ArticleSensors (Basel, Switzerland)2022
How Validation Methodology Influences Human Activity Recognition Mobile Systems.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis of AI posture recognition for work-related musculoskeletal disorders prevention in occupational activities: comparison between untransformed, logit and Freeman-Tukey transformed performance.Frontiers in artificial intelligence · 2026Pooled it
- Ultrasonic and Resistivity Sensor Fusion for Discriminating Gas Injection Rates.Sensors (Basel, Switzerland) · 2026Article
- Unified time series classification framework for explainable artificial intelligence.Scientific reports · 2026Article
- Wearable Sensor-Based Human Activity Recognition: Performance and Interpretability of Dynamic Neural Networks.Sensors (Basel, Switzerland) · 2025Article
- Strategies for Reliable Stress Recognition: A Machine Learning Approach Using Heart Rate Variability Features.Sensors (Basel, Switzerland) · 2024Article
- Recognition of sports and daily activities through deep learning and convolutional block attention.PeerJ. Computer science · 2024Article
- Integrating Surrounding Vehicle Information for Vehicle Trajectory Representation and Abnormal Lane-Change Behavior Detection.Sensors (Basel, Switzerland) · 2023Article
- Hybrid convolution neural network with channel attention mechanism for sensor-based human activity recognition.Scientific reports · 2023Article
- Explaining and Visualizing Embeddings of One-Dimensional Convolutional Models in Human Activity Recognition Tasks.Sensors (Basel, Switzerland) · 2023Article
- Learning-Based Motion-Intention Prediction for End-Point Control of Upper-Limb-Assistive Robots.Sensors (Basel, Switzerland) · 2023Article
- Sensor-Based Human Activity and Behavior Research: Where Advanced Sensing and Recognition Technologies Meet.Sensors (Basel, Switzerland) · 2022Article
- Comparing Handcrafted Features and Deep Neural Representations for Domain Generalization in Human Activity Recognition.Sensors (Basel, Switzerland) · 2022Article
- Explaining One-Dimensional Convolutional Models in Human Activity Recognition and Biometric Identification Tasks.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
In this article, we introduce explainable methods to understand how Human Activity Recognition (HAR) mobile systems perform based on the chosen validation strategies. Our results introduce a new way to discover potential bias problems that overestimate the prediction accuracy of an algorithm because of the inappropriate choice of validation methodology. We show how the SHAP (Shapley additive explanations) framework, used in literature to explain the predictions of any machine learning model, presents itself as a tool that can provide graphical insights into how human activity recognition models achieve their results. Now it is possible to analyze which features are important to a HAR system in each validation methodology in a simplified way. We not only demonstrate that the validation procedure
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