for Static and Dynamic Balance in Healthy Adults: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- Walking and scuba diving assisted amphibious exoskeleton robots: the designing of power assist control and myoelectricity based wearers' fatigue evaluation.Frontiers in neuroscience · 2024Article
- Spatial and Temporal Gait Characteristics in Patients Admitted to a Neuro-Rehabilitation Department with Age-Related White Matter Changes: A Gait Analysis and Clinical Study.Neurology international · 2023Article
- Automatic Body Segment and Side Recognition of an Inertial Measurement Unit Sensor during Gait.Sensors (Basel, Switzerland) · 2023Article
- A global bibliometric and visualized analysis of gait analysis and artificial intelligence research from 1992 to 2022.Frontiers in robotics and AI · 2023Article
- An Intelligent Clinical Decision Support System for Predicting Acute Graft-versus-host Disease (aGvHD) following Allogeneic Hematopoietic Stem Cell Transplantation.Journal of biomedical physics & engineering · 2021Article
- New Position Candidate Identification via Clustering toward an Extensible On-Body Smartphone Localization System.Sensors (Basel, Switzerland) · 2021Article
- Human Activities and Postures Recognition: From Inertial Measurements to Quaternion-Based Approaches.Sensors (Basel, Switzerland) · 2019Article
- A Human Activity Recognition Algorithm Based on Stacking Denoising Autoencoder and LightGBM.Sensors (Basel, Switzerland) · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Many motion sensor-based applications have been developed in recent years because they provide useful information about daily activities and current health status of users. However, most of these applications require knowledge of sensor positions. Therefore, this research focused on the problem of detecting sensor positions. We collected standing-still and walking sensor data at various body positions from ten subjects. The offset values were removed by subtracting the sensor data of standing-still phase from the walking data for each axis of each sensor unit. Our hierarchical classification technique is based on optimizing local classifiers. Many common features are computed, and informative features are selected for specific classifications. In this approach, local classifiers such as arm-side and hand-side discriminations yielded F1-scores of 0.99 and 1.00, correspondingly. Overall, the proposed method achieved an F1-score of 0.81 and 0.84 using accelerometers and gyroscopes, respectively. Furthermore, we also discuss contributive features and parameter tuning in this analysis.
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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.