ArticleSensors (Basel, Switzerland)2026
Impact of Gyroscope Integration, Sensor Placement, and Activity Granularity on Human Activity Recognition Performance.
Alejandro Castellanos, Antonio M López, Miguel Á Salinas, Juan C Álvarez, Diego Álvarez, Gonzalo García, Ángel Buendía-Romero, Asier Mañas, Raquel Bailón, Vicente Martín and 3 more
Abstract read
In one paragraphArticle in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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.
2 · The registryThe 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.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
13 authors.
Alejandro CastellanosMultisensor Systems and Robotics Research Group (SiMuR), Electrical Engineering Department, University of Oviedo, 33204 Gijón, Spain.ORCID 0000-0002-0934-6716 Antonio M LópezMultisensor Systems and Robotics Research Group (SiMuR), Electrical Engineering Department, University of Oviedo, 33204 Gijón, Spain.ORCID 0000-0002-5589-6954 Miguel Á SalinasMultisensor Systems and Robotics Research Group (SiMuR), Electrical Engineering Department, University of Oviedo, 33204 Gijón, Spain.ORCID 0009-0001-9507-6491 Juan C ÁlvarezMultisensor Systems and Robotics Research Group (SiMuR), Electrical Engineering Department, University of Oviedo, 33204 Gijón, Spain.ORCID 0000-0002-8910-4855 Diego ÁlvarezMultisensor Systems and Robotics Research Group (SiMuR), Electrical Engineering Department, University of Oviedo, 33204 Gijón, Spain.ORCID 0000-0003-0395-2712 Gonzalo GarcíaMultisensor Systems and Robotics Research Group (SiMuR), Electrical Engineering Department, University of Oviedo, 33204 Gijón, Spain.ORCID 0009-0000-0920-3099 Ángel Buendía-RomeroGENUD Toledo Research Group, Faculty of Sports Sciences, Universidad de Castilla-La Mancha, 45071 Toledo, Spain.ORCID 0000-0001-7044-8191 Asier MañasGENUD Toledo Research Group, Faculty of Sports Sciences, Universidad de Castilla-La Mancha, 45071 Toledo, Spain.ORCID 0000-0002-1683-1365 Raquel BailónBiomedical Signal Interpretation and Computational Simulation Research Group (BSICoS), University of Zaragoza, Campus Río Ebro, I+D+i Building-C/Mariano Esquillor, S/N, 50018 Zaragoza, Spain.ORCID 0000-0003-1272-0550 Vicente MartínGene-Environment-Health Interactions Research Group (GIIGAS), Department of Biomedical Sciences, Faculty of Veterinary Science, University of León, 24071 León, Spain.ORCID 0000-0003-0552-2804 Ana Carbonell-BaezaCTS-1038 eMpOwering health by physical actiVity, Exercise and nutrITion Research Group (MOVE-IT), Department of Physical Education, Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), Universidad de Cádiz, 11002 Cadiz, Spain.ORCID 0000-0003-1762-2925 Verónica Cabanas-SánchezDepartment of Preventive Medicine and Public Health, School of Medicine, Universidad Autonoma de Madrid, 28029 Madrid, Spain.ORCID 0000-0003-1235-3535 David Martinez-GomezDepartment of Preventive Medicine and Public Health, School of Medicine, Universidad Autonoma de Madrid, 28029 Madrid, Spain.ORCID 0000-0002-9598-019X Funding
Agencia de Investigación e Innovación de Castilla-La-Mancha Instituto de Investigación Sanitaria de Castilla-La Mancha-IDISCAM (TEC2022-007).European Union FEDER funds (2025-GRIN-38408).Gobierno del Principado de Asturias Severo Ochoa predoctoral fellowship program.Instituto de Salud Carlos III Project PI23/00663 (R&D&I Projects in Health).Instituto de Salud Carlos III Project PMP22/00028 (Next Generation EU funds, Mechanism for Recovery and Resilience).Ministerio de Ciencia, Innovación y Universidades Postdoctoral contract (JDC2023-052593-I, funded by MCIU/AEI/10.13039/501100011033).University of Castilla-La Mancha CIBERFES (CB16/10/00477), Plan Propio de Investigación.
6 · The paper itselfAbstract
This study systematically evaluates the impact of sensor configuration, body location, classification granularity, and model choice on inertial-based human activity recognition in a laboratory dataset aligned with the Spanish IMPaCT cohort design. Data were collected from 85 participants instrumented with thigh-, wrist-, and hip-mounted inertial measurement units over a structured protocol of 13 semi-structured daily activities, a resting phase and a structured activity. After manual correction of timestamp drift, signals were segmented into overlapping 10-s windows and analyzed using convolutional neural networks, Random Forest, and XGBoost classifiers.Two classification targets were defined: fine-grained recognition of 15 laboratory-controlled activities and coarse-grained classification into four MET-based intensity levels. Results showed that classification granularity is the primary determinant of performance (F=224.85,
Indexed as
Human ActivitiesAccelerometryAdultClassification AlgorithmsConvolutional Neural NetworksFemaleHumansMaleRandom Forestconvolutional neural networksdecision tree-based modelshuman activity recognitioninertial measurement unitmachine learningphysical activity
Identifiers
PMID42356654
PMCPMC13306829
What OpenQuestion holds
Textmetadata
LicenceCC BY
Read underepoch 390